Scipedia: Collection of open articles in transport research

Environmental Impact Assessment of the Transportation Sector and Hybrid Vehicle Implications in Palestine

Scipedia content — Fri, 12 Feb 2021 12:26:34 +0100

During the last two decades, the development of sustainable transportation systems has been highlighted as a key element in solving environmental problems related to climate change and impacts on greenhouse gases. Globally, the transportation sector has become one of the main contributors to these environmental problems. Thus, the environmental impact assessment of this sector and the implications of new vehicle technologies have begun to be considered as first steps for any long-term future strategies in this sector. In Palestine, the lack of environmental data related to the transportation sector and the absence of studies that address the new vehicle technologies (such as hybrid vehicles) and their future implications make it difficult to set up any future strategies or plans. In this study, the current and the future environmental impacts of the transportation sector have been assessed, and the future implications of hybrid vehicles have been determined. The gross domestic product (GDP), population, and the number of vehicles for the period 1994–2018 have been used to develop an auto regressive integrated moving average (ARIMA) prediction model for the future number of vehicles. Then, the total traveled kilometers and the total consumed fuels (by diesel and gasoline vehicles) have been predicted. After that, the current and future (2020 and 2030) greenhouse gas (GHG) emissions, including CO"sub"2"/sub", N"sub"2"/sub"O, and CH"sub"4"/sub", have been estimated. Finally, the future implications of hybrid vehicles, based on two scenarios (10% and 20% hybrid vehicles) have been estimated. The results have showed that the estimated CO"sub"2"/sub", N"sub"2"/sub"O, and CH"sub"4"/sub" emissions from the transportation sector in 2020 are 4,842,164.5, 213.8, and 445.8 tons, which are very high, and even much higher than the total national emissions of 2014 (the only officially available data). Moreover, in 2030, replacing 20% of internal combustion engine vehicles (ICEVs) by hybrid vehicles would lead to 4.66% and 13.31% reductions in CO"sub"2"/sub" and N"sub"2"/sub"O, respectively, as compared to 100% ICEVs, while the CH"sub"4 "/sub"emissions will increase. However, the overall CO"sub"2"/sub"-equivalent will decrease by 5%; therefore, a more sustainable transport system will be achieved.

Document type: Article

A Fail-Operational Control Architecture Approach and Dead-Reckoning Strategy in Case of Positioning Failures

Scipedia content — Fri, 12 Feb 2021 12:26:53 +0100

Presently, in the event of a failure in Automated Driving Systems, control architectures rely on hardware redundancies over software solutions to assure reliability or wait for human interaction in takeover requests to achieve a minimal risk condition. As user confidence and final acceptance of this novel technology are strongly related to enabling safe states, automated fall-back strategies must be assured as a response to failures while the system is performing a dynamic driving task. In this work, a fail-operational control architecture approach and dead-reckoning strategy in case of positioning failures are developed and presented. A fail-operational system is capable of detecting failures in the last available positioning source, warning the decision stage to set up a fall-back strategy and planning a new trajectory in real time. The surrounding objects and road borders are considered during the vehicle motion control after failure, to avoid collisions and lane-keeping purposes. A case study based on a realistic urban scenario is simulated for testing and system verification. It shows that the proposed approach always bears in mind both the passenger&rsquo

s safety and comfort during the fall-back maneuvering execution.

Document type: Article

Multimode Traffic Travel Behavior Characteristics Analysis and Congestion Governance Research

Scipedia content — Fri, 12 Feb 2021 12:28:20 +0100

The rapid aggregation of modern urban population and the rapid growth of car travel lead to traffic congestion, environmental pollution, and other problems. In view of the limited land resources in our country, it is impractical to meet residents’ travel demand by blindly increasing traffic supply. Therefore, addressing the urban road congestion problem for sustainable development of modern cities, the paper makes research on residents’ travel behavior characteristics and travel preference under the condition of multimodal transportation to formulate reasonable traffic demand management strategy for the guide on public traffic demand, bus priority strategy, and congestion management. The operation characteristic of each transportation mode is analyzed by comparing its related traffic and economic characteristics. Multimode traffic choice behavior is discussed by establishing multiple logistic regression models to analyze the main influencing factors to travelers’ social and economic attributes, travel characteristics, and preference based on travel survey data of urban residents. The paper proposes the development of an urban public transportation system and travelling mode shift from cars to public transportation as reasonable travel structure for congestion management and sustainable development of modern cities.

Document type: Article

Smart Cities Oriented Project Planning and Evaluation Methodology Driven by Citizen Perception—IoT Smart Mobility Case

Scipedia content — Fri, 12 Feb 2021 12:29:09 +0100

Smart Cities empower progress through technology integration directed with a strategic approach to sustainable development and citizen well-being. The creation of solid strategic planning boosts the development of infrastructure, innovation, and technology. However, the above can be compromised if citizens are not properly involved; therefore, it is relevant to enhance citizen participation when a new Smart City project appears on the horizon. This work presents a Smart Cities Oriented Project Planning and Evaluation (SCOPPE) Methodology that combines the citizen participation and the Minimum Viable Product creation through adaptive project management. Moreover, since the smart mobility projects represent the first step towards a Smart City, a case of study of an Intelligent Parking System (SEI-UVM) is presented following the SCOPPE Methodology. The application’s steps results lead us to key and useful information when defining, designing, and implementing the minimum viable product of the cornerstone device of the SEI-UVM: the Smart Vehicle Presence Sensor (SPIN-V). It is worthwhile to mention that the proposed SCOPPE Methodology could be extended to any Smart City project.

Document type: Article

PDMS-FBG-based fiber optic system for traffic monitoring in urban areas

Scipedia content — Fri, 12 Feb 2021 12:32:48 +0100

This article introduces fiber Bragg grating (FBG) system for monitoring selected traffic flow parameters in urban areas. The system is able to monitor traffic density or speed of cars driving in single lane. The proposed system consists of five Bragg gratings encapsulated in Polydimethylsiloxane polymer and is characterized by easy and inexpensive installation in the milled upper layer of the road covered with an asphalt mixture. The results of first operational tests presented in this study include 3978 passing vehicles of various specifications. The system's vehicle detection success rate is 99.62%. And further, a mean absolute error 1.35 kph and a relative error 2.62% when measuring vehicle speed. Web of Science 8 127658 127648

Document type: Article

Visualizing the Intellectual Structure and Evolution of Intelligent Transportation Systems: A Systematic Analysis of Research Themes and Trends

Scipedia content — Fri, 12 Feb 2021 12:33:24 +0100

ording to the "i"United Nations"/i", 70% of the world’s population will live in cities by 2050. This growth will be reflected in the demand for better services that should be adjusted to the collective and individual needs of the population. Governments and organizations are working on defining and implementing strategies that will enable them to respond to these challenges. The main challenges are related to transport and its management, considering transportation as a core issue in the economy, sustainability, and development of the regions. In this way, the Intelligent Transportation Systems (ITS) play a key role in the response to these scenarios, being that they are the framework where the new hardware and software tools are integrated, allowing an efficient development of transportation systems management, attending to aspects such as: traffic management, communications between vehicles and infrastructures, and security, among others. Nevertheless, the concept of ITS evolves rapidly so it is necessary to understand its evolution. To do that, the current research develops a thematic analysis of ITS in literature, evaluating the intellectual structure and its evolution using "i"SciMAT"/i", quantifying the main bibliometric performance indicators, and identifying the main research areas, authors, journals, and countries. To this purpose, the publications related to ITS from 1993 to 2019 available in the "i"Web of Science (WoS) Core Collection"/i" were retrieved (7649 publications) and analyzed. Finally, one of the main results is the latest research themes map of ITS, considering its intellectual structure, evolution, and relationship. It assists in the definition and implementation of strategies, the identification of the scientific, academic, and business opportunities, and future research lines to consolidate the role of ITS in the new city models.

Document type: Article

Data Analysis for Self-Driving Vehicles in Intelligent Transportation Systems

Scipedia content — Fri, 12 Feb 2021 12:35:24 +0100

International audience

Document type: Article

Research on the Influence of a High-Speed Railway on the Spatial Structure of the Western Urban Agglomeration Based on Fractal Theory—Taking the Chengdu–Chongqing Urban Agglomeration as an Example

Scipedia content — Fri, 12 Feb 2021 12:37:06 +0100

By shortening the transportation time between cities, high-speed rail shortens the spatial distance between cities and exerts a far-reaching influence on urban agglomerations’ spatial structures. In order to explore the influence of high-speed rail on the spatial reconstruction of an urban agglomeration in western China, this paper employs fractal theory to compare and analyze the spatial structure evolution of the Chengdu–Chongqing urban agglomeration in western China before and after the opening of a high-speed railway. The results show that after the completion of the high-speed railway, the intercity accessibility is improved. The Chengdu–Chongqing urban agglomeration’s spatial distribution shows a decreasing density from the central city to the surrounding areas. Furthermore, the urban system presents a trend of an agglomeration distribution. Therefore, strengthening the construction of high-speed rail channels between primary and medium-sized cities, as well as accelerating the construction of intercity railway networks and rapid transportation systems based on high-speed rail cities, would help develop urban agglomerations in western China.

Document type: Article

An Interacting Multiple Model Approach for Target Intent Estimation at Urban Intersection for Application to Automated Driving Vehicle

Scipedia content — Fri, 12 Feb 2021 12:37:28 +0100

Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms.

Document type: Article

Adaptive Traffic Signal Control Model on Intersections Based on Deep Reinforcement Learning

Scipedia content — Fri, 12 Feb 2021 12:38:30 +0100

Controlling traffic signals to alleviate increasing traffic pressure is a concept that has received public attention for a long time. However, existing systems and methodologies for controlling traffic signals are insufficient for addressing the problem. To this end, we build a truly adaptive traffic signal control model in a traffic microsimulator, i.e., “Simulation of Urban Mobility” (SUMO), using the technology of modern deep reinforcement learning. The model is proposed based on a deep "jats:italic"Q"/jats:italic"-network algorithm that precisely represents the elements associated with the problem: agents, environments, and actions. The real-time state of traffic, including the number of vehicles and the average speed, at one or more intersections is used as an input to the model. To reduce the average waiting time, the agents provide an optimal traffic signal phase and duration that should be implemented in both single-intersection cases and multi-intersection cases. The co-operation between agents enables the model to achieve an improvement in overall performance in a large road network. By testing with data sets pertaining to three different traffic conditions, we prove that the proposed model is better than other methods (e.g., "jats:italic"Q"/jats:italic"-learning method, longest queue first method, and Webster fixed timing control method) for all cases. The proposed model reduces both the average waiting time and travel time, and it becomes more advantageous as the traffic environment becomes more complex.

Document type: Article

CO3D MISSION DIGITAL SURFACE MODEL PRODUCTION PIPELINE

Scipedia content — Fri, 12 Feb 2021 12:40:04 +0100

Abstract. Earth Observation (EO) remote sensing missions are producing an increasing volume of data due to higher spatial and spectral resolutions, and higher frequency of acquisitions. Thus, in order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made. Since mid-2019, CNES in partnership with Airbus Defense & Space, has started a new High Resolution Optical EO mission dedicated to very high resolution 3D observation called CO3D (“Constellation Optique 3D”). To achieve those objectives, a new image processing pipeline prototype is being developed taking in consideration the lessons learned from the previous studies. The paper will introduce this new image processing pipeline, the processing paradigms used to take advantage of big data technologies and the results of production benchmarks at a large scale. The on-going works to optimize the processing pipeline and Cloud cluster will be also discussed.

Document type: Article

Path Planning for Autonomous Vehicle Based on a Two-Layered Planning Model in Complex Environment

Scipedia content — Fri, 12 Feb 2021 12:41:48 +0100

The autonomous vehicle consists of perception, decision-making, and control system. The study of path planning method has always been a core and difficult problem, especially in complex environment, due to the effect of dynamic environment, the safety, smoothness, and real-time requirement, and the nonholonomic constraints of vehicle. To address the problem of travelling in complex environments which consists of lots of obstacles, a two-layered path planning model is presented in this paper. This method includes a high-level model that produces a rough path and a low-level model that provides precise navigation. In the high-level model, the improved Bidirectional Rapidly-exploring Random Tree (Bi-RRT) based on the steering constraint is used to generate an obstacle-free path while satisfying the nonholonomic constraints of vehicle. In low-level model, a Vector Field Histogram- (VFH-) guided polynomial planning algorithm in Frenet coordinates is introduced. Based on the result of VFH, the aim point chosen from improved Bi-RRT path is moved to the most suitable location on the basis of evaluation function. By applying quintic polynomial in Frenet coordinates, a real-time local path that is safe and smooth is generated based on the improved Bi-RRT path. To verify the effectiveness of the proposed planning model, the real autonomous vehicle has been placed in several driving scenarios with different amounts of obstacles. The two-layered real-time planning model produces flexible, smooth, and safe paths that enable the vehicle to travel in complex environment.

Document type: Article

A Novel Surface Inset Permanent Magnet Synchronous Motor for Electric Vehicles

Scipedia content — Fri, 12 Feb 2021 12:43:04 +0100

Aiming to successfully meet the requirements of a large output torque and a wide range of flux weakening speed expansion in permanent magnet synchronous motors (PMSM) for electric vehicles, a novel surface insert permanent magnet synchronous motor (SIPMSM) is developed. The method of notching auxiliary slots between the magnetic poles in the rotor and unequal thickness magnetic poles is proposed to improve the performance of the motor. By analyzing the magnetic circuit characteristics of the novel SIPMSM, the notching auxiliary slots between the adjacent magnetic poles can affect the q-axis inductance, and the shape of magnetic pole effects the d-axis inductance of the motor. The combined action of the two factors not only weakens the cogging torque, but also improves the flux weakening capability of the motor. In this paper, the response surface methodology (RSM) is used to establish a mathematical model of the relationship between the structural parameters of the motor and the optimization objectives, and the optimal design of the motor is completed by solving the mathematical model. Experimental validation has been conducted to show the correctness and effectiveness of the proposed SIPMSM.

Document type: Article

Transient Phenomena Generated in Emptying Operations in Large-Scale Hydraulic Pipelines

Scipedia content — Fri, 12 Feb 2021 12:47:31 +0100

Air pockets generated during emptying operations in pressurized hydraulic systems cause significant pressure drops inside pipes. To avoid these sudden pressure changes, one of the most widely used methods involves the installation of air valves along the pipeline route. These elements allow air exchange between the exterior and the interior of the pipe, which alleviates the pressure drops produced and thus prevents possible breaks or failures in the structure of the installation. This study uses a mathematical model previously validated by the authors in smaller installations to simulate all hydraulic variables involved in emptying processes over time. The purpose of these simulations is the validation of the mathematical model in real large-scale installations, and to do this, the results obtained with the mathematical model are compared with actual measurements made by the partner company. The hydraulic system selected for the study is a pipeline with a nominal diameter of 400 mm and a total length of 1020 m. The results obtained from the mathematical model show great similarity with the experimental measurements, thus validating the model for emptying large pipes.

Document type: Article

Standardized Test Procedure for External Human–Machine Interfaces of Automated Vehicles

Scipedia content — Fri, 12 Feb 2021 12:48:45 +0100

Research on external human&ndash

machine interfaces (eHMIs) has recently become a major area of interest in the field of human factors research on automated driving. The broad variety of methodological approaches renders the current state of research inconclusive and comparisons between interface designs impossible. To date, there are no standardized test procedures to evaluate and compare different design variants of eHMIs with each other and with interactions without eHMIs. This article presents a standardized test procedure that enables the effective usability evaluation of eHMI design solutions. First, the test procedure provides a methodological approach to deduce relevant use cases for the evaluation of an eHMI. In addition, we define specific usability requirements that must be fulfilled by an eHMI to be effective, efficient, and satisfying. To prove whether an eHMI meets the defined requirements, we have developed a test protocol for the empirical evaluation of an eHMI with a participant study. The article elucidates underlying considerations and details of the test protocol that serves as framework to measure the behavior and subjective evaluations of non-automated road users when interacting with automated vehicles in an experimental setting. The standardized test procedure provides a useful framework for researchers and practitioners.

Document type: Article

A Novel Traffic Flow Forecasting Method Based on RNN-GCN and BRB

Scipedia content — Fri, 12 Feb 2021 12:49:28 +0100

As an important part of a smart city, intelligent transport can effectively reduce energy consumption and environmental pollution. Traffic flow forecasting provides a reliable traffic dispatch basis for intelligent transport, and most of the existing prediction methods only predict a single saturation or speed and do not use the saturation and speed in a unified way. This paper proposes a new traffic flow prediction method based on RNN-GCN and BRB. First, the belief rule base (BRB) is used for data fusion to obtain new traffic flow data, then the recurrent neural network (RNN) and graph convolution neural network (GCN) model is used to obtain the time correlation of the traffic data, and finally, the traffic flow is predicted by the topology graph. The experimental results show that the method has a better performance than ARIMA, LSTM, and GCN.

Document type: Article

The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review

Scipedia content — Fri, 12 Feb 2021 12:52:09 +0100

Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.

Document type: Article

Mobile Application to Provide Traffic Congestion Estimates and Tourism Spots to Promote Additional Stopovers

Scipedia content — Fri, 12 Feb 2021 12:55:28 +0100

In Japan, traffic congestions often occur on the expressways connecting tourism areas with the Tokyo metropolitan area. This congestion can be mitigated if tourists delayed their departure of homeward trips to avoid peak traffic hours. A potential method to promote staggered departure times is providing the estimates of near-future traffic congestion. This study hypothesized and experimentally confirmed that some tourists would delay their departure to avoid traffic based on near-future traffic estimates. The experiment was conducted in the Yatsugatake area using a mobile application that provided this information to tourists. The results suggest that approximately 40% of self-driving tourists will perform an additional stopover if the returning route is congested and near-future traffic congestion estimate is provided.

Document type: Article

Analysing airport efficiency in East China using a three-stage data envelopment analysis

Scipedia content — Fri, 12 Feb 2021 12:57:05 +0100

This paper evaluates the Technical Efficiencies (TEs) of a group of airports in East China by applying a three-stage Data Envelopment Analysis (DEA) method. The merit of this method allows us to consider the impact of the environmental factors on measuring airport efficiencies. Three variables, i.e. per capita Gross Domestic Product (GDP), the proportion of the tertiary industry, and the number of tourists, are used to represent the environmental factors. The results show that the environmental factors have airport-specific impacts on the value of the efficiencies. Additionally, airport TE are dominated by both Pure Technical Efficiency (PTE) and Scale Efficiency (SE). Based on empirical results, airport specific strategies can be provided to enhance airport efficiency, such as taking the effects of environmental variables and the statistical noise into consideration when analysing the airport efficiency, improving airport efficiencies according to their own conditions and improving the PTE or SE according to their categorizations.

Document type: Article

The effect of emission inventory on modelling of seasonal exposure metrics of particulate matter and ozone with the WRF-Chem model for Poland

Scipedia content — Fri, 12 Feb 2021 12:58:02 +0100

In Poland, high concentrations of particulate matter (with a diameter smaller than 2.5 or 10 μm) exceeding the WHO threshold values are often measured in winter, while ozone (O"sub"3"/sub") concentrations are high in spring. In winter high PM2.5 and PM10 concentrations are linked to high residential combustion and road transport. The main objective of this study was to assess performance of the Weather Research and Forecasting model with Chemistry (WRF-Chem) model in reproducing observations for a period of 2017–2018 covering various meteorological conditions. We compare modelled and observed exposure metrics for PM2.5, PM10 and O"sub"3"/sub" for two sets of the WRF-Chem model runs: with coarse and fine resolution emission inventory (European Monitoring and Evaluation Programme (EMEP) and Chief Inspectorate of Environmental Protection (CIEP), respectively). CIEP run reduces the negative bias of PM2.5 and PM10 and improves the model performance for number of days with exceedance of WHO (World Health Organization) threshold for PM2.5 and PM10 24-h mean concentration. High resolution emission inventory for primary aerosols helps to better distinguish polluted urban areas from non-urban ones. There are no large differences for the model performance for O"sub"3"/sub" and secondary inorganic aerosols, and high-resolution emission inventory does not improve the results in terms of 8-h rolling mean concentrations of ozone.

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Sustainable European Transport System in a 100% Renewable Economy

Scipedia content — Fri, 12 Feb 2021 12:58:22 +0100

Europe must move towards a 100% renewable transportation system for climate, energy and sustainability reasons. We estimate the capital and energy required for building and operating a renewable transportation system providing similar services as the EU-28 transport system of 2016. It could be based on: biogas or fuel cell vessels; liquid biogas powered aircrafts; electric railways and fuel cell or electric vehicles between major cities; and car sharing, electric buses and electric two- and three-wheelers, for short journeys. A system of charging posts on the streets and roads for passenger and commercial e-vehicles is studied. Alternatively, a Tracked Electric Vehicle system of continuous power on European roads would improve energy efficiency and the saving of scarce metals (Ni, Li), at a lower cost, if only national roads were electrified. The investment for the construction of the whole system would be 2.3–2.7% of the EU’s GDP per year for 30 years. The new system operation would require 16% less energy than that of 2016, with reduction of 70% in road transport. However, shipping and aviation would demand 162% and 149% more energy, respectively, if liquefied biogas were used as fuel. A type of land transport fully based on trains would provide a similar service to that of an electric vehicle fleet, with a 29% lower energy consumption.

This study was founded by the European Union, MEDEAS project (“Modeling the Renewable Energy Transition in Europe”, European Union’s Horizon 2020 research and innovation program, grant agreement No 691287 of the Framework Program for Research and Innovation actions, H2020 LCE-21-2015).

Peer reviewed

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Real-Time Abnormal Event Detection for Enhanced Security in Autonomous Shuttles Mobility Infrastructures

Scipedia content — Fri, 12 Feb 2021 13:00:22 +0100

Autonomous vehicles (AVs) are already operating on the streets of many countries around the globe. Contemporary concerns about AVs do not relate to the implementation of fundamental technologies, as they are already in use, but are rather increasingly centered on the way that such technologies will affect emerging transportation systems, our social environment, and the people living inside it. Many concerns also focus on whether such systems should be fully automated or still be partially controlled by humans. This work aims to address the new reality that is formed in autonomous shuttles mobility infrastructures as a result of the absence of the bus driver and the increased threat from terrorism in European cities. Typically, drivers are trained to handle incidents of passengers’ abnormal behavior, incidents of petty crimes, and other abnormal events, according to standard procedures adopted by the transport operator. Surveillance using camera sensors as well as smart software in the bus will maximize the feeling and the actual level of security. In this paper, an online, end-to-end solution is introduced based on deep learning techniques for the timely, accurate, robust, and automatic detection of various petty crime types. The proposed system can identify abnormal passenger behavior such as vandalism and accidents but can also enhance passenger security via petty crimes detection such as aggression, bag-snatching, and vandalism. The solution achieves excellent results across different use cases and environmental conditions.

Document type: Article

Development and Validation of Improved Impedance Functions for Roads with Mixed Traffic Using Taxi GPS Trajectory Data and Simulation

Scipedia content — Fri, 12 Feb 2021 13:02:56 +0100

This paper proposes an improved impedance function for roads with mixed traffic. It is known that only limited studies consider the impact of nonmotorized traffic on travel impedance of a road segment, and a comparison of the impedance considering nonmotorized traffic with the classic BPR function, which does not consider the former, is scarce. Most of the previous studies targeted road conditions in developed countries, where the presence of nonmotorized traffic is negligible, and therefore limited efforts have been invested to develop improved impedance function considering mixed traffic. To overcome this limitation, this paper develops an improved impedance function and carries out a case study for a road in the city of Wuhan, China. The improved impedance function explicitly considers the interaction between motorized and nonmotorized traffic. Taxi GPS data from the case study road is used to extract and analyze the travel time of the “probe vehicles” running through the sampled segment at any time during a sampling day. The capacity of the road segment is measured, and the traffic flow of motorized vehicles and nonmotorized vehicles on the segment is counted. Based on the above data, the classic BPR function and the improved one proposed in this paper are calibrated. After comparing and analyzing the observed road impedance based on both analytical and simulation results, the classic BPR function and the proposed impedance function, the proposed impedance function is found to be more accurate to simulate the observed road impedance, with the error reducing from 14.83 s with the classic BPR impedance function to 6.50 s with the improved function. The proposed impedance function possesses a simple structure and high flexibility, and the parameters calibrated in this paper can be applied to similar roads to provide more realistic impedance than the previous ones based on the classic BPR function. The calibrated improved impedance function’s transferability to other similar roads is validated by applying it to another road and the results show that the percentage error between the predicted travel times and the observed ones is only 3.8%.

Document type: Article

Study and Analysis of a Multi-Mode Power Split Hybrid Transmission

Scipedia content — Fri, 12 Feb 2021 13:05:01 +0100

A two-motor power-split dedicated hybrid transmission (DHT) with two planetary gears is proposed for the applications of a hybrid electric vehicle (HEV) and plug-in HEV (PHEV). The proposed DHT can provide electronically controlled continuous variable transmission (eCVT) with two different gear ratios. One of two electric motors is employed to act as a speeder for splitting the input power of internal combustion engine (ICE) and the other acts as a torquer to assist ICE for boosting. Assisted by an electric motor, ICE can always be enhanced to operate at its efficient area for the benefits of fuel economy improvement. The maximum ICE torque is viable to be mechanically transmitted to vehicle wheels from standstill with two different gear ratios. This feature can help reduce the traction motor torque and power sizing significantly. The paper presents detailed theoretical analyses of the proposed eCVT. Comprehensive simulation demonstrations for a pickup truck HEV application are given to address that the vehicle fuel consumption can be considerably reduced without compromising acceleration performance.

Document type: Article

Analytical and computational indoor shelter models for infiltration of carbon dioxide into buildings : comparison with experimental data

Scipedia content — Fri, 12 Feb 2021 13:06:00 +0100

This paper describes two indoor shelter models – an analytical model and a Computational Fluid Dynamics (CFD) model - that can be used to predict the level of infiltration of carbon dioxide (CO2) into a building following a release from an onshore CO2 pipeline. The motivation behind the development of these models was to demonstrate that the effects of shelter should be considered as part of a Quantitative Risk Assessment (QRA) for CO2 pipeline infrastructure and to provide a methodology for considering the impact of a CO2 release on building occupants.A key component in the consequence modelling of a release from a CO2 pipeline is an infiltration model for CO2 into buildings which can describe the impact on people inside buildings during a release event. This paper describes the development of an analytical shelter model and a CFD model which are capable of predicting the change in internal concentration, temperature and toxic load within a single roomed building that is totally engulfed by a transient cloud of gaseous CO2. Application of the models is demonstrated by comparison with experimental measurements of CO2 accumulation in a building placed in the path of a drifting cloud of CO2. The analytical and CFD models are shown to make good predictions of the average change in internal concentration. Furthermore, it is demonstrated that the effects of shelter should be taken into account when conducting QRA assessments on CO2 pipelines.

Document type: Article

LIMIT STATES OF STEEL SUPPORTING STRUCTURE FOR BRIDGE CRANES

Scipedia content — Fri, 12 Feb 2021 13:06:21 +0100

This paper describes a question of evaluation necessity of bridge cranes using the method of limit deformation state and oscillation damping. The solution was performed by means of theoretical analysis and an experimental verification at the selected bridge crane. The final result sounds that in the case of a correct strength computing of given bridge crane, it is not necessary to also check deformation and damping of oscillation as well. Web of Science 108 158 141

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On-Demand Flexible Transit in Fast-Growing Cities: The Case of Dubai

Scipedia content — Fri, 12 Feb 2021 13:10:52 +0100

Increase in city population and size leads to growing transport demand and heterogeneous mobility habits. In turn, this may result in economic and social inequalities within the context of rapid economic growth. Provision of flexible transit in fast-growing cities is a promising strategy to overcome the limits of conventional public transport and avoid the use of private cars, towards better accessibility and social inclusion. This paper presents the case of Dubai (UAE), where a demand responsive transit service called MVMANT (a company based in Italy) has been tested in some low demand districts. The contribution of this work relies on the use of an agent-based model calibrated with Geographic Information System (GIS) real data to reproduce the service and find optimal configurations from both the perspective of the transport operator and the community. Different scenarios were simulated, by changing the vehicle assignment strategy and capacity, and comparing MVMANT with a ride-sharing service with smaller vehicles. Results suggest that route choice strategy is important to find a balance between operator and user costs, and that these types of flexible transit can satisfy transport demand with limited total costs compared to other shared mobility services. They can also be effective in satisfying fluctuating demand by adopting heterogeneous fleets of vehicles. Finally, appropriate planning and evaluation of these services are needed to fully explore their potential in covering the gap between low-quality fixed public transport and unsustainable private transport.

Document type: Article

Correction: Formation Mechanism of Trailing Oil in Product Oil Pipeline. "i"Processes"/i" 2019, "i"7"/i", 7

Scipedia content — Fri, 12 Feb 2021 13:12:41 +0100

We were not aware of some errors made in the proofreading phase; therefore, we wish to make the following corrections to the mathematical equations in the text in [...]

Document type: Article

Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality

Scipedia content — Fri, 12 Feb 2021 13:13:52 +0100

The prevention and control of COVID-19 in megacities is under large pressure because of tens of millions and high-density populations. The majority of epidemic prevention and control policies implemented focused on travel restrictions, which severely affected urban mobility during the epidemic. Considering the impacts of epidemic and associated control policies, this study analyzes the relationship between COVID-19, travel of residents, Point of Interest (POI), and social activities from the perspective of taxi travel. First, changes in the characteristics of taxi trips at different periods were analyzed. Next, the relationship between POIs and taxi travels was established by the Geographic Information System (GIS) method, and the spatial lag model (SLM) was introduced to explore the changes in taxi travel driving force. Then, a social activities recovery level evaluation model was proposed based on the taxi travel datasets to evaluate the recovery of social activities. The results demonstrated that the number of taxi trips dropped sharply, and the travel speed, travel time, and spatial distribution of taxi trips had been significantly influenced during the epidemic period. The spatial correlation between taxi trips was gradually weakened after the outbreak of the epidemic, and the consumption travel demand of people significantly decreased while the travel demand for community life increased dramatically. The evaluation score of social activity is increased from 8.12 to 74.43 during the post-epidemic period, which may take 3–6 months to be fully recovered as a normal period. Results and models proposed in this study may provide references for the optimization of epidemic control policies and recovery of public transport in megacities during the post-epidemic period.

Document type: Article

Toward Group Applications: A Critical Review of the Classification Strategies of Lithium-Ion Batteries

Scipedia content — Fri, 12 Feb 2021 13:14:15 +0100

To solve the problems of the decreased reliability and safety of battery pack due to the inconsistency between batteries after single batteries are grouped is of great significance to find an appropriate sorting method of single batteries. This study systematically reviews the available literature on battery sorting applications for battery researchers and users. These methods can be roughly divided into three types: direct measurement, sorting based on the model, and sorting based on the material chemistry of batteries. Among them, direct measurement is about the direct measurement of the state parameters of batteries using some professional instruments or testing tools to sort and group batteries with similar or close parameters. Sorting based on the model classifies batteries into groups by establishing a battery equivalent model and carrying out model identification and parameter estimation with machine learning or artificial intelligence algorithm. Sorting based on the material chemistry of batteries is to explore some characteristics related to the chemical mechanism inside the battery. On the basis of reading extensive literature, the methods for classification of battery are provided with an in-depth explanation, and each corresponding strengths and weaknesses of these methods are analyzed. Finally, the future developments of advanced sorting algorithms and batteries prospect.

Document type: Article

Microscopic Traffic Simulation Calibration Level for Reliable Estimation of Vehicle Emissions

Scipedia content — Fri, 12 Feb 2021 13:17:45 +0100

Vehicle emissions are largely determined by the details of driving behaviours. Accordingly, emissions are often estimated by integrating micro-scale emission models into traffic simulations. Under this approach, it is essential to replicate the actual traffic situation being considered in an emission evaluation using a proper calibration procedure. Most previous research with respect to traffic flow has primarily focused on adjusting the complex combinations of parameters evaluated in these models, but it is not guaranteed that the use of widely used calibration measures can lead more accurate emissions estimates. Accordingly, we propose a systematic guideline for calibration to ensure reliable micro-scale emissions estimates. A calibration procedure is thus established in this paper based on various measure of effect (MOE) compositions (i.e., calibration levels) consisting of aggregated traffic data to identify the level that most reliably estimates micro-scale emissions. Five calibration levels of progressively more detailed measurements are first defined, valid calibration levels are identified, and the reliable calibration level is finally selected based on the available traffic data. The effect of vehicle type (i.e., light vs. heavy vehicles) composition on the estimated emissions is also evaluated for a well-calibrated simulation. We expect that a highly reliable estimation of emissions is possible using this more detailed traffic simulation calibration measurement.

Document type: Article

Fleet Transition from Combustion to Electric Vehicles: A Case Study in a Portuguese Business Campus

Scipedia content — Fri, 12 Feb 2021 13:18:31 +0100

This paper aims to contribute to the urgent reflection as a society about environmental protection, in the ultimate challenge that is the sustainable use of energy resources. Since Portugal is at an early stage of market development internally, governmental and local stimulation policies play a central role and are a key element in the successful diffusion of Electric Mobility. The study will focus on the transition of a company car fleet, which currently consists of combustion vehicles, to electric vehicles. With this change it becomes necessary to understand how the electrical installation will be affected due to the installation of charging stations, allowing the company to have some autonomy from the public grid. The various changes resulting from the installation consumption profile will be studied and compared. The state of the art, the level of maturity and where the development of electric mobility in Portugal is heading will also be appreciated.

Document type: Article

Modern Hybrid Excited Electric Machines

Scipedia content — Fri, 12 Feb 2021 13:21:49 +0100

The paper deals with the overview of different designs of hybrid excited electrical machines, i.e., those with conventional permanent magnets excitation and additional DC-powered electromagnetic systems in the excitation circuit. The paper presents the most common topologies for this type of machines found in the literature—they were divided according to their electrical, mechanical and thermal properties. Against this background, the designs of hybrid excited machines that were the subject of scientific research of the authors are presented.

Document type: Article

Bearing assessment tool for longitudinal bridge performance

Scipedia content — Fri, 12 Feb 2021 13:25:45 +0100

This work provides an unsupervised learning approach based on a single-valued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection method for longitudinal displacements to assess the behavior of a singular asymmetric prestressed concrete structure with a 120 m high central pier acting as a fixed point. We first show that the available long-term horizontal displacement measurements recorded during the undamaged state exhibit strong correlations at the different locations of the bearings. Thus, we combine measurements from four sensors to design a robust performance indicator that is only weakly affected by temperature variations after the application of principal component analysis. We validate the method and show its efficiency against false positives and negatives using several metrics: accuracy, precision, recall, and F1 score. Due to its unsupervised learning scope, the proposed technique is intended to serve as a real-time supervision tool that complements maintenance inspections. It aims to provide support for the prioritization and postponement of maintenance actions in bridge management. Authors would like to acknowledge the discussions with Marcos Pantaleón from APIA XXI, Ambher Monitoring Systems and Banobras S.N.C. This work has received funding from the European’s Union Horizon 2020 research and innovation program under the grant agreement No 690660 (RAGTIME Project) and No 769373 (FORESEE Project). This paper reflects only the author’s views. The European Commission and INEA are not responsible for any use that may be made of the information contained therein. David Pardo has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 777778 (MATHROCKS), the European POCTEFA 2014-2020 Project PIXIL (EFA362/19) by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-France-Andorra program, the Project of the Spanish Ministry of Science and Innovation with reference PID2019-108111RBI00 (FEDER/AEI), the BCAM “Severo Ochoa” accreditation of excellence (SEV-2017-0718), and the Basque Government through the BERC 2018-2021 program, the two Elkartek projects 3KIA (KK-2020/00049) and MATHEO (KK-2019-00085), the grant "Artificial Intelligence in BCAM number EXP. 2019/00432", and the Consolidated Research Group MATHMODE (IT1294-19) given by the Department of Education.

Document type: Article

Distribution Route Optimization for Electric Vehicles in Urban Cold Chain Logistics for Fresh Products under Time-Varying Traffic Conditions

Scipedia content — Fri, 12 Feb 2021 13:28:58 +0100

Electric vehicles (EVs) have been widely used in urban cold chain logistic distribution and transportation of fresh products. In this paper, an electric vehicle routing problem (EVRP) model under time-varying traffic conditions is designed for planning the itinerary for fresh products in the urban cold chain. The object of the EVRP model is to minimize the total cost of logistic distribution that includes economic cost and fresh value loss cost. To reflect the real situation, the EVRP model considers several influencing factors, including time-varying road network traffic, road type, client’s time-window requirement, freshness of fresh products, and en route queuing for charging. Furthermore, to address the EVRP, an improved adaptive ant colony algorithm is designed. Simulation test results show that the proposed method can allow EVs to effectively avoid traffic congestion during the distribution process, reduce the total distribution cost, and improve the performance of the cold chain logistic distribution process for fresh products.

Document type: Article

Research on Hydraulic Safety Assessment of Water Distribution Systems

Scipedia content — Fri, 12 Feb 2021 13:29:22 +0100

There are two key issues in the safety assessment of the water distribution system (WDS). One is how to evaluate the safety levels of water supply for customers, while the other is how to describe the importance of a pipe for the global or local WDS. The water demand guarantee rate (DGR) and the water demand failure rate (DFR) are proposed. The mathematical expectations of the DGR and DFR describe the average customer’s water safety levels for the first issue. Moreover, the unit influence of pipe failure (UIPF) is put forward for the second issue. It describes the importance of the pipe for the global or local system. Several cases show how to calculate the above values with the pressure-driven model. It is also shown how to find key pipelines in the WDS. The results show that the method can provide an effective reference for real-life WDS management.

Document type: Article

Effects of Link Capacity Reductions on the Reliability of an Urban Rail Transit Network

Scipedia content — Fri, 12 Feb 2021 13:30:03 +0100

Link capacity reductions, which occur often, degrade the service quality and performance of urban rail transit (URT) networks. To measure the reliability of a URT network when link capacity reductions occur in a given time period, the passengers’ generalized travel cost (GTC) is computed and passengers are divided into three categories. The GTC considers here the crowding in trains, seat availability, and perceived travel time. Passengers whose relative increase in GTC on a URT is below or above a preset threshold belong to category I or II, respectively, while passengers who cannot travel on the URT due to insufficient capacities on their paths belong to category III. Passenger trips in categories I are acceptable since their GTC increases only slightly with link capacity reductions. The fraction of acceptable trip (FAT) and total GTC increase ratio (TGCR) in a given time period are defined here as the network’s reliability and unreliability metrics, respectively. The ratio of affected passenger trip (RAPT) is proposed to identify each line’s most critical links. The reliability and unreliability metrics of Wuhan’s URT network during evening peak hours are computed when the capacities of the most critical link or multiple most critical links are reduced. The results show that the proposed RAPT indicator is effective in identifying the most critical links that greatly affect the reliability and performance of a URT network. For capacity reductions on a line’s most critical link, the proposed method can determine the capacity reduction ratio corresponding to network’s high FAT and low TGCR as well as the priorities of lines needing emergency measures to maintain high network reliability and performance. For capacity reductions on critical links of multiple lines, the proposed method can identify the number of reduction links and the capacity reduction ratio that the network can withstand while maintaining its reliability and performance above a specified level.

Document type: Article

Evaluation of the effectiveness of anti-turbulent additives in the oil pipeline transportation

Scipedia content — Fri, 12 Feb 2021 13:30:39 +0100

The authors of the article have developed the computer application allows to determine the value of the friction coefficient λ and anti-turbulent additives efficiency with a high degree of accuracy. The program can be used in the calculations and design of oil pipelines. The paper presents experimental studies of the effect anti-turbulent additives on the magnitude of pressure losses during fluid movement through pipes. The data gained by the developed computer program has been proved by the data of practical application of additives in the real oil pipeline transportation system called Eastern Siberia-Pacific Ocean oil pipeline.

Document type: Article

Safety of Autonomous Vehicles

Scipedia content — Fri, 12 Feb 2021 13:30:57 +0100

Autonomous vehicle (AV) is regarded as the ultimate solution to future automotive engineering; however, safety still remains the key challenge for the development and commercialization of the AVs. Therefore, a comprehensive understanding of the development status of AVs and reported accidents is becoming urgent. In this article, the levels of automation are reviewed according to the role of the automated system in the autonomous driving process, which will affect the frequency of the disengagements and accidents when driving in autonomous modes. Additionally, the public on-road AV accident reports are statistically analyzed. The results show that over 3.7 million miles have been tested for AVs by various manufacturers from 2014 to 2018. The AVs are frequently taken over by drivers if they deem necessary, and the disengagement frequency varies significantly from 2 × 10−4 to 3 disengagements per mile for different manufacturers. In addition, 128 accidents in 2014–2018 are studied, and about 63% of the total accidents are caused in autonomous mode. A small fraction of the total accidents (∼6%) is directly related to the AVs, while 94% of the accidents are passively initiated by the other parties, including pedestrians, cyclists, motorcycles, and conventional vehicles. These safety risks identified during on-road testing, represented by disengagements and actual accidents, indicate that the passive accidents which are caused by other road users are the majority. The capability of AVs to alert and avoid safety risks caused by the other parties and to make safe decisions to prevent possible fatal accidents would significantly improve the safety of AVs. Practical applications. This literature review summarizes the safety-related issues for AVs by theoretical analysis of the AV systems and statistical investigation of the disengagement and accident reports for on-road testing, and the findings will help inform future research efforts for AV developments.

Document type: Article

Electric cars: Are they solution to reduce CO2 emission?

Scipedia content — Fri, 12 Feb 2021 13:31:30 +0100

Reducing CO2 emission is one of the major environmental challenges for transportation. One way to solve this problem is to replace old cars that use fossil fuels (petrol, diesel) with new electric cars. In this paper, the existing model for calculating well-to-wheels CO2 emission during the life cycle of the car (fossil fuel car and electric car) is upgraded. The developed model is used for comparing optimal lifetime and optimal car’s kilometers driven during a lifetime in the replacement process of a fossil fuel car with a new electric car. We find that reducing CO2 emission depends on the type of fossil fuel, and the weight of fossil fuel cars and electric cars. Changing petrol fossil fuel cars with lower weight electric cars have the greatest potential for reducing CO2 emission. However, the introduction of electric cars does not achieve a significant reduction of CO2 emission in countries where electricity is primarily produced in thermal power plants, i. e. in countries with a high emission factor of electricity production. [Projects of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36010, Grant no. TR 36022 and Grant no. TR 36027]

Document type: Article

Scour Protection Effects of a Geotextile Mattress with Floating Plate on a Pipeline

Scipedia content — Fri, 12 Feb 2021 13:34:21 +0100

Underwater pipelines are vital to the oil industry. Extending the service life of these pipelines is a key issue in improving the sustainability of oil transportation. A geotextile mattress with floating plate (GMFP) is a novel and sustainable countermeasure for scour and erosion control and is herein introduced to protect a partially buried pipeline from local scour in steady currents. A series of experiments was designed to verify the protection capabilities of the GMFP and investigate its parametric effects on protection. The average seepage hydraulic gradient under the pipeline was adopted to depict the protection effects of the GMFP, and was calculated with the pore pressure readings under the pipeline. The test results show that the GMFP is capable of protecting a pipeline from the onset of local scour in a unidirectional current. The average seepage hydraulic gradient below the pipeline decreases remarkably after a GMFP is installed. The average hydraulic gradient shows a descending trend with increased sloping angle &alpha

when 0.64 <

sin&alpha

0.77. The hydraulic gradient hits a nadir at sin&alpha

= 0.77 and climbs with the increasing sloping angle when sin&alpha

0.82. The hydraulic gradient ascends when the bottom opening ratio &delta

increases from 0.167 to 0.231, due to the decreased intensity of the bottom vortex. The hydraulic gradient drops with a rising plate height, except for a fluctuation at Hp = 0.12 m. An approximate negative correlation is found between the obstruction height of the floating plate and the average hydraulic gradient under the pipeline. This could be partially attributed to the extension and amplification of the bottom vortex on the leeside of the pipeline due to the increased plate obstruction height.

Document type: Article

Performance Improvement of Concentrated-Flux Type IPM PMSM Motor with Flared-Shape Magnet Arrangement

Scipedia content — Fri, 12 Feb 2021 13:35:28 +0100

This study demonstrates that the use of a flared-shape rotor structure in interior permanent magnet (IPM) permanent magnet synchronous motor (PMSM) yields better performance than the basic IPM PMSM motor, using a spoke structure with ferrite magnets. To concentrate the effective magnetic flux, the proposed rotor structure is composed of a number of ferrite magnets, which are inserted in a flared shape in the rotor core. This paper shows the comparison with the analysis results of 2D finite element method (FEM), and it is shown that the proposed IPM PMSM motor can be an effective substitute for the basic IPM PMSM motor, which requires low torque ripple and high efficiency. In particular, the proposed flared IPM PMSM motor has lower pulsation of torque and superior efficiency, as well as lower acoustic noise and vibration, compared to the basic IPM PMSM motor. To verify the performance improvement of the proposed model, a prototype of the proposed model was manufactured. It was experimentally confirmed that the proposed model has lower torque ripple and higher efficiency than the basic model. Based on this performance improvement, the proposed flared IPM PMSM motor is suitable for electric vehicles and home appliances.

Document type: Article

Phase behavior study on gas hydrates formation in gas dominant multiphase pipelines with crude oil and high CO2 mixed gas

Scipedia content — Fri, 12 Feb 2021 13:41:13 +0100

"jats:p"This research is focused on understanding the phase behavior of gas hydrate formation in the gas dominant multiphase pipelines containing mixed gas with high CO"jats:sub"2"/jats:sub", crude oil, and deionized water. The experimental conditions are in the pressure range of 3–7 MPa with water cut as 20% of the volume. Initially, the effect of high CO"jats:sub"2"/jats:sub" content in natural gas on the phase boundary conditions of hydrates is studied through simulation (CSMGEM software) and experiments. Later, an additional phase of crude oil was introduced, with 15% of the volume to study the multiphase system. From the experimental analysis, thermodynamic equilibrium conditions were found, and the hydrate-liquid–vapor-equilibrium (HLVE) curves were drawn. The phase behavior is comprehended by comparing the HLVE curves of pure and multiphase systems. It is found that the high CO"jats:sub"2"/jats:sub" content tends to promote the gas hydrate formation. Based on the results, temperature variance and enthalpy of formation were calculated for the multiphase system. With a difference of 1.32 average temperature variance, the multiphase system exhibits inhibition. A basic statistical regression model was made to predict the gas hydrate formation in multiphase transmission pipelines. This work helps in understanding the effect of a new phase on gas hydrate formation.

Document type: Article

Safe and Ecological Speed Control for Heavy-Duty Vehicles on Long–Steep Downhill and Sharp-Curved Roads

Scipedia content — Fri, 12 Feb 2021 13:42:49 +0100

To contribute to the development of sustainable transport that is safe, eco-friendly, and efficient, this research proposed a safe and ecological speed control system for heavy-duty vehicles on long–steep downhill and sharp-curved roads under a partially connected vehicles environment consisting of connected heavy-duty vehicles (CHDVs) and conventional human-driven vehicles. This system prioritizes braking and lateral motion safety before improving fuel efficiency and ensuring traffic mobility at optimal status, and optimizes the speed trajectories of CHDVs to control the entire traffic. Speed optimization is modelled as an optimal control problem and solved by the iterative Pontryagin’s maximum principle algorithm. The simulation-based evaluation shows that the proposed system effectively reduces the peak temperature of the brake drums, the lateral slip angle of the vehicle wheels, and the lateral load transfer rate of the vehicle body; all these measurements of effectiveness are limited to safe ranges. A detailed investigation reveals that the proposed system reduces fuel consumption by up to 15.49% and inhibits the adverse effects on throughput. All benefits increase with the market penetration rate (MPR) of CHDVs and the traffic congestion level and reach significant levels under low MPRs of CHDVs. This indicates that the proposed system has good robustness for the impedance from conventional vehicles and could be implemented in the near future.

Document type: Article

An Overview on the Current Status and Future Perspectives of Smart Cars

Scipedia content — Fri, 12 Feb 2021 13:45:07 +0100

In recent years, the smart car sector has been increasing enormously in the Internet of Things (IoT) market. Furthermore, the number of smart cars seems set to increase over the next few years. This goal will be achieved because the application of recent IoT technologies to the automotive sector opens up innovative opportunities for the mobility of the future, in which connected cars will be more and more prominent in smart cities. This paper aims to provide an overview of the current status and future perspectives of smart cars, taking into account technological, transport, and social features. An analysis concerning the approaches to making smart a generic car, the possible evolutions that could occur in the coming decades, the characteristics of 5G, ADAS (advanced driver assistance systems), and the power sources is carried out in this paper.

Document type: Article

Seismic Analysis of Connections of Buried Continuous Pipelines

Scipedia content — Fri, 12 Feb 2021 13:46:02 +0100

Buried pipelines serve as a critical component of lifeline systems, such as water and gas supply. They are interconnected to form a network to transport utilities. The connections change the geometry and stiffness of pipelines and impact the seismic response of the pipelines. This paper investigates the influence of connections on the seismic response of buried continuous steel trunk lines. A finite element model is introduced for analyzing the seismic response of buried pipeline networks. The seismic response of continuous steel pipelines with different connections, including cruciform and T-, K-, L-, and Y-shaped, is analyzed. The impact of site class, pipe diameter, branch angle, and angle of wave incidence on the response of pipe connections is explored. An influence coefficient defined to characterize the strain amplification at the connections is proposed for different forms of connections. Engineering measures to reduce the strain amplification at connections are suggested.

Document type: Article

Natural Gas Transmission Pipelines: Risks and Remedies for Host Communities

Scipedia content — Fri, 12 Feb 2021 13:47:24 +0100

Transmission pipelines deliver natural gas to consumers around the world for the production of heat, electricity, and organic chemicals. In the United States, 2.56 million miles (4.12 million km) of pipelines carry natural gas to more than 75 million customers. With the benefits of pipelines come the risks to health and property posed by leaks and explosions. Proposals for new and recommissioned pipelines challenge host communities with uncertainty and difficult decisions about risk management. The appropriate community response depends on the risk level, the potential cost, and the prospect for compensation in the event of an incident. This article provides information on the risks and expected costs of pipeline leaks and explosions in the United States, including the incident rates, risk factors, and magnitude of harm. Although aggregated data on pipeline incidents are available, broadly inclusive data do not serve the needs of communities that must make critical decisions about hosting a pipeline for natural gas transmission. This article breaks down the data relevant to such communities and omits incidents that occurred offshore or as part of gas gathering or local distribution. The article then explains possible approaches to risk management relevant to communities, pipeline companies, and policymakers.

Document type: Article

Optimization Design and Analysis of Polymer High Efficiency Mixer in Offshore Oil Field

Scipedia content — Fri, 12 Feb 2021 13:48:04 +0100

The degree of polymer-water mixing in high-pressure pipelines on offshore oilfields usually influences the polymer solution&rsquo

s performance. To realize efficient mixing of the polymer mother liquor with dilution water in the high-pressure pipeline, a high-efficiency mixer is designed and optimized. The designed mixer consists of four parts: a T-shaped pipe as the main body, an inlet flow-splitting plate, a stainless-steel flow-guiding tube, and an outlet flow-splitting plate. Mathematical models are built by using computational fluid dynamics (CFD) and the mixing effects are compared by using Fluent. The research results show that compared with conventional T-shaped mixers, the designed high-efficiency mixer has better mixing performance and increases the mixing rate to 80%. To optimize the mixing rate, the length of the stainless-steel tube is increased and the tube is perforated to guide the flow. The result shows that boring holes along straight lines around the tube can achieve good optimization effect and increase the mixing rate to 95%. The designed high-efficiency mixer can effectively improve the dissolving efficiency and solve problems in polymer-water mixing in the high-pressure pipeline.

Document type: Article

Road Markings and Their Impact on Driver Behaviour and Road Safety: A Systematic Review of Current Findings

Scipedia content — Fri, 12 Feb 2021 13:51:36 +0100

As part of the traffic control plan, road markings form the traffic surface and provide visual guidance for road users. Since their first application to the present day, road markings have become a common element of road infrastructure and one of the basic low-cost safety measures. The aim of this paper is to provide a systematic review of the most significant academic activities to date regarding the influence of longitudinal and transverse road markings as well as road markings for hazard locations (curves, intersections, and rural-urban transitions) on driver’s behaviour and overall road safety. The review includes a total of 71 studies from which are 52 peer-reviewed journal studies, 4 conference proceedings, and 15 professional reports. The studies are, based on their aim, divided into two categories: (1) studies on the impact of road markings on driver behaviour (36 studies) and (2) studies on the impact of road markings on road safety (35 studies).

Document type: Article

Potential Dynamics of CO2 Stream Composition and Mass Flow Rates in CCS Clusters

Scipedia content — Fri, 12 Feb 2021 13:53:25 +0100

Temporal variations in CO"sub"2"/sub" stream composition and mass flow rates may occur in a CO"sub"2"/sub" transport network, as well as further downstream when CO"sub"2"/sub" streams of different compositions and temporally variable mass flow rates are fed in. To assess the potential impacts of such variations on CO"sub"2"/sub" transport, injection, and storage, their characteristics must be known. We investigated variation characteristics in a scenario of a regional CO"sub"2"/sub" emitter cluster of seven fossil-fired power plants and four industrial plants that feed captured CO"sub"2"/sub" streams into a pipeline network. Variations of CO"sub"2"/sub" stream composition and mass flow rates in the pipelines were simulated using a network analysis tool. In addition, the potential effects of changes in the energy mix on resulting mass flow rates and CO"sub"2"/sub" stream compositions were investigated for two energy mix scenarios that consider higher shares of renewable energy sources or a replacement of lignite by hard coal and natural gas. While resulting maximum mass flow rates in the trunk line were similar in all considered scenarios, minimum flow rates and pipeline capacity utilisation differed substantially between them. Variations in CO"sub"2"/sub" stream composition followed the power plants’ operational load patterns resulting e.g., in stronger composition variations in case of higher renewable energy production.

Document type: Article

Lewis–Mogridge Points: A Nonarbitrary Method to Include Induced Traffic in Cost-Benefit Analyses

Scipedia content — Fri, 12 Feb 2021 13:53:45 +0100

We propose a new method to estimate benefits of road network improvements, which allows to include the induced demand without arbitrary assumptions. Instead of estimating induced demand (which is nontrivial and hardly possible in practice), we search for demand induction where initial benefits are mitigated to zero. Such approach allows to formulate a dual measure of benefit, covering both the potential benefits and the likelihood of consuming them by the induced traffic. We first estimate benefits of road network improvement assuming that traffic demand is fixed. Consequently, we find demand model configurations at which the benefits of the new investment become null, i.e., all the initial benefits are consumed by the traffic demand growth. We call such states of induced demand the Lewis–Mogridge points of the analysed improvement. We select the most probable of such points and use it to calculate the proposed novel indicator "jats:italic"μ"/jats:italic", for which the initial benefits (obtained under a fixed-demand assumption) are multiplied with a demand increase rate needed to consume them. We believe that such measure allows to include the critical phenomena of induced traffic and, at the same time, to overcome problems associated with reliable estimation of induced demand. As we illustrate with the case of two alternative road improvement schemes in Kraków, Poland, the proposed method allows to estimate maximal threshold of induced traffic and to select scenario more resilient to induced traffic.

Document type: Article

Research on feeder network design: a case study of feeder service for the port of Kotka

Scipedia content — Fri, 12 Feb 2021 13:55:27 +0100

"jats:p"By exemplifying the feeder service for the port of Kotka, this study proposed a multi-objective optimization model for feeder network design. Innovative for difference from the single-objective evaluation system, the objective of feeder network design was proposed to include single allocation cost, intra-Europe cargo revenue, equipment balance, sailing cycle, allocation utilization, service route competitiveness, and stability. A three-stage control system was presented, and numerical experiment based on container liner’s real life data was conducted to verify the mathematical model and the control system. The numerical experiment revealed that the three-stage control system is effective and practical, and the research ideas had been applicable with satisfactory effect.

Document type: Article

Optimal Design of Bus Stop Locations Integrating Continuum Approximation and Discrete Models

Scipedia content — Fri, 12 Feb 2021 13:56:18 +0100

Although transit stop location problem has been extensively studied, the two main categories of modeling methodologies, i.e., discrete models and continuum approximation (CA) ones, seem have little intersection. Both have strengths and weaknesses, respectively. This study intends to integrate them by taking the advantage of CA models’ parsimonious property and discrete models’ fine consideration of practical conditions. In doing so, we first employ the state-of-the-art CA models to yield the optimal design, which serves as the input to the next discrete model. Then, the stop location problem is formulated into a multivariable nonlinear minimization problem with a given number of stop location variables and location constraint. The interior-point algorithm is presented to find the optimal design that is ready for implementation. In numerical studies, the proposed model is applied to a variety of scenarios with respect to demand levels, spatial heterogeneity, and route length. The results demonstrate the consistent advantage of the proposed model in all scenarios as against its counterparts, i.e., two existing recipes that convert CA model-based solution into real design of stop locations. Lastly, a case study is presented using real data and practical constraints for the adjustment of a bus route in Chengdu (China). System cost saving of 15.79% is observed by before-and-after comparison.

Document type: Article

Radar Data Integrity Verification Using 2D QIM-Based Data Hiding

Scipedia content — Fri, 12 Feb 2021 13:57:15 +0100

The modern-day vehicle is evolved in a cyber-physical system with internal networks (controller area network (CAN), Ethernet, etc.) connecting hundreds of micro-controllers. From the traditional core vehicle functions, such as vehicle controls, infotainment, and power-train management, to the latest developments, such as advanced driver assistance systems (ADAS) and automated driving features, each one of them uses CAN as their communication network backbone. Automated driving and ADAS features rely on data transferred over the CAN network from multiple sensors mounted on the vehicle. Verifying the integrity of the sensor data is essential for the safety and security of occupants and the proper functionality of these applications. Though the CAN interface ensures reliable data transfer, it lacks basic security features, including message authentication, which makes it vulnerable to a wide array of attacks, including spoofing, replay, DoS, etc. Using traditional cryptography-based methods to verify the integrity of data transmitted over CAN interfaces is expected to increase the computational complexity, latency, and overall cost of the system. In this paper, we propose a light-weight alternative to verify the sensor data’s integrity for vehicle applications that use CAN networks for data transfers. To this end, a framework for 2-dimensional quantization index modulation (2D QIM)-based data hiding is proposed to achieve this goal. Using a typical radar sensor data transmission scenario in an autonomous vehicle application, we analyzed the performance of the proposed framework regarding detecting and localizing the sensor data tampering. The effects of embedding-induced distortion on the applications using the radar data were studied through a sensor fusion algorithm. It was observed that the proposed framework offers the much-needed data integrity verification without compromising on the quality of sensor fusion data and is implemented with low overall design complexity. This proposed framework can also be used on any physical network interface other than CAN, and it offers traceability to in-vehicle data beyond the scope of the in-vehicle applications.

Document type: Article

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

Scipedia content — Fri, 12 Feb 2021 13:59:51 +0100

As the demand for transport is growing, more and more attention is being paid to its quality aspects. These include, among other things, efficiency, safety, and a continuous effort to reduce external costs. That is why the transport policies of the EU countries and individual regions are increasingly addressing the issue of sustainable transport development. Multimodal transport, which is seen as a key element to effectively counterbalance the dominant role of vehicle transport in the economic progress of the European Community, plays an important role in these programmes. For consistency and continuity of freight flows, cooperation between neighbouring countries and regions is essential. The future of multimodal freight transport within the cross-border area of Poland, Czech Republic and Slovakia is not as evident as the transport policies imply. Therefore, the purpose of the paper is to identify a set of factors determining the development of multimodal transport within the cross-border area of TRITIA (The European Grouping of Territorial Cooperation of the four regional governments of Moravian-Silesian Region (CZ), Opole Voivodeship (PL), Silesian Voivodeship (PL) and Žilina Self-governing Region (SK)) and to develop four scenarios, the execution of which in the 2030 perspective depends on the implementation of cross-border infrastructure and organisational projects and the increasing level of cooperation in the field of multimodal transport. The article contains the methodology for developing scenarios of multimodal freight transport development. The research showed that initiating activities targeted at the development of multimodal transport within the cross-border area requires the involvement of all participants in the process, i.e., all countries (Poland, Czech Republic and Slovakia), along with many different stakeholders. The future development of multimodal transport as provided for in the scenarios is not linearly correlated with the increase in cooperation and the number of implemented infrastructure and organisational projects. It is vital for future research to define the role of stakeholders both in terms of cooperation and collaboration development.

Document type: Article

Does High-Speed Rail Influence Urban Dynamics and Land Pricing?

Scipedia content — Fri, 12 Feb 2021 14:00:10 +0100

present, many countries around the world have significantly invested in sustainable transportation systems, especially for high-speed rail (HSR) infrastructures, since they are believed to improve economies, and regenerate regional and business growth. In this study, we focus on economic growth, dynamic land use, and urban mobility. The emphasis is placed on testing a hypothesis about whether HSRs can enable socio-economic development. Real case studies using big data from large cities in China, namely Shanghai province and Minhang districts, are taken into account. Socio-technical information such as employment rate, property pricing, and agglomeration in the country&rsquo

s economy is collected from the China Statistics Bureau and the China Academy of Railway Sciences for analyses. This research aims to re-examine practical factors resulting from HSR&rsquo

s impact on urban areas by using ANOVA analysis and dummy variable regression to analyse urban dynamics and property pricing. In addition, this study enhances the prediction outcomes that lead to urban planning strategies for the business area. The results reveal that there are various effects (i.e., regional accessibility, city development plans, and so on) required to enable the success of HSR infrastructure in order to enrich urban dynamics and land pricing. This paper also highlights critical perspectives towards sustainability, which are vital to social and economic impacts. In addition, this study provides crucial perspectives on sustainable developments for future HSR projects.

Document type: Article

Improving Aviation Safety through Modeling Accident Risk Assessment of Runway

Scipedia content — Fri, 12 Feb 2021 14:01:06 +0100

The exponential increase in aviation activity and air traffic in recent decades has raised several public health issues. One of the critical public health concerns is runway safety and the increasing demand for airports without accidents. In addition to threatening human lives, runway accidents are often associated with severe environmental and pollution consequences. In this study, a three-step approach is used for runway risk assessment considering probability, location, and consequences of accidents through advanced statistical methods. This study proposes novel models for the implementation of these three steps in Iran. Data on runway excursion accidents were collected from several countries with similar air accident rates. The proposed models empower engineers to advance an accurate assessment of the accident probability and safety assessment of airports. For in-service airports, it is possible to assess existing runways to remove obstacles close to runways if necessary. Also, the proposed models can be used for preliminary evaluations of developing existing airports and the construction of new runways.

Document type: Article

Modelling rainfall with a Bartlett–Lewis process: New developments

Scipedia content — Fri, 12 Feb 2021 14:04:54 +0100

The use of Poisson cluster processes to model rainfall time series at a range of scales now has a history of more than 30 years. Among them, the randomised (also called modified) Bartlett–Lewis model (RBL1) is particularly popular, while a refinement of this model was proposed recently "span class="cit" id="xref_paren.1""(RBL2; "a href="#bib1.bibx10""Kaczmarska et al."/a", "a href="#bib1.bibx10""2014"/a")"/span". Fitting such models essentially relies upon minimising the difference between theoretical statistics of the rainfall signal and their observed estimates. The first statistics are obtained using closed form analytical expressions for statistics of the orders 1 to 3 of the rainfall depths, as well as useful approximations of the wet–dry structure properties. The second are standard estimates of these statistics for each month of the data. This paper discusses two issues that are important for the optimal model fitting of RBL1 and RBL2. The first issue is that, when revisiting the derivation of the analytical expressions for the rainfall depth moments, it appears that the space of possible parameters is wider than has been assumed in past papers. The second issue is that care must be exerted in the way monthly statistics are estimated from the data. The impact of these two issues upon both models, in particular upon the estimation of extreme rainfall depths at hourly and sub-hourly timescales, is examined using 69 years of 5 min and 105 years of 10 min rainfall data from Bochum (Germany) and Uccle (Belgium), respectively.

Document type: Article

Combining Machine Learning Analysis and Incentive-Based Genetic Algorithms to Optimise Energy District Renewable Self-Consumption in Demand-Response Programs

Scipedia content — Fri, 12 Feb 2021 14:07:41 +0100

The recent rise of renewable energy sources connected to the distribution networks and the high peak consumptions requested by electric vehicle-charging bring new challenges for network operators. To operate smart electricity grids, cooperation between grid-owned and third-party assets becomes crucial. In this paper, we propose a methodology that combines machine learning with multi-objective optimization to accurately plan the exploitation of the energy district&rsquo

s flexibility with the objective of reducing peak consumption and avoiding reverse power flow. Using historical data, acquired by the smart meters deployed on the pilot district, the district&rsquo

s power profile can be predicted daily and analyzed to identify potentially critical issues on the network. District&rsquo

s resources, such as electric vehicles, charging stations, photovoltaic panels, buildings energy management systems, and energy storage systems, have been modeled by taking into account their operational constraints and the multi-objective optimization has been adopted to identify the usage pattern that better suits the distribution operator&rsquo

s (DSO) needs. The district is subject to incentives and penalties based on its ability to respond to the DSO request. Analysis of the results shows that this methodology can lead to a substantial reduction of both the reverse power flow and peak consumption.

Document type: Article

Power Density Maximization in Medium Frequency Transformers by Using Their Maximum Flux Density for DC–DC Converters

Scipedia content — Fri, 12 Feb 2021 14:08:03 +0100

The medium frequency transformer (MTF) is a key component of various new DC&ndash

DC converters that are designed for applications in modern electrical power grids at medium and high voltage. To attain the high performance that are necessary for targeting these applications, MFTs should have high power density and high efficiency as characteristics. For this endeavor, newly designed MFT procedures, which also take advantages of new core materials, are under investigation. Differently to other design proposals, most of which use conventional transformer design procedures based on equating core losses to copper conduction losses, in this paper, an MTF with a nanocrystalline (VITROPERM 500F) core is designed with a new procedure that is oriented in aiming the maximum flux density (Bmax). The characteristics of the MFTs that are obtained by using this procedure are compared with those of the MFTFs that are designed with a conventional procedure. The results show that by using the proposed technique, we get a 25% reduction in the winding size, a higher power density, and a lower MTF building cost while maintaining a high efficiency (>

98%). The design methodology is developed through a rigorous mathematical analysis that is verified with computer simulations in Matlab-Simulink and validated with experimental results from two MTF laboratory prototypes designed at a flux density of 0.9 T (75% Bmax) and 1.2 T (Bmax).

Document type: Article

Decarbonizing Maritime Transport: The Importance of Engine Technology and Regulations for LNG to serve as a Transition Fuel

Scipedia content — Fri, 12 Feb 2021 14:10:15 +0100

Current Greenhous gas emissions (GHG) from maritime transport represent around 3% of global anthropogenic GHG emissions and will have to be cut in half by 2050 to meet Paris agreement goals. Liquefied natural gas (LNG) is by many seen as a potential transition fuel for decarbonizing shipping. Its favorable hydrogen to carbon ratio compared to diesel (marine gas oil, MGO) or bunker fuel (heavy fuel oil, HFO) translates directly into lower carbon emissions per kilowatt produced. However, these gains may be nullified once one includes the higher Well-to-tank emissions (WTT) of the LNG supply chain and the vessel’s un-combusted methane slip (CH4) from its combustion engine. Previous studies have tended to focus either on greenhouse gas emissions from LNG in a Well-to-wake (WTW) perspective, or on alternative engine technologies and their impact on the vessel’s Tank-to-wake emissions (TTW). This study investigates under what conditions LNG can serve as a transition fuel in the decarbonization of maritime transport, while ensuring the lowest possible additional global warming impact. Transition refers to the process of moving away from fossil fuels towards new and low carbon fuels and engine technologies. Our results show: First, the importance of applying appropriate engine technologies to maximize GHG reductions; Second, that applying best engine technologies is not economically profitable; Third, how regulations could be amended to reward best engine technologies. Importantly, while the GHG reduction of LNG even with best engine technology (dual fuel diesel engine) are limited, ships with these engines can with economically modest modification switch to ammonia produced with renewable energy when it becomes available in sufficient amounts. This study has been financially supported by the Norwegian Research Council project (Norges Forskningsråd) SFI Smart Maritime project number 237917.

Document type: Article

Influence of the length parameter of an underground oil pipeline on the frequency of free oscillation

Scipedia content — Fri, 12 Feb 2021 14:12:12 +0100

The problem of finding the natural frequencies of thin-walled underground oil pipelines is solved, based on the application of a semi-momentless theory of cylindrical shells of medium bending, in which bending moments in the longitudinal direction are not taken into account in view of their smallness compared with moments acting in the transverse direction. The solution to this approach is a fourth-order homogeneous differential equation satisfying the boundary conditions of articulation at each end. This equation includes the parameters of the length, internal pressure, thinness of the pipeline, as well as the values of the coefficient of elastic resistance of the soil, the attached mass of the soil and the attached mass of the flowing oil. Based on the data obtained by the derived formulas, the frequency characteristics of large-diameter thin-walled underground oil pipelines are determined depending on the length of the element, as well as on the soil conditions. It has been established that the minimum frequencies are realized for shell modes of vibration with a length parameter of the pipeline section (the ratio of the length of the section to the radius) not exceeding 13. A formula is derived that allows one to determine the boundary between the use of the rod and shell theory for calculating pipelines for dynamic effects. Using the dynamic stability criterion, in which the frequency of natural oscillations vanishes, expressions are derived that allow one to determine the external critical pressure on the wall of the pipeline, which takes into account the length of the pipeline, as well as the number of half waves in the transverse and longitudinal directions, in which the pipeline goes into emergency condition.

Document type: Article

Model for Collaboration among Carriers to Reduce Empty Container Truck Trips

Scipedia content — Fri, 12 Feb 2021 14:14:14 +0100

In recent years, intermodal transport has become an increasingly attractive alternative to freight shippers. However, the current intermodal freight transport is not as efficient as it could be. Oftentimes an empty container needs to be transported from the empty container depot to the shipper, and conversely, an empty container needs to be transported from the receiver to the empty container depot. These empty container movements decrease the freight carrier’s profit, as well as increase traffic congestion, decrease roadway safety, and add unnecessary emissions to the environment. To this end, our study evaluates a potential collaboration strategy to be used by carriers for domestic intermodal freight transport based on an optimization approach to reduce the number of empty container trips. A binary integer-linear programming model is developed to determine each freight carrier’s optimal schedule while minimizing its operating cost. The model ensures that the cost for each carrier with collaboration is less than or equal to its cost without collaboration. It also ensures that average savings from the collaboration are shared equally among all participating carriers. Additionally, two stochastic models are provided to account for uncertainty in truck travel times. The proposed collaboration strategy is tested using empirical data and is demonstrated to be effective in meeting all of the shipment constraints.

Document type: Article

Discovering the Graph-Based Flow Patterns of Car Tourists Using License Plate Data: A Case Study in Shenzhen, China

Scipedia content — Fri, 12 Feb 2021 14:18:44 +0100

Identifying flow patterns from massive trajectories of car tourists is considered a promising way to improve the management of tourism traffic. Previous researches have mainly focused on tourist movements at the macro-scale, such as inbound, domestic, and urban tourism using flow maps. Compared with modeling the flow patterns of tourists at the macro-scale, modeling tourist flow at the microscale is more complicated. This paper takes Dapeng Island located in Shenzhen as the study area and uses the car recognition devices to collect traffic flow. Firstly, car tourists are separated from the mixed traffic flow after analyzing the spatial-temporal characteristics of tourists and residents. Next, daily graphs of tourist movements between road segments and tourist attractions are constructed. Finally, a frequent subgraph mining algorithm is used to extract the flow patterns of car tourists. The experimental results show that (1) car tourists have obvious preferences in the selection of trip time and tourist attractions; (2) the intercity tourists tend to take multidestination trips rather than a single destination trip in the same type of attractions; (3) car tourists are inclined to park their cars in an easy-to-access place, even if the attractions visited are changed. The main contribution of this paper is to present a new method for discovering the flow patterns of car tourists hidden in massive amounts of license plate data.

Document type: Article

Metro Scheduling to Minimize Travel Time and Operating Cost Considering Spatial and Temporal Constraints on Passenger Boarding

Scipedia content — Fri, 12 Feb 2021 14:19:21 +0100

Passengers on metro platforms can board a train only when the train has surplus capacity and the dwell time is sufficient, while the latter condition is omitted in previous studies. Taking into account the impacts of train capacity and dwell time on passengers boarding, this study develops a model on optimizing metro timetable to reduce passenger travel time and metro operating cost, through regulating trains’ inter-station run-time, dwell time and headway. The NSGA-II algorithm is employed to obtain the near-optimal Pareto Frontier of the proposed model. To address insufficient dwell time scheduled in the timetable, three operating strategies are proposed and compared: a. sticking to nominal timetable; b. extending dwell time only; c. extending dwell time and recovering delay as soon as possible by compressing train inter-station run-time. Case studies on real-life metro line prove that some passengers cannot board the train during peak hours due to insufficient dwell time. In this context, strategy a brings low-quality service because passengers are stranded at platform even though the train has surplus capacity. In contrast, more passengers can board the train with strategies b and c because dwell time is extended for passengers’ boarding when train has surplus capacity. Compared to strategy b, strategy c reduces the average in-vehicle time of passengers by 2.5% through compressing inter-station run-time to recover the delay. The timetable optimized based on strategy c saves total travel time of passengers by 3.1% without increasing operating cost when compared to the practical timetable.

Document type: Article

Evolution Regularity Mining and Gating Control Method of Urban Recurrent Traffic Congestion: A Literature Review

Scipedia content — Fri, 12 Feb 2021 14:21:16 +0100

To understand the status quo of urban recurrent traffic congestion, the current results of recurrent traffic congestion, and gating control are reviewed from three aspects: traffic congestion identification, evolution trend prediction, and urban road network gating control. Three aspects of current research are highlighted: (a) The majority of current studies are based on statistical analyses of historical data, while congestion identification is performed by acquiring small-scale traffic parameters. Thus, congestion studies on the urban global roadway network are lacking. Situation identification and the failure to effectively warn or even avoid traffic congestion before congestion forms are not addressed; (b) correlation studies on urban roadway network congestion are inadequate, especially regarding deep learning, and considering the space-time correlation for congestion evolution trend prediction; and (c) quantitative research methods, dynamic determination of gating control areas, and effective countermeasures to eliminate traffic congestion are lacking. Regarding the shortcomings of current studies, six research directions that can be further explored in the future are presented.

Document type: Article

Placement of Infrastructure for Urban Electromobility: A Sustainable Approach

Scipedia content — Fri, 12 Feb 2021 14:22:16 +0100

Over the last few years, electric vehicles (EVs) have turned into viable urban transportation alternatives. Charging infrastructure is an issue, since high investment is needed and there is a lot of demand uncertainty. Seeking to fill gaps in past studies, this investigation proposes a set of procedures to identify the most adequate places for implementing the EV charging infrastructure. In order to identify the most favorable districts for the installation and operation of electric charging infrastructure in São Paulo city, the following public available information was considered: the density of points of interest (POIs), distribution of the average monthly per capita income, and number of daily trips made by transportation mode. The current electric vehicle charging network and most important business corridors were additionally taken into account. The investigation shows that districts with the largest demand for charging stations are located in the central area, where the population also exhibits the highest purchasing power. The charging station location process can be applied to other cities, and it is possible to use additional variables to measure social inequality.

Document type: Article

Fundamental Elements of an Urban UTM

Scipedia content — Fri, 12 Feb 2021 14:25:51 +0100

Urban airspace environments present exciting new opportunities for delivering drone services to an increasingly large global market, including: information gathering; package delivery; air-taxi services. A key challenge is how to model airspace environments over densely populated urban spaces, coupled with the design and development of scalable traffic management systems that may need to handle potentially hundreds to thousands of drone movements per hour. This paper explores the background to Urban unmanned traffic management (UTM), examining high-level initiatives, such as the USA’s Unmanned Air Traffic (UTM) systems and Europe’s U-Space services, as well as a number of contemporary research activities in this area. The main body of the paper describes the initial research outputs of the U-Flyte R&D group, based at Maynooth University in Ireland, who have focused on developing an integrated approach to airspace modelling and traffic management platforms for operating large drone fleets over urban environments. This work proposes pragmatic and innovative approaches to expedite the roll-out of these much-needed urban UTM solutions. These approaches include the certification of drones for urban operation, the adoption of a collaborative and democratic approach to designing urban airspace, the development of a scalable traffic management and the replacement of direct human involvement in operating drones and coordinating drone traffic with machines. The key fundamental elements of airspace architecture and traffic management for busy drone operations in urban environments are described together with initial UTM performance results from simulation studies.

Document type: Article

Perspective Review on Subsea Jet Trenching Technology and Modeling

Scipedia content — Fri, 12 Feb 2021 14:26:08 +0100

This paper presents a comprehensive review on subsea jet trenching technology via a critical analysis of its principle, mechanism, devices, modeling approaches, as well as properties of subsea sediments. This review shows that the success of jet trenching operations is closely related to some key factors including the soil conditions, trencher specifications, and characteristics of pipelines or cables. Three case histories are presented to demonstrate the importance of these key factors and their interrelationships. This paper also points out a number of challenges pertaining to the implementation of the jet trenching method in carbonate sediments, as well as some limitations and gaps in the existing modeling approaches. Future perspective researches that are recommended to develop: (1) promising theories, like turbulent submerged flow, and (2) robust numerical approaches, such as the smoothed particle hydrodynamics (SPH) and material point method (MPM) to substantiate the experimental experience and reveal possible hidden mechanisms.

Document type: Article

Innovative health care mobility services in the US

Scipedia content — Fri, 12 Feb 2021 14:26:37 +0100

Background Transportation barriers prevent millions of people from accessing health care each year. Health policy innovations such as shared savings payment models (commonly used in accountable care organizations) present financial incentives for providers to offer patient transportation to medical care. Meanwhile, ridesourcing companies like Uber and Lyft have entered the market to capture a significant share of spending on non-emergency health care transportation. Our research examines the current landscape of innovative health care mobility services in the US. Methods We conducted an environmental scan to identify case examples of utilization of ridesourcing technology to facilitate non-emergency health care transportation and developed a typology of innovative health care mobility services. The scan used a keyword-based search of news publications with inductive analysis. For each instance identified, we abstracted key information including: stakeholders, launch date, transportation provider, location/service area, payment/booking method, target population, level of service, and any documented outcomes. Results We discovered 53 cases of innovation and among them we identified three core types of innovation or collaboration. The first and most common type of innovation is when a health care provider leverages ridesourcing technology to book patient trips. This involves both established and nascent transportation companies tailoring the ridesourcing experience to the health care industry by adding HIPAA-compliance to the booking process. The second type of innovation involves an insurer or health plan formally partnering with a ridesourcing company to expand transportation offerings to beneficiaries or offer these services for the first time. The third type of innovation is when a paratransit provider partners with a ridesourcing company; these cases cite increased flexibility and reliability of ridesourcing services compared to traditional paratransit. Conclusions Ridesourcing options are becoming a part of the mode choice set for patients through formal partnerships between ridesourcing companies, health care providers, insurers, and transit agencies. The on-demand nature of rides, booking flexibility, and integration of ride requests and payment options via electronic medical records appear to be the strongest drivers of this innovation.

Document type: Article

Scope of Using Autonomous Trucks and Lorries for Parcel Deliveries in Urban Settings

Scipedia content — Fri, 12 Feb 2021 14:28:59 +0100

Courier, express, and parcel (CEP) services represent one of the most challenging and dynamic sectors of the logistics industry. Companies of this sector must solve several challenges to keep up with the rapid changes in the market. In this context, the introduction of autonomous delivery using self-driving trucks might be an appropriate solution to overcome the problems that the industry is facing today. This paper investigates if the introduction of autonomous trucks would be feasible for deliveries in urban areas from the experts’ point of view. Furthermore, the potential advantages of such autonomous vehicles were highlighted and compared to traditional delivery methods. At the same time, barriers that could slow down or hinder such an implementation were also discovered by conducting semi-structured interviews with experts from the field. The results show that CEP companies are interested in innovative logistics solutions such as autonomous vans, especially when it comes to business-to-consumer (B2C) activities. Most of the experts acknowledge the benefits that self-driving vans could bring once on the market. Despite that, there are still some difficulties that need to be solved before actual implementation. If this type of vehicle will become the sector’s disruptor is yet to be seen.

Document type: Article

Study on Driving Cycle Synthesis Method for City Buses considering Random Passenger Load

Scipedia content — Fri, 12 Feb 2021 14:29:34 +0100

This paper proposes a novel driving cycle construction method in consideration of velocity, road slope, and passenger load, based on a real-world bus route with a plug-in hybrid electric bus (PHEB). The main purpose is to address the disadvantage that an inaccurate reflection of the real-world driving characteristics for city buses will be caused when ignoring the passenger load in the course of a driving cycle synthesis. Two contributions are supplemented to distinguish from the previous research. Firstly, a novel station-based method is proposed aiming at developing a driving cycle with high accuracy. The kinematic segments are partitioned according to the distance of adjacent bus stops, while a two-dimensional Markov chain Monte Carlo method is employed to synthesize driving cycle between each interval of adjacent bus stops. Secondly, the random passenger load for different bus stops is treated as a discrete Markov chain model, according to the correlation analysis of the measured passenger data which are distinguished for off-peak and peak hours. Meanwhile, Monte Carlo simulation and maximum likelihood estimation are utilized to determine the most likely number of passengers for each bus stop. At last, the fuel consumption of the PHEB is simulated with the best-synthesized driving cycle and contrasted to the mean fuel consumption of the later measured data which is composed of the velocity, road slope, and the passenger load. The results demonstrate that the synthesized driving cycle has a higher accuracy on fuel consumption estimation.

Document type: Article

The waterlogged limits of the infrastructural state : the failure of the T’aean Canalization Projects in pre-industrial Korea, 1134-1537.

Scipedia content — Fri, 12 Feb 2021 14:29:56 +0100

One of the chronic problems of pre-industrial Korean history has been the difficulty of material integration between core regions of the Korean peninsula. This article analyzes five major canalization attempts made by Koryŏ and Chosŏn states in the T’aean region to address the problem of infrastructural integration. Located along a critical shipping route between the southern grain basket and the capital region, the T’aean coastline had been infamous for centuries for its treacherous tides and proclivity for hastening shipwrecks. Consequently, from 1134 to 1537, Koryŏ and Chosŏn officials attempted canalization projects that, if successful, would have allowed grain ships to bypass the most troublesome zones. However, the canalization efforts all ended in failure. Utilizing Chosŏn-era institutional records, I argue that the canalization failures: 1) exposed a pre-industrial state’s logistical and technological limits, notably, the difficulty of coastal canalization efforts in areas of high tidal variation and granite bedrock, and 2) prompted shifts in the infrastructural priorities of the Chosŏn state.

Document type: Article

Regenerative Braking Strategy of a Formula SAE Electric Race Car Using Energetic Macroscopic Representation

Scipedia content — Fri, 12 Feb 2021 14:30:20 +0100

This paper presents a braking strategy analysis for a Formula SAE electric race car. The proposed braking strategy aims to increase the recovery energy by a relevant distribution of the braking forces between the rear and front wheels. A mathematical model of the car is presented, and a simulation is performed in Matlab-Simulink. The model is organized using the energetic macroscopic representation graphical formalism. A real racetrack driving cycle is considered. Three braking strategies are compared considering the energy recovery and the vehicle stability. The simulation results show that the proposed strategy enables higher energy recovery while avoiding locking on both rear and front wheels. As in such a race the driving range is fixed, the reduction in energy consumption can be used to reduce the battery size. The battery weight can thus be decreased to improve the vehicle performance during competition.

Document type: Article

Effect of Loudspeakers on the In Situ Electric Field in a Driver Body Model Exposed to an Electric Vehicle Wireless Power Transfer System

Scipedia content — Fri, 12 Feb 2021 14:31:11 +0100

This study computationally evaluates the effect of loudspeakers on the in situ electric field in a driver body model exposed to the magnetic field from a wireless power transfer (WPT) system in an electric vehicle (EV), one with a body made of carbon fiber reinforced plastic (CFRP) and the other made with aluminum. A quasi-static two-step approach was applied to compute the in situ electric field. The computational results showed that the magnetic field distribution generated by the WPT is significantly altered around the loudspeakers, and shows obvious discontinuity and local enhancement. The maximum spatial-average magnetic field strength in the driver’s body was increased by 11% in the CFRP vehicle. It was 2.25 times larger than the reference levels (RL) prescribed in the International Commission of Non-Ionizing Radiation Protection (ICNIRP) guidelines in 2010. In addition, we found that the in situ electric field computed by the line- and volume-averaging methods were stable if the top 0.1% voxels are excluded. The maximum value was well below the basic restriction (BR) of the ICNIRP guidelines. Nevertheless, the presence of the loudspeaker led to increments in the electric field strength in parts of the human body, suggesting the potential influence of permissible transmitting power in the WPT system. The maximum electric field strength in the thigh and buttock with the woofer, increased by 27% in the CFRP vehicle. The arm value was up to 3 times higher than that obtained without the tweeter in the aluminum vehicle. Moreover, this study found that the maximum electric field strength depended on the location of the loudspeaker with respect to the WPT system and the separation from the driver model. Therefore, the loudspeaker should be considered when evaluating the maximum in situ electric field strength in the vehicle body design stage.

Document type: Article

An Active Hybrid Energy Storage System Utilising a Fuzzy Logic Rule-Based Control Strategy

Scipedia content — Fri, 12 Feb 2021 14:31:43 +0100

The research presented in this paper documents the implementation of an active hybrid energy storage system that combined a battery pack and an ultracapacitor bank. The implemented hybrid energy storage system was used to reduce the peak-power that the battery needs to provide to the load. An active topology utilising two direct current/direct current (DC/DC) converters and a switch was used to implement the hybrid energy storage system. Fuzzy logic was used as a close-loop control structure to control the DC/DC converters in the topology, whilst a rule-based control strategy was used to control the operating states of the hybrid energy storage system. Experimental implementation of the system showed that the system was able to actively control the energy flow throughout the hybrid energy storage system in order to limit the power drawn from the battery to a user-defined limit. The performance of the fuzzy logic controllers was also experimentally found to be sufficient when used in conjunction with the rule-based control strategy. The system allows one to utilize batteries that are optimized for energy density seeing that the system was able to actively limit the power drawn from the battery, whilst providing the required power to the load by utilising the ultracapacitor bank.

Document type: Article

Representation of Traffic Congestion Data for Urban Road Traffic Networks Based on Pooling Operations

Scipedia content — Fri, 12 Feb 2021 14:32:47 +0100

In order to improve the efficiency of transportation networks, it is critical to forecast traffic congestion. Large-scale traffic congestion data have become available and accessible, yet they need to be properly represented in order to avoid overfitting, reduce the requirements of computational resources, and be utilized effectively by various methodologies and models. Inspired by pooling operations in deep learning, we propose a representation framework for traffic congestion data in urban road traffic networks. This framework consists of grid-based partition of urban road traffic networks and a pooling operation to reduce multiple values into an aggregated one. We also propose using a pooling operation to calculate the maximum value in each grid (MAV). Raw snapshots of traffic congestion maps are transformed and represented as a series of matrices which are used as inputs to a spatiotemporal congestion prediction network (STCN) to evaluate the effectiveness of representation when predicting traffic congestion. STCN combines convolutional neural networks (CNNs) and long short-term memory neural network (LSTMs) for their spatiotemporal capability. CNNs can extract spatial features and dependencies of traffic congestion between roads, and LSTMs can learn their temporal evolution patterns and correlations. An empirical experiment on an urban road traffic network shows that when incorporated into our proposed representation framework, MAV outperforms other pooling operations in the effectiveness of the representation of traffic congestion data for traffic congestion prediction, and that the framework is cost-efficient in terms of computational resources.

Document type: Article

Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections

Scipedia content — Fri, 12 Feb 2021 14:33:20 +0100

This paper focuses on investigating electric bikers’ (e-bikers) crossing behavior and violations based on survey data of 3,126 e-bikers collected at signalized intersections in Nantong, China. We first explore e-bikers’ characteristics of late crossing, incomplete crossing, and violating crossing behaviors by frequency analysis and duration distribution, and examine a few influential factors for e-bikers’ red-light running (RLR) behavior, including site type, crossing length and traffic signal countdown timers (TSCTs). E-bikers’ RLR behavior is further divided into three categories, namely GR near-violations, RR violations, and RG violations. Second, we use a binary logistic regression model to identify the relationship between e-bikers’ RLR behavior and potential influential factors, including demographic attributes, movement information, and infrastructure conditions. We not only make regression analysis for respective violation type, but also carry out an integrated regression of a census of all three types of violations. Some insightful findings are revealed: (i) the green signal time and site type are the most significant factors to GR near-violations, but with little impact on the other two violation types; (ii) the waiting time, waiting position, passing cars and crossing length exert considerable impact on RR violations; (iii) for RG violations, TSCTs, leading violators and gender are the most significant factors; (iv) it is also unveiled that site type, green signal time and TSCTs have negligible impact on the whole violations regardless of the violation types. Thus, it is more meaningful to investigate the impacts of these variables on e-bikers’ RLR behavior according to different violation types; otherwise, the potential relationship between some crucial factors and e-bikers’ RLR behavior might be ignored. These findings would help to improve intersection crossing safety for traffic management.

Document type: Article

The Electric Riverboat Charging Station Location Problem

Scipedia content — Fri, 12 Feb 2021 14:34:16 +0100

Nowadays, the electric mobility is mainly focused on urban areas. However, the use of Photovoltaic-assisted Charging Stations (PVCSs) can contribute to implement the electric mobility in rural areas disconnected from the national grid. Inspired by the new river operations with an Electric Boat (EB), we introduce a new location problem named the Electric Riverboat Charging Station Location Problem (ERCSLP). This problem estimates the necessary infrastructure for an EB to be able to perform a round trip. In this case, we decide the location of the PVCSs and the size of the EB battery aiming to minimize the sum of the PVCS and the EB battery costs. In this problem, we include the nonlinear behavior of the charging function and the variation of the solar radiation. For solving this problem, we propose a Mixed-Integer Linear Programming (MILP) formulation. For testing this MILP formulation, we build a set of instances based on real river transport operations that have the potential to migrate to the electric mobility. In our computational experiments, we show that our MILP formulation can find the optimal solution of the instances. Finally, we perform a sensitivity analysis and an economic viability analysis of the electric mobility in these operations.

Document type: Article

Supporting Drivers of Partially Automated Cars Through an Adaptive Digital In-Car Tutor

Scipedia content — Fri, 12 Feb 2021 14:35:42 +0100

Drivers struggle to understand how, and when, to safely use their cars&rsquo

complex automated functions. Training is necessary but costly and time consuming. A Digital In-Car Tutor (DIT) is proposed to support drivers in learning about, and trying out, their car automation during regular drives. During this driving simulator study, we investigated the effects of a DIT prototype on appropriate automation use and take-over quality. The study had three sessions, each containing multiple driving scenarios. Participants needed to use the automation when they thought that it was safe, and turn it off if it was not. The control group read an information brochure before driving, while the experiment group received the DIT during the first driving session. DIT users showed more correct automation use and a better take-over quality during the first driving session. The DIT especially reduced inappropriate reliance behaviour throughout all sessions. Users of the DIT did show some under-trust during the last driving session. Overall, the concept of a DIT shows potential as a low-cost and time-saving solution for safe guided learning in partially automated cars.

Document type: Article

Automated Emergency Vehicle Control Strategy Based on Automated Driving Controls

Scipedia content — Fri, 12 Feb 2021 14:36:35 +0100

This study proposes an integrated driving control strategy by taking advantage of the automated driving technology at the individual vehicle level and the traffic signal preemption strategy at the traffic infrastructure level. This aims to facilitate an automated driving-based emergency vehicle control and ultimately to achieve efficient and safe control of emergency vehicles. To this end, this study developed the integrated emergency vehicle control logic, implemented the logic in the microscopic traffic simulation environment using the simulation software’s application programming interface capability, and evaluated the impacts of the proposed emergency vehicle control logic in the aspects of mobility and safety with different driving aggressiveness and preemption initiation settings. The study’s results show that the proposed emergency vehicle control logic achieved benefits on mobility and safety and the benefits of emergency vehicle control strategy can be maximized when the signal preemption and the automated driving control operate in collaboration. Therefore, the proposed integrated approach of automated driving controls and signal preemption will be a great reference for enhancing automated driving technologies supporting a safe and fast mobility solution.

Document type: Article

Model-based assessment of the impact of driver-assist vehicles using kinetic theory

Scipedia content — Fri, 12 Feb 2021 14:39:22 +0100

"jats:p"In this paper, we consider a kinetic description of follow-the-leader traffic models, which we use to study the effect of vehicle-wise driver-assist control strategies at various scales, from that of the local traffic up to that of the macroscopic stream of vehicles. We provide theoretical evidence of the fact that some typical control strategies, such as the alignment of the speeds and the optimisation of the time headways, impact on the local traffic features (for instance, the speed and headway dispersion responsible for local traffic instabilities) but have virtually no effect on the observable macroscopic traffic trends (for instance, the flux/throughput of vehicles). This unobvious conclusion, which is in very nice agreement with recent field studies on autonomous vehicles, suggests that the kinetic approach may be a valid tool for an organic multiscale investigation and possibly the design of driver-assist algorithms.

Document type: Article

Multi-Objective Electric Vehicles Scheduling Using Elitist Nondominated Sorting Genetic Algorithm

Scipedia content — Fri, 12 Feb 2021 14:40:21 +0100

The introduction of electric vehicles (EVs) will have an important impact on global power systems, in particular on distribution networks. Several approaches can be used to schedule the charge and discharge of EVs in coordination with the other distributed energy resources connected on the network operated by the distribution system operator (DSO). The aggregators, as virtual power plants (VPPs), can help the system operator in the management of these distributed resources taking into account the network characteristics. In the present work, an innovative hybrid methodology using deterministic and the elitist nondominated sorting genetic algorithm (NSGA-II) for the EV scheduling problem is proposed. The main goal is to test this method with two conflicting functions (cost and greenhouse gas (GHG) emissions minimization) and performing a comparison with a deterministic approach. The proposed method shows clear advantages in relation to the deterministic method, namely concerning the execution time (takes only 2% of the time) without impacting substantially the obtained results in both objectives (less than 5%).

Document type: Article

Which factors affect willingness-to-pay for automated vehicle services? Evidence from public road deployment in Stockholm, Sweden

Scipedia content — Fri, 12 Feb 2021 14:42:07 +0100

"jats:title"Introduction"/jats:title" "jats:p"Travel demand and travel satisfaction of a transport service are affected by user perceptions of the service quality attributes, and such perceptions should be included in studying user willingness-to-pay (WTP) for automated vehicle (AV) services. This study applied structural equation modelling with service quality attribute perceptions as latent variables affecting WTP."/jats:p" "/jats:sec""jats:sec" "jats:title"Objectives"/jats:title" "jats:p"We investigated how WTP AV services are affected by socio-demographic characteristics, knowledge and experiences with AV, existing travel modes and particularly, perceptions of the associated service quality attributes. The AV services are: 1) "jats:italic"on-demand personalised AV (PAV) service"/jats:italic", 2) "jats:italic"demand responsive shared AV (SAV) service"/jats:italic", and 3) "jats:italic"first−/last-mile automated bus (AB) service"/jats:italic"."/jats:p" "/jats:sec""jats:sec" "jats:title"Methods"/jats:title" "jats:p"The data were collected from 584 potential users of a first−/last-mile AB service trial operated in Kista, Stockholm."/jats:p" "/jats:sec""jats:sec" "jats:title"Results"/jats:title" "jats:p"Results show people hold different expectations towards each type of AV service. These expectations act as the minimum requirements for people to pay for the AV services. Respondents are found to be willing to pay more for PAV service if it is safe, provides good ride comfort, and is competitively priced relative to the price travelling by metro and train over a same distance. Other than service quality attribute perceptions, income level, existing travel modes for daily trips, familiarity with automated driving technology and AB ride experience are important factors affecting WTP for the AV services."/jats:p" "/jats:sec""jats:sec" "jats:title"Conclusion"/jats:title" "jats:p"The developed model can be applied to understand expectations of potential users towards a new AV service, and to identify user groups who are willing to pay the service. New AV services can thus be designed sensibly according to users’ actual needs."/jats:p" "/jats:sec

Document type: Article

Termite inspired algorithm for traffic engineering in hybrid software defined networks

Scipedia content — Fri, 12 Feb 2021 14:44:27 +0100

In the era of Internet of Things and 5G networks, handling real time network traffic with the required Quality of Services and optimal utilization of network resources is a challenging task. Traffic Engineering provides mechanisms to guide network traffic to improve utilization of network resources and meet requirements of the network Quality of Service (QoS). Traditional networks use IP based and Multi-Protocol Label Switching (MPLS) based Traffic Engineering mechanisms. Software Defined Networking (SDN) have characteristics useful for solving traffic scheduling and management. Currently the traditional networks are not going to be replaced fully by SDN enabled resources and hence traffic engineering solutions for Hybrid IP/SDN setups have to be explored. In this paper we propose a new Termite Inspired Optimization algorithm for dynamic path allocation and better utilization of network links using hybrid SDN setup. The proposed bioinspired algorithm based on Termite behaviour implemented in the SDN Controller supports elastic bandwidth demands from applications, by avoiding congestion, handling traffic priority and link availability. Testing in both simulated and physical test bed demonstrate the performance of the algorithm with the support of SDN. In cases of link failures, the algorithm in the SDN Controller performs failure recovery gracefully. The algorithm also performs very well in congestion avoidance. The SDN based algorithm can be implemented in the existing traditional WAN as a hybrid setup and is a less complex, better alternative to the traditional MPLS Traffic Engineering setup.

Document type: Article

Numerical Investigation into Freak Wave Effects on Deepwater Pipeline Installation

Scipedia content — Fri, 12 Feb 2021 14:45:25 +0100

Freak waves are an extreme marine environment factor in offshore structure design and become a potential risk, particularly for laying oil-gas pipelines in deep waters. The objective of this study was to reveal the freak wave effects on dynamic behaviors of offshore pipelines for deepwater installation. Thus, a dedicated finite element model (FEM) for deepwater pipeline installation by the S-lay method was developed with special consideration of freak waves. The FEM also took pipelay vessel motions, pipe&ndash

stinger roller interactions, and the cyclic contacts between the pipeline and seabed soil into account. Real vessel and stinger data from an actual engineering project in the South China Sea were collected to obtain an accurate simulation. Moreover, an effective superposition approach of combined transient wave trains and random wave trains was introduced, and various types of freak wave trains were simulated. Extensive numerical analyses of a 12 inch gas pipeline being installed into a water depth of 1500 m were implemented under various freak wave conditions. The noticeable influences of freak waves on the pipeline and seabed responses were identified, which provides significant awareness of offshore pipelines for deepwater installation design and field operation monitoring.

Document type: Article

A NEW SATELLITE IMAGERY STEREO PIPELINE DESIGNED FOR SCALABILITY, ROBUSTNESS AND PERFORMANCE

Scipedia content — Fri, 12 Feb 2021 14:46:00 +0100

Abstract. This paper presents a new Multiview Stereo Pipeline (MVS), called CARS, dedicated to satellite imagery. This pipeline is intended for massive Digital Surface Model (DSM) production and has therefore been designed to maximize scalability robustness and performance. Those two properties have driven the design of the workflow as well as the choice of algorithms and parameter trends, making our pipeline unique with respect to existing solutions in literature. This paper intends to serve as a reference paper for the pipeline implementation, and therefore provides a detailed description of algorithms and workflow. It also demonstrates the pipeline robustness and stability in several use cases, and compares its accuracy with the state-of-the-art pipelines on a reference dataset.

Document type: Article

An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand

Scipedia content — Fri, 12 Feb 2021 14:46:34 +0100

The development of high-speed railways (HSR) in China has attracted a large number of passengers from highway and aviation to railways due to their comfort and high speed. In this case, HSR passenger transportation can improve the operating income by optimizing the ticket allocation. Here, we propose an optimization method of multiclass price railway passenger transport ticket allocation under high passenger demand. First, for the “censored data” problem in the railway passenger demand forecast, we constructed an unconstrained model of railway passenger demand and solved the unconstrained demand through an expectation-maximization algorithm. Then, on this basis, we use gray neural networks (GNNs) to predict the passenger demand of different origins and destinations (ODs), and according to the prediction results, we propose two ticket allocation methods based on operation and capacity control: accurate predivided model and fuzzy predivided model. And we solve this problem by constructing a particle swarm optimization algorithm. Lastly, we use examples to prove that the proposed ticket allocation method can meet the passengers’ needs and have good economic benefits.

Document type: Article

Identification of factors affecting competitive tension in the domestic air transport market in Turkey

Scipedia content — Fri, 12 Feb 2021 14:46:48 +0100

Competitive tension refers to pressure that is considered to exist among firms operating in a competitive market and that forces them to take competitive action against each other. An imaginary upper limit of competitive tension symbolizes the difference between whether to take competitive action or not. The antecedents of competitive tension are examined in this study. Within this scope, market commonality and resource similarity are the variables studied as components of competitor analysis; market concentration that provides clues for the competitive structure of competed markets; and finally, competitive asymmetry, presuming that the competition among the companies is not equal and rivals do not consider each other at the same level as competing firms, were taken as primary variables of competitive tension. In order to test whether these variables have an effect on competitive tension among airlines, airlines operating in the domestic air transport market in Turkey were examined in this study. The perceived competitive tension that was detected as a result of regression analyses was studied on three different dimensions, namely, internal tension, external tension, and total tension, and each dimension was analyzed as a different model. The findings of the study revealed that market commonality and market concentration have a significant effect on competitive tension. These effects were found to be positive for market commonality and negative for market concentration. Resource similarity and competitive asymmetry were found to have no significant effect.

Document type: Article

PipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools

Scipedia content — Fri, 12 Feb 2021 14:47:05 +0100

We present pipeComp ( https://github.com/plger/pipeComp ), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on multi-level evaluation metrics. We apply it to the benchmark of single-cell RNA-sequencing analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction, and clustering. pipeComp can easily integrate any other step, tool, or evaluation metric, allowing extensible benchmarks and easy applications to other fields, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.

Document type: Article

Driving Fatigue Prediction Model considering Schedule and Circadian Rhythm

Scipedia content — Fri, 12 Feb 2021 14:48:13 +0100

Driver fatigue level was considered an accumulated result contributed by circadian rhythms, hours of sleep before driving, driving duration, and break time during driving. This article presents an investigation into the regression model between driver fatigue level and the above four time-related variables. With the cooperation of one commercial transportation company, a Naturalistic Driving Study (NDS) was conducted, and NDS data from thirty-four middle-aged drivers were selected for analysis. With regard to the circadian rhythms, commercial drivers operated the vehicle and started driving at around 09:00, 14:00, and 21:00, respectively. Participants’ time of sleep before driving is also surveyed, and a range from 4 to 7 hours was selected. The commercial driving route was the same for all participants. After getting the fatigue level of all participants using the Karolinska Sleepiness Scale (KSS), the discrete KSS data were converted into consecutive value, and curve fitting methods were adopted for modeling. In addition, a linear regression model was proposed to represent the relationship between accumulated fatigue level and the four time-related variables. Finally, the prediction model was verified by the driving performance measurement: standard deviation of lateral position. The results demonstrated that fatigue prediction results are significantly relevant to driving performance. In conclusion, the fatigue prediction model proposed in this study could be implemented to predict the risk driving period and the maximum consecutive driving time once the driving schedule is determined, and the fatigue driving behavior could be avoided or alleviated by optimizing the driving and break schedule.

Document type: Article

Characterization of Daily Travel Distance of a University Car Fleet for the Purpose of Replacing Conventional Vehicles with Electric Vehicles

Scipedia content — Fri, 12 Feb 2021 14:49:13 +0100

This study attempts to fit daily travel distances (DTD) data collected from the Nagoya University (NU) car-sharing system for one year to several distribution functions, including a lognormal mixture model. It is deemed here that the lognormal distribution performs best among the five tested single-distribution functions based on their "i"p"/i"-values. Moreover, the lognormal mixture model can represent the driving pattern better overall with respect to the Akaike information criterion (AIC). Taking two types of electric vehicles (EVs) into consideration, the results show that 30 out of 48 vehicles can be substituted by the EV type with a larger battery capacity according to the observed DTD data and when a 95% confidence level is considered. In this exercise, the updated car-sharing system can have up to nine available vehicles at peak hour, which can reach the peak-shaving need and provides the possibility of contributing electricity for common use with the help of the vehicle-to-grid (V2G) system. Additionally, the updated system with a larger battery capacity can also reduce 24% of the CO"sub"2"/sub" emissions. These types of systems could be widely applied to other organizations or companies in the consideration of electricity consumption and emission reduction.

Document type: Article

Study of the Sediment Transport Law in a Reverse-Slope Section of a Pressurized Pipeline

Scipedia content — Fri, 12 Feb 2021 14:50:32 +0100

This article reveals the change law of the head loss and critical deposition velocity during hydraulic transmission of a solid–liquid two-phase pipeline. This article also establishes a physical test model. A single variable is used to conduct the experimental research by changing the conditions of the pipeline flow rate, the sediment concentration, and the reverse slope degree. Based on an analysis of the test process, a new formula is proposed to determine the critical sedimentation rate of the pipeline that considers a change in the adverse slope. By analyzing the variation rule of the hydraulic slope of the pipeline sediment in different states and comparing the hydraulic slope of the horizontal pipeline and reverse pipeline in different states, different factors that influence head loss are revealed. Finally, the measured value of this test is compared with the Durand equation and the Worster equation. It was found that the measured value of this test was more similar to the Durand equation. This study not only provides theoretical support for sand removal in pipelines but also promotes sedimentation in reservoirs.

Document type: Article

The impact of driving homogeneity due to automation and cooperation of vehicles on uphill freeway sections

Scipedia content — Fri, 12 Feb 2021 14:51:01 +0100

Background Surging acceptance of adaptive cruise control (ACC) across the globe is further escalating concerns over its energy impact. Two questions have directed much of this project: how to distinguish ACC driving behaviour from that of the human driver and how to identify the ACC energy impact. As opposed to simulations or test-track experiments as described in previous studies, this work is unique because it was performed in real-world car-following scenarios with a variety of vehicle specifications, propulsion systems, drivers, and road and traffic conditions. Methods Tractive energy consumption serves as the energy impact indicator, ruling out the effect of the propulsion system. To further isolate the driving behaviour as the only possible contributor to tractive energy differences, two techniques are offered to normalize heterogeneous vehicle specifications and road and traffic conditions. Finally, ACC driving behaviour is compared with that of the human driver from transient and statistical perspectives. Its impact on tractive energy consumption is then evaluated from individual and platoon perspectives. Results Our data suggest that unlike human drivers, ACC followers lead to string instability. Their inability to absorb the speed overshoots may partly be explained by their high responsiveness from a control theory perspective. Statistical results might imply the followers in the automated or mixed traffic flow generally perform worse in reproducing the driving style of the preceding vehicle. On the individual level, ACC followers have tractive energy consumption 2.7 – 20.5 % higher than those of human counterparts. On the platoon level, the tractive energy values of ACC followers tend to consecutively increase (11.2 – 17.3 %). Conclusions In general, therefore, ACC impacts negatively on tractive energy efficiency. This research provides a feasible path for evaluating the energy impact of ACC in real-world applications. Moreover, the findings have significant implications for ACC safety design when handling the stability-responsiveness trade-off.

Document type: Article

Analysis of Rock Raw Materials Transport and its Implications for Regional Development and Planning. Case Study of Lower Silesia (Poland)

Scipedia content — Fri, 12 Feb 2021 14:51:27 +0100

The movement of rock raw materials from source to demand areas is carried out predominately with road and railway transport. The latter is less damaging to infrastructure, the environment and society and is cheaper for longer distances, but it is also less flexible and not widely used. The Lower Silesia region in southwestern Poland is an important producer of rock raw materials and the principal provider of igneous and metamorphic dimension stones and crushed rocks in the country. A multicriteria scoring scheme has been developed and applied to identify mines presently using road transport, that are predisposed to switch to or include a railway form of transport. Four criteria have been proposed, C1&mdash

distance to railway loading point, C2&mdash

annual production of rock raw material, C3&mdash

economic reserves, and C4&mdash

type of rock raw material. The scoring scheme (classification) was developed based on the results of descriptive statistics for mines presently using railway or combined road and railway forms of transport. Two scenarios were analyzed, one with equal weights (0.25) and the other with higher significance of C1 = 0.40 and C2 = 0.30, and lower significance of C3 = 0.20 and C4 = 0.10. In the result, 24 mines were identified and ranked in terms of their potential to introduce railway transport. The proposed methodology can be used universally for other regions and countries, and the results will be included in drawing up regional spatial development policies.

Document type: Article

Railway Safety Risk Assessment and Control Optimization Method Based on FTA-FPN: A Case Study of Chinese High-Speed Railway Station

Scipedia content — Fri, 12 Feb 2021 14:51:42 +0100

In order to make safety risk assessment more accurately and more reasonably for high-speed railway station in China, this paper analyzes risk factors of fault tree and transfers the fault tree of risk accident into fuzzy petri net and then builds the FPN-FTA model by combining the dynamic weighting fuzzy petri net (FPN) and fault tree analysis (FTA) based on the latter. This paper simulates the FTA-FPN model with Stateflow of Matlab software. Then, it builds up a bi-objective risk control model, making the minimum safety risk level and minimum necessary cost as the objectives, and it designs discrete particle swarm optimization algorithm to solve the risk control model. Finally, this paper selects stampede accident of Shijiazhuang high-speed railway station as an example in case study for assessing stampede risk level and gets the risk control schemes for this station. The results verify the feasibility and validity of the model and algorithm.

Document type: Article

Performance Analysis of Decentralized VS Centralized Control for the Traffic Signal Synchronization Problem

Scipedia content — Fri, 12 Feb 2021 14:52:34 +0100

This paper suggests the adoption of a spatial decomposition method to solve the signal synchronization problem. A good signal setting maximizes the number of vehicles passing through intersections, while minimizing gas emissions and possible delays experienced by drivers. The signals synchronization issue can be defined as the problem of finding the offsets, the green timings, and the cycle length for a series of controlled intersections, minimizing the total delay of the network subject to admissibility constraints. In this paper, the authors optimized the signal setting through a new Surrogate Method calculating the objective function via the "jats:inline-formula" "math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"" "msub" "mrow" "mtext"CTM"/mtext" "/mrow" "mrow" "mtext"UT"/mtext" "/mrow" "/msub" "/math" "/jats:inline-formula" model while performing a simulation. A spatial decomposition approach is here suggested with a simultaneous analysis of different levels of cooperation among subnetworks. This study tries to identify a subnetwork that might be representative of the entire network while taking into consideration two factors: efficiency and efficacy. A comparison between centralized and decentralized control is performed.

Document type: Article

Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network

Scipedia content — Fri, 12 Feb 2021 14:52:49 +0100

This paper proposes an evaluation method based on a T-S fuzzy neural network for evaluating the speed grade of public-transport lines in the context of large-scale rail-transit planning and construction in Hangzhou. The six-dimensional data of morning peak/evening peak average speed, average speed at peak, average station distance, proportion of dedicated lanes, and nonlinear coefficients were selected as input data for the neural network to output the operating speed grade of bus lines. Improving and optimizing the membership function of the Takagi–Sugeno (T-S) model improves its predicted result accuracy compared to a traditional T-S model. The line data of 28 typical trunk lines or expressways in Hangzhou were used as an example; the results demonstrate that the speed grade evaluation method based on an improved T-S fuzzy neural network can effectively and quickly evaluate the speed grade of Hangzhou public-transportation lines. This paper presents a novel analysis and method for large-scale rail-transit planning and evaluation of urban public-transport lines. The aim is to provide practical instruction for the subsequent optimization of public-transportation lines in Hangzhou.

Document type: Article

Scalable System for Smart Urban Transport Management

Scipedia content — Fri, 12 Feb 2021 14:54:20 +0100

Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heterogeneous data, in order to perform smart analytics of urban networks in real time. However, dynamic response that relies on intelligent demand-side transport management is particularly challenging due to the increasing flow of transmitted sensor data. In this work, a novel smart service-driven, adaptable middleware architecture is proposed to acquire, store, manipulate, and integrate information from heterogeneous data sources in order to deliver smart analytics aimed at supporting strategic decision-making. The architecture offers adaptive and scalable data integration services for acquiring and processing dynamic data, delivering fast response time, and offering data mining and machine learning models for real-time prediction, combined with advanced visualisation techniques. The proposed solution has been implemented and validated, demonstrating its ability to provide real-time performance on the existing, operational, and large-scale bus network of a European capital city.

Document type: Article

Examining the Environmental, Vehicle, and Driver Factors Associated with Crossing Crashes of Elderly Drivers Using Association Rules Mining

Scipedia content — Fri, 12 Feb 2021 14:54:37 +0100

In the aging society, reducing vehicle crashes caused by elderly drivers has become a crucial issue. To find effective methods to reduce these vehicle crashes, it is necessary to give some insights into the characteristics of vehicle crashes and those of traffic violations caused by elderly drivers. However, multiple significant factors associated with crossing crashes due to elderly drivers were not extensively observed in previous studies. To fill this research gap, this study identifies the crash pattern and examines the environmental, vehicle, and driver factors associated with crossing crashes due to elderly drivers. The 5-year crash data in Toyota City, Japan, are used for empirical analysis. The emerging data mining method called association rules mining is applied to discover various factors associated with crossing crashes of elderly and nonelderly drivers, respectively. The significant findings indicate that (1) elderly drivers are more likely to lead to crossing or right-turn crashes, compared with nonelderly drivers; (2) there are more factors including crash location (intersection without signal), lighting (daylight), road condition (dry and other), weather condition (clear and raining), vehicle type (light motor truck), and traffic violation (fail to confirm safety) associated with the large proportion of crossing crashes due to elderly drivers. The findings of this study can be used by traffic safety professionals to implement some countermeasures to reduce the crossing crashes due to elderly drivers.

Document type: Article

User rating and acceptance of attention-adaptive driver safety systems

Scipedia content — Fri, 12 Feb 2021 14:57:51 +0100

Current statistics show that distraction is a central cause of traffic accidents. Safety systems with distance control currently available on the market have great potential for preventing accidents and significantly reducing their severity. However, depending on the driver’s level of attention, the systems warn too early or too late, which impairs use acceptance. Adaptive systems allow for personalization according to driver’s attention level. Studies were carried out in a driving simulator in order to compare the system adaptations with regard to acceptance for attentive and distracted driving phases. Seventy-two participants took part in the study, with a between-subjects test design. Acceptance ratings shows highest acceptability for the adaptive systems in distractive situations. We conclude that personalization of attention-adaptive systems shall be implemented in case safety benefits are proven.

Document type: Article

A Study on Determining Time-Of-Flight Difference of Overlapping Ultrasonic Signal: Wave-Transform Network

Scipedia content — Fri, 12 Feb 2021 14:58:32 +0100

An ultrasonic sensors system is commonly used to measure the wall thickness of buried pipelines in the transportation of oil and gas. The key of the system is to precisely measure time-of-flight difference (TOFD) produced by the reflection of ultrasonic on the inner and outer surfaces of the pipelines. In this paper, based on deep learning, a novel method termed Wave-Transform Network is proposed to tackle the issues. The network consists of two parts: part 1 is designed to separate the potential overlapping ultrasonic echo signals generated from two surfaces, and part 2 is utilized to divide the sample points of each signal into two types corresponding to before and after the arrival time of ultrasonic echo, which can determine the time-of-flight (TOF) of each signal and calculate the thickness of pipelines. Numerical simulation and actual experiments are carried out, and the results show satisfactory performances.

Document type: Article

A Framework for Detecting Vehicle Occupancy Based on the Occupant Labeling Method

Scipedia content — Fri, 12 Feb 2021 15:01:47 +0100

High-occupancy vehicle (HOV) lanes or congestion toll discount policies are in place to encourage multipassenger vehicles. However, vehicle occupancy detection, essential for implementing such policies, is based on a labor-intensive manual method. To solve this problem, several studies and some companies have tried to develop an automated detection system. Due to the difficulties of the image treatment process, those systems had limitations. This study overcomes these limits and proposes an overall framework for an algorithm that effectively detects occupants in vehicles using photographic data. Particularly, we apply a new data labeling method that enables highly accurate occupant detection even with a small amount of data. The new labeling method directly labels the number of occupants instead of performing face or human labeling. The human labeling, used in existing research, and occupant labeling, this study suggested, are compared to verify the contribution of this labeling method. As a result, the presented model’s detection accuracy is 99% for the binary case (2 or 3 occupants or not) and 91% for the counting case (the exact number of occupants), which is higher than the previously studied models’ accuracy. Basically, this system is developed for the two-sided camera, left and right, but only a single side, right, can detect the occupancy. The single side image accuracy is 99% for the binary case and 87% for the counting case. These rates of detection are also better than existing labeling.

Document type: Article

Orthogonal Reference Surrogate Fuels for Operability Testing

Scipedia content — Fri, 12 Feb 2021 15:02:41 +0100

The approval and evaluation process for sustainable aviation fuels (SAF) via ASTM D4054 is both cost- and volume-intensive, namely due to engine operability testing under severe conditions. Engine operability tests of combustor under figures of merit (FOM) limit phenomena are the fuel effects on lean blowout, high-altitude relight, and cold-start ignition. One method to increase confidence and reduce volume in tiered testing is to use surrogate fuels for manipulation of properties. Key fuel performance properties (surface tension, viscosity, density) for cold-start ignition was determined prior to this study. Prior work regarding this FOM has not considered the combination of these properties. A surface tension blending rule was validated and incorporated into the jet fuel blend optimizer (JudO). A generalized surrogate calculator for N-dimensional surrogate components and features was developed. Jet fuel surrogates developed in this study were a mixture of conventional and sustainable aviation fuels instead of pure components. These surrogates suggested to be tested in this study could illuminate near worst-case effects for sustainable aviation fuel in a given configuration/rig. With those scenarios tested, we can further understand the influence on the key properties relative to cold-start ignition. This work and supporting experimental evidence could potentially lower the barrier for SAF approval processes.

Document type: Article

Participation of an EV aggregator in the reserve market through chance-constrained optimization

Scipedia content — Fri, 12 Feb 2021 15:02:56 +0100

The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a failure in the provision of upward or downward reserve. Therefore, stochastic and chance-constrained programming are used to handle the uncertainty of a small fleet of EVs and the risk profile of the EV aggregator. Two different relaxation approaches, i.e., Big-M and McCormick, of the chance-constrained model are tested and validated for different number of scenarios and risk levels, based on an actual test case in Denmark with actual driving patterns. As a final remark, the McCormick relaxation presents better performance when the uncertainty budget increases, which is appropriated for large-scale problems.

Document type: Article

Investigation of Thermal Effects in Different Lightweight Constructions for Vehicular Wireless Power Transfer Modules

Scipedia content — Fri, 12 Feb 2021 15:06:19 +0100

This paper presents a thermal investigation of lightweight on-board receiver modules of wireless power transfer systems for electric vehicles. The studied modules are capable of receiving up to 11 kW at a resonance frequency of 85 kHz over a distance of 110–160 mm. The receiver modules were built as sandwich and space–frame concept to design stiff and lightweight structures. The high transmission power of automotive wireless power transfer systems combined with the multi-part assembly of receiver modules led to challenges in heat management. To address this, the physical behaviour of the proposed lightweight concepts were studied on component and system level using a hardware-in-the-loop testing facility for wireless power transfer systems. Special emphasis was laid on the validation of a thermal simulation model, which uses analytical calculated power losses taking into account their temperature dependency. The proposed simulation model is consistent with the experimental validation of the critical active components. The performed systematic studies build the basis for a more sophisticated thermal dimensioning of various constructions for wireless power transfer modules.

Document type: Article

Single-Point Adaptive Control Method for Urban Mixed Traffic Flow

Scipedia content — Fri, 12 Feb 2021 15:06:35 +0100

In urban traffic, motor vehicles, nonmotor vehicles, pedestrians, and other traffic are mixed, which seriously affects the urban traffic efficiency. At the intersections of urban roads especially, the priority setting of various travel modes is crucial to improve the urban traffic efficiency. In the urban hybrid traffic system, the architecture and algorithm flowchart of the single-point adaptive control system for urban hybrid traffic flow are presented. The control effect of this method is verified by VISSIM software. The simulation results show that the traffic efficiency of the priority objects at the intersection is increased by 6.03%, and the overall traffic efficiency is also significantly improved. This method has a certain practical value.

Document type: Article

Trip and Personal Characteristics towards the Intention to Cycle in Larnaca, Cyprus: An EFA-SEM Approach

Scipedia content — Fri, 12 Feb 2021 15:06:51 +0100

Mobility is one of the most important and challenging aspects that influence climate change, air quality, and especially the quality of citizens&rsquo

lives. Therefore, creating sustainable transport solutions makes way for different modes of transport such as the bicycle, which is continuously gaining more supporters, due to the health, economic, and environmental benefits that it provides. However, cyclists are facing several barriers (e.g., lack of infrastructure), a fact that keeps away commuters from using a bicycle for their daily trips. Investigating the factors that reflect on the commuters&rsquo

intention to use a bicycle is a sine qua non for the promotion of sustainable mobility. Therefore, the objective of this paper is the investigation of the factors that prevent residents with low experience or with no cultural/lifestyle background in regards to cycling from cycling. The case study of the city of Larnaca (Cyprus) is deployed by exploring the socio-demographic and trip characteristics of the city&rsquo

s residents and their relation with the intention to cycle. A two-step approach is developed, namely Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM). Despite the promotion of cycling that education is attempting to do (successfully), other factors (such as age, distance, and time) appear to prevent Larnaca&rsquo

s residents from cycling. Among the actions that local authorities should undertake is that of safety prevention of the vulnerable users of the road network. This group includes elderly people, who need major encouraging interventions by local policymakers and stakeholders.

Document type: Article

How Accurate Can UWB and Dead Reckoning Positioning Systems Be? Comparison to SLAM Using the RPLidar System

Scipedia content — Fri, 12 Feb 2021 15:08:07 +0100

This paper compares two positioning systems, namely ultra-wideband (UWB) based micro-location technology and dead reckoning and a RPLidar based simultaneous localization and mapping (SLAM) solution. This new approach can be used to improve the quality of the positioning system and increase the functionality of advanced driver assistance systems (ADAS). This is achieved by using stationary nodes and UWB tags on the vehicles. Thus, the redundancy of localization can be achieved by this approach, e.g., as a backup to onboard sensors like RPlidar or radar. Additionally, UWB based micro-location allows additional data channels to be used for communication purposes. Furthermore, it is shown that the regular use of correction data increases UWB and dead reckoning accuracy. These correction data can be based on onboard sensors. This shows that it is promising to develop a system that fuses onboard sensors and micro-localization for safety-critical tasks like the platooning of commercial vehicles.

Document type: Article

A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

Scipedia content — Fri, 12 Feb 2021 15:09:07 +0100

Based on the price-quantity adjustment behaviour principle of disequilibrium theory, the route choices of travellers are also affected by a quantity signal known as traffic flow, while the route cost is considered as a price signal in economics. Considering the quantity signal’s effect among travellers, a new route comfort choice behaviour criterion and its corresponding equilibrium condition are established. The network travellers are classified into three groups according to their route choice behaviour: travellers in the first group choose the shortest route following the route rapidity behaviour criterion with complete information forming the UE (user equilibrium) pattern, travellers in the second group choose the most comfortable route following the route comfort behaviour criterion with complete information forming the QUE (quantity adjustment user equilibrium) pattern, and travellers in the third group choose a route according to their perceived travel time with incomplete information forming the SUE (stochastic user equilibrium) pattern. The traffic flows of all three groups converge to a new UE-QUE-SUE mixed equilibrium flow pattern after interaction. To depict the traveller-diversified choice behaviour and the traffic flow interaction process, a mixed equilibrium traffic flow evolution model is formulated. After defining the route comfort indicator and the corresponding user equilibrium state, the equilibrium conditions of the three group flows are given under a mixed equilibrium pattern. In addition, an equivalent mathematical programming of the mixed equilibrium traffic flow evolution model is proposed to demonstrate that the developed model converges to the mixed equilibrium state. Finally, numerical examples are examined to evaluate the effect of route comfort proportions on the traffic network flow evolution and analyse the performance of the proposed model.

Document type: Article

The Design a TDCP-Smoothed GNSS/Odometer Integration Scheme with Vehicular-Motion Constraint and Robust Regression

Scipedia content — Fri, 12 Feb 2021 15:12:06 +0100

Global navigation satellite system (GNSS) is widely regarded as the primary positioning solution for intelligent transport system (ITS) applications. However, its performance could degrade, due to signal outages and faulty-signal contamination, including multipath and non-line-of-sight reception. Considering the limitation of the performance and computation loads in mass-produced automotive products, this research investigates the methods for enhancing GNSS-based solutions without significantly increasing the cost for vehicular navigation system. In this study, the measurement technique of the odometer in modern vehicle designs is selected to integrate the GNSS information, without using an inertial navigation system. Three techniques are implemented to improve positioning accuracy; (a) Time-differenced carrier phase (TDCP) based filter: A state-augmented extended Kalman filter is designed to incorporate TDCP measurements for maximizing the effectiveness of phase-smoothing; (b) odometer-aided constraints: The aiding measurement from odometer utilizing forward speed with the lateral constraint enhances the state estimation; the information based on vehicular motion, comprising the zero-velocity constraint, fault detection and exclusion, and dead reckoning, maintains the stability of the positioning solution; (c) robust regression: A weighted-least-square based robust regression as a measurement-quality assessment is applied to adjust the weightings of the measurements adaptively. Experimental results in a GNSS-challenging environment indicate that, based on the single-point-positioning mode with an automotive-grade receiver, the combination of the proposed methods presented a root-mean-square error of 2.51 m, 3.63 m, 1.63 m, and 1.95 m for the horizontal, vertical, forward, and lateral directions, with improvements of 35.1%, 49.6%, 45.3%, and 21.1%, respectively. The statistical analysis exhibits 97.3% state estimation result in the horizontal direction for the percentage of epochs that had errors of less than 5 m, presenting that after the intervention of proposed methods, the positioning performance can fulfill the requirements for road level applications.

Document type: Article

An Energy Solution for Predicting Buried Pipeline Response Induced by Tunneling Based on a Uniform Ground Movement Model

Scipedia content — Fri, 12 Feb 2021 15:12:48 +0100

The construction of shield tunnels inevitably causes displacement of the surrounding soil and additional stress and deformation of the buried pipeline. An energy solution for predicting the deformation of buried pipelines caused by tunneling is proposed in this study. First, based on the uniform ground movement model, the interval of the free displacement field of soil around the pipeline induced by tunneling is calculated. Then, we use the Pasternak model to establish the total potential energy equation of the tunnel-soil-pipeline interaction. The final settlement interval of the pipeline is obtained by solving the numerical calculation program with MATLAB. The calculation results of the energy solution are compared with the results of the centrifugal test and the reported theoretical solutions of Winkler and Pasternak, and then the applicability of the solution for predicting the pipeline response under different geotechnical conditions is verified. Combined with an engineering case, the energy method calculation results, numerical simulation results, and measured results are compared to obtain the most unfavorable position of the pipeline caused by tunneling. At the end of this study, the application steps of the proposed method in actual construction are summarized. These steps are used to predict pipeline response in order to take protective measures.

Document type: Article

The Bird Strike Challenge

Scipedia content — Fri, 12 Feb 2021 16:03:22 +0100

Collisions between birds and aircraft pose a severe threat to aviation and avian safety. To understand and prevent these bird strikes, knowledge about the factors leading to these bird strikes is vital. However, even though it is a global issue, data availability strongly varies and is difficult to put into a global picture. This paper aims to close this gap by providing an in-depth review of studies and statistics to obtain a concise overview of the bird strike problem in commercial aviation on an international level. The paper illustrates the factors contributing to the occurrence and the potential consequences in terms of effect on flight and damage. This is followed by a presentation of the risk-reducing measures currently in place as well as their limitations. The paper closes with an insight into current research investigating novel methods to prevent bird strikes.

Document type: Article

Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network

Scipedia content — Fri, 12 Feb 2021 16:03:52 +0100

To study the guidance method of driverless travel mode choice from the perspective of traffic supply-demand, we assume that all vehicles are driverless and establish a multimodal travel market model to depict the supply-demand relationship of multimodal driverless transportation network. To regulate the disequilibrium multimodal travel market, an optimal price regulation law is proposed, which aims to minimize the supply-demand deviation and the amplitude of price regulation. Then, the existence, uniqueness, and stability of the optimal price regulation law are confirmed. In the calculation process of a numerical example, the travel prices of driverless car and driverless subway are realized by congestion fee and subway fare, respectively. The results indicate that the optimal price regulation law can reduce the supply-demand deviation of the multimodal travel market and guide travelers to choose a reasonable travel mode to travel in the driverless transportation network.

Document type: Article

A weighted travel time index based on data from Uber Movement

Scipedia content — Fri, 12 Feb 2021 16:06:50 +0100

In this paper, we combine data from Uber Movement and from a representative household travel survey to constructs a weighted travel time index for the Metropolitan Region of São Paulo. The index is calculated based on the average travel time of Uber trips taken between each pair of traffic zone and in each hour between January 1st, 2016 to December 31, 2018. The index is weighted based on trips reported in a household travel survey that was designed to be statistically representative of all trips made in the city during a typical business day. We show that the index has a strong correlation with traditional measures of congestion, however, with a broader coverage of the road network. Finally, we use the index to run a multivariate ex-post analysis that estimates the effect of different events on traffic congestion in the city, including holidays, public transit strikes, road shutdowns, rain and major sport events.

Document type: Article

Digital Transformation Supporting Transport Decarbonisation: Technological Developments in EU-Funded Research and Innovation

Scipedia content — Fri, 12 Feb 2021 16:07:42 +0100

The European Commission&rsquo

s Communication on a European Green Deal sets out the objective of achieving climate neutrality by 2050, which will require a reduction in transport emissions. To this aim, digital technologies, together with connectivity and automation, are transforming traditional concepts of mobility, with a potential impact towards transport decarbonisation. New business models are emerging and giving rise to innovative mobility services including new online platforms for car-pooling, car or bicycle sharing services, freight operations, or smartphone applications offering real-time travel information and other analytics. This study provides an overview of the European Union (EU) funded research and innovation (R&

I) and related technologies that are influencing the uptake of digital transformation in transport and identifies issues and challenges from a European perspective. To that end, it follows a two-tier approach that examines policy and legislative initiatives from the European Commission, highlighting possible challenges and enablers. Moreover, it analyses transport technology developments in Europe, focusing on the technology maturity from EU R&

I framework programmes, using the European Commission&rsquo

s Transport Research and Innovation Monitoring and Information System (TRIMIS). The technology analysis provides insights that aid policy decisions related to funding allocation in future R&

I framework programmes.

Document type: Article

BEHT: Blockchain-Based Efficient Highway Toll Paradigm for Opportunistic Autonomous Vehicle Platoon

Scipedia content — Fri, 12 Feb 2021 16:07:57 +0100

Autonomous vehicle platoon is a promising paradigm towards traffic congestion problems in the intelligent transportation system. However, under certain circumstances, the advantage of the platoon cannot be fully developed. In this paper, we focus on the highway Electronic Toll Collection (ETC) charging problem. We try to let the opportunistic platoon pass the ETC as a whole. There are three main issues in this scenario. Firstly, the opportunistic platoon is temporarily composed; vehicles do not trust each other. Secondly, single vehicle may try to escape from the ETC charging by following the platoon. Finally, platoon members may collude with each other and try to underreport the number of vehicles in the platoon so as to evade payment. To solve these challenges, we propose a blockchain-based efficient highway toll paradigm for the opportunistic platoon. The driving history, credential information of every registered vehicle, is recorded and verified from the blockchain. A roadside unit (RSU) is adopted to distinguish the single vehicle from the platoon and in charge of lane allocation. Additionally, an aggregate signature is introduced to accelerate the authentication procedure in the RSU. We analyse the potential security threats in this scenario. The experimental result indicates that our scheme is efficient and practical.

Document type: Article

Analysis of Complex Transportation Network and Its Tourism Utilization Potential: A Case Study of Guizhou Expressways

Scipedia content — Fri, 12 Feb 2021 16:08:20 +0100

Transportation is an example of a typical, open, fluid complex network system. Expressways are one form of complex transportation networks, and expressway service areas serve as infrastructure nodes in the expressway transportation network; hence, their construction has a significant impact on tourism development and utilization. Domestic and foreign studies on complex transportation networks have mostly been conducted from the perspective of railways, air transport, and urban transportation but seldom on expressway transportation networks. This study employed complex network theory, social network analysis, kernel density analysis, and bivariate autocorrelation to characterize the spatial structure of expressway transport networks in terms of geographical centrality. By innovating the coupling of geographical centrality and passenger flow centrality in clustering, the study also quantitatively analyzed the differences between the geographical advantage and actual passenger flow advantage of China’s Guizhou expressway transportation network to analyze the tourism utilization potential of expressway service areas. We found that (1) the geographical centrality of the Guizhou expressway transportation network ranged from −1.28 to 3.33, and its distribution shows a single-core, polyconcentric dispersed spatial structure; (2) the passenger-car flow rate ranged from 15,000 to 3.66 million, and its distribution showed a dual-core, polycentric dispersed structure that is weakly concentric; and (3) there was a positive correlation of 0.22 between the geographical centrality and passenger flow of the Guizhou expressway transportation network, which showed seven cluster types—“high-high,” “moderately high-high,” “low-high,” “moderately low-high,” “high-low,” “moderately high-low,” and “low-low”—for which seven corresponding models of tourism development were proposed. This study broadens the practical application of traffic network complexity research and provides a scientific basis for upgrading and transforming the Guizhou expressway transportation network as well as for developing composite tourism uses for expressway service areas.

Document type: Article

A Method for the Combined Estimation of Battery State of Charge and State of Health Based on Artificial Neural Networks

Scipedia content — Fri, 12 Feb 2021 16:12:33 +0100

This paper proposes a method for the combined estimation of the state of charge (SOC) and state of health (SOH) of batteries in hybrid and full electric vehicles. The technique is based on a set of five artificial neural networks that are used to tackle a regression and a classification task. In the method, the estimation of the SOC relies on the identification of the ageing of the battery and the estimation of the SOH depends on the behavior of the SOC in a recursive closed-loop. The networks are designed by means of training datasets collected during the experimental characterizations conducted in a laboratory environment. The lithium battery pack adopted during the study is designed to supply and store energy in a mild hybrid electric vehicle. The validation of the estimation method is performed by using real driving profiles acquired on-board of a vehicle. The obtained accuracy of the combined SOC and SOH estimator is around 97%, in line with the industrial requirements in the automotive sector. The promising results in terms of accuracy encourage to deepen the experimental validation with a deployment on a vehicle battery management system.

Document type: Article

Analysis of the State-Dependent Queueing Model and Its Application to Battery Swapping and Charging Stations

Scipedia content — Fri, 12 Feb 2021 16:13:18 +0100

This study analyzes the performance of a queue length-dependent overload control policy using a leaky bucket (LB) scheme. This queueing model is applied to the operation of a battery swapping and charging station for electric vehicles (EVs). In addition to the LB scheme, we propose two congestion control policies based on EV queue length thresholds. With these policies, the model determines both EV-arrival and battery-supply intervals, and these depend on the number of EVs waiting in the queue. The queue length distributions, including those at arbitrary epochs, are derived using embedded Markov chain and supplementary variable methods. Performance measures such as blocking probability and mean waiting time are investigated using numerical examples. We study the characteristics of the system using numerical examples and use a cost analysis to investigate situations in which the application of each congestion control policy is advantageous.

Document type: Article

Integrating in situ Measurements and City Scale Modelling to Assess the COVID–19 Lockdown Effects on Emissions and Air Quality in Athens, Greece

Scipedia content — Fri, 12 Feb 2021 16:13:52 +0100

The lockdown measures implemented worldwide to slow the spread of the COVID–19 pandemic have allowed for a unique real–world experiment, regarding the impacts of drastic emission cutbacks on urban air quality. In this study we assess the effects of a 7–week (23 March–10 May, 2020) lockdown in the Greater Area of Athens, coupling in situ observations with estimations from a meteorology–atmospheric chemistry model. Measurements in central Athens during the lockdown were compared with levels during the pre– and post–lockdown 3–week periods and with respective levels in the four previous years. We examined regulatory pollutants as well as CO"sub"2"/sub", black carbon (BC) and source–specific BC components. Models were run for pre–lockdown and lockdown periods, under baseline and reduced–emissions scenarios. The in–situ results indicate mean concentration reductions of 30–35% for traffic–related pollutants in Athens (NO"sub"2"/sub", CO, BC from fossil fuel combustion), compared to the pre–lockdown period. A large reduction (53%) was observed also for the urban CO"sub"2"/sub" enhancement while the reduction for PM"sub"2.5"/sub" was subtler (18%). Significant reductions were also observed when comparing the 2020 lockdown period with past years. However, levels rebounded immediately following the lift of the general lockdown. The decrease in measured NO"sub"2"/sub" concentrations was reproduced by the implementation of the city scale model, under a realistic reduced–emissions scenario for the lockdown period, anchored at a 46% decline of road transport activity. The model permitted the assessment of air quality improvements on a spatial scale, indicating that NO"sub"2"/sub" mean concentration reductions in areas of the Athens basin reached up to 50%. The findings suggest a potential for local traffic management strategies to reduce ambient exposure and to minimize exceedances of air quality standards for primary pollutants.

Document type: Article

Economic impact of autonomous vehicles in Spain

Scipedia content — Fri, 12 Feb 2021 16:16:12 +0100

"jats:sec" "jats:title"Background"/jats:title" "jats:p"Pollution, traffic accidents, and congestion are huge problems in most urban areas. Autonomous and electric vehicles are leading our society to a new mobility model, also known as the New Era of Transportation (NERTRA). Mobility is a strategic issue for any country, and this change of model will mean, in addition to a great technological revolution, an economic revolution."/jats:p" "/jats:sec" "jats:sec" "jats:title"Methodology"/jats:title" "jats:p"The purpose of this work is to carry out a study of the main economic sectors affected in Spain and evaluate the economic impact that autonomous vehicles will have on each one. Data from this sector have been collected, analyzing the economic and technological factors that will affect to a greater or lesser extent and made evolution forecasts."/jats:p" "/jats:sec" "jats:sec" "jats:title"Results"/jats:title" "jats:p"The study presents three different scenarios depending on how the transition progresses. The results are presented by each sector in each of these scenarios. These results have great value for the industry itself and the professionals affected, as well as for the authorities of the country to take the appropriate measures from the beginning of the transition. The sectors directly affected by this change represent more than 38% of the gross domestic product of Spain. Key factors, such as technological innovation in vehicles, and the emergence of new business and mobility models determine drastic changes in some important sectors. It is important to make quick decisions both from administrations and from the industry itself to adapt to new mobility."/jats:p" "/jats:sec

Document type: Article

Moving Object Classification Using 3D Point Cloud in Urban Traffic Environment

Scipedia content — Fri, 12 Feb 2021 16:17:01 +0100

Moving object classification is essential for autonomous vehicle to complete high-level tasks like scene understanding and motion planning. In this paper, we propose a novel approach for classifying moving objects into four classes of interest using 3D point cloud in urban traffic environment. Unlike most existing work on object recognition which involves dense point cloud, our approach combines extensive feature extraction with the multiframe classification optimization to solve the classification task when partial occlusion occurs. First, the point cloud of moving object is segmented by a data preprocessing procedure. Then, the efficient features are selected via Gini index criterion applied to the extended feature set. Next, Bayes Decision Theory (BDT) is employed to incorporate the preliminary results from posterior probability Support Vector Machine (SVM) classifier at consecutive frames. The point cloud data acquired from our own LIDAR as well as public KITTI dataset is used to validate the proposed moving object classification method in the experiments. The results show that the proposed SVM-BDT classifier based on 18 selected features can effectively recognize the moving objects.

Document type: Article

Behavioural Effects of Spatially Structured Scoring Systems in Location-Based Serious Games—A Case Study in the Context of OpenStreetMap

Scipedia content — Fri, 12 Feb 2021 16:18:19 +0100

Location-based games have become popular in recent years, with Poké

mon Go and Ingress being two very prominent examples. Some location-based games, known as Serious Games, go beyond entertainment and serve additional purposes such as data collection. Such games are also found in the OpenStreetMap context and playfully enrich the project&rsquo

s geodatabase. Examples include Kort and StreetComplete. This article examines the role of spatially structured scoring systems as a motivational element. It is analysed how spatial structure in scoring systems is correlated with changes observed in the game behaviour. For this purpose, our study included two groups of subjects who played a modified game based on StreetComplete in a real urban environment. One group played the game with a spatially structured scoring system and the other with a spatially random scoring system. We evaluated different indicators and analysed the players&rsquo

GPS trajectories. In addition, the players filled out questionnaires to investigate whether they had become aware of the scoring system they were playing. The results obtained show that players who are confronted with a spatially structured scoring system are more likely to be in areas with high scores, have a longer playing time, walk longer distances and are more willing to take detours. Furthermore, discrepancies between the perception of a possible system in the scoring system and corresponding actions were revealed. The results are informative for game design, but also for a better understanding of how players interact with their geographical context during location-based games.

Document type: Article

Predicting Wet-Road Crashes Using the Finite-Mixture Zero-Truncated Negative Binomial Model

Scipedia content — Fri, 12 Feb 2021 16:18:49 +0100

Inclement weather affects traffic safety in various ways. Crashes on rainy days not only cause fatalities and injuries but also significantly increase travel time. Accurately predicting crash risk under inclement weather conditions is helpful and informative to both roadway agencies and roadway users. Safety researchers have proposed various analytic methods to predict crashes. However, most of them require complete roadway inventory, traffic, and crash data. Data incompleteness is a challenge in many developing countries. It is common that safety researchers only have access to data on sites where a crash has occurred (i.e., zero-truncated data). The conventional crash models are not applicable to zero-truncated safety data. This paper proposes a finite-mixture zero-truncated negative binomial (FMZTNB) model structure. The model is applied to three-year wet-road crash data on 395 divided roadway segments (total 586 km), and the parameters are estimated using the Markov chain Monte Carlo (MCMC) method. Comparison indicates that the proposed FMZTNB model has better fitting performance and is more accurate in predicting the number of wet-road crashes. The model is capable of capturing the heterogeneity within the sample crash data. In addition, lane width showed mixed effects in different components on wet-road crashes, which are not observed in conventional modeling approaches. Practitioners are encouraged to consider the finite-mixture zero-truncated modeling approach when complete safety dataset is not available.

Document type: Article

Auction Based Algorithm for a Smart Junction with Social Priorities

Scipedia content — Fri, 12 Feb 2021 16:20:31 +0100

Smart devices and their connections to the Internet of Things (IoT) have been the subject of many papers in the past decade. In the context of IoT in transportation, one feature is the smart junction. This research deals with this junction, where several cars approach the intersection from different directions, and a smart traffic light must decide regarding the time intervals of red and green light in each direction. Out novel approach is based not only on the number of vehicles in each lane, but also on the social characteristics of the passengers (e.g. a handicapped person, a driver with no previous traffic violations). These factors will be gleaned from IoT network sources on cars, traffic lights, individuals, municipality data, and more. In this paper, we suggest using a VCG (Vickrey-Clarke-Groves) auction mechanism for the intersection scheduling, combining the social characteristic with a benefit parameter that expresses the passenger’s subjective perception of the importance of crossing the intersection as soon as possible. Our simulation results show the efficiency of the suggested protocol and demonstrate how the intersection scheduling depends on the passengers’ preferences, as well as on their social priorities.

Document type: Article

Electrical bearing failures in electric vehicles

Scipedia content — Fri, 12 Feb 2021 16:20:49 +0100

In modern electric equipment, especially electric vehicles, inverter control systems can lead to complex shaft voltages and bearing currents. Within an electric motor, many parts have electrical failure problems, and among which bearings are the most sensitive and vulnerable components. In recent years, electrical failures in bearing have been frequently reported in electric vehicles, and the electrical failure of bearings has become a key issue that restricts the lifetime of all-electric motor-based power systems in a broader sense. The purpose of this review is to provide a comprehensive overview of the bearing premature failure in the mechanical systems exposed in an electrical environment represented by electric vehicles. The electrical environments in which bearing works including the different components and the origins of the shaft voltages and bearing currents, as well as the typical modes of electrical bearing failure including various topographical damages and lubrication failures, have been discussed. The fundamental influence mechanisms of voltage/current on the friction/lubrication properties have been summarized and analyzed, and corresponding countermeasures have been proposed. Finally, a brief introduction to the key technical flaws in the current researches will be made and the future outlook of frontier directions will be discussed.

Document type: Article

What Motivates Drivers to Comply with Speed Guidance Information at Signalized Intersections?

Scipedia content — Fri, 12 Feb 2021 16:21:05 +0100

This study explored the intrinsic motivation of drivers most likely to accept guidance information at signalized intersections by using a mixed model approach. The proposed approach contains a multiple-indicator multiple-cause model (MIMIC) with a latent class analysis (LCA). The MIMIC model was used to quantify intrinsic motivations according to individual heterogeneity. From a group similarity perspective, the LCA was employed for the latent classification of drivers. The features and possibility of accepting guidance information of each class were also analyzed according to the intrinsic motivation of drivers. Data were collected from the stated preference online surveys, in which the questionnaire was designed according to the diffusion of innovation, in 2015 and 2019 in China. Four subjective perceptions of drivers were identified: the perception of innovating guidance information, the perception of convenience regarding guidance information transmission, the perception of surrounding complexity, and the individual innovation. The estimation results show that age, driving experience, education levels, and familiarity with road network are significant factors of compliance behavior. The proportion of conservatives gradually decreased from 2015 to 2019, while the proportion of early followers and late followers increased through market penetration, familiarity with the Internet of vehicles, and social networks in the same period. This prevalence demonstrates that guidance information at signalized intersections is gradually becoming acceptable in China.

Document type: Article

Long-Term Forecast of Energy and Fuels Demand Towards a Sustainable Road Transport Sector in Ecuador (2016–2035): A LEAP Model Application

Scipedia content — Fri, 12 Feb 2021 16:21:58 +0100

The total energy demand in the transport sector represented 48.80% of the total consumption in Ecuador throughout 2016, where 89.87% corresponded to the road transport sector. Therefore, it is crucial to analyze the future behavior of this sector and assess the economic and environmental measures towards sustainable development. Consequently, this study analyzed: (1) the total energy demand for each vehicle class and fuel type

(2) the GHG (greenhouse gas) emissions and air pollutants NOx and PM10

and (3) the cost attributed to the fuel demand, between 2016 and 2035. For this, four alternative demand scenarios were designed: BAU: Bussiness As Usual

EOM: Energy Optimization and Mitigation

AF: Alternative Fuels

and SM: Sustainable Mobility using Long-range Energy Alternatives Planning system. After analysis, the EOM, AF, and SM scenarios have advantages relative to BAU, where SM particularly stands out. The results show that SM compared to BAU, contributes with a 12.14% (141,226 kBOE) decrease of the total energy demand, and the economic savings for this fuel demand is of 14.22% (26,720 MUSD). Moreover, global NOx and PM10 emissions decreased by 14.91% and 13.78%, respectively. Additionally, accumulated GHG emissions decreased by 13.49% due to the improvement of the fuel quality for the vehicles that mainly consume liquefied petroleum gas, natural gas, and electricity.

Document type: Article

Research on Day-ahead Dispatch of Electricity-heat Integrated Energy System Based on Improved PSO Algorithm

Scipedia content — Fri, 12 Feb 2021 16:22:19 +0100

With the increasingly serious environmental pollution, it is of great significance to construct a comprehensive day-ahead dispatch model of the integrated energy system. For the regional electricity-heat integrated energy system, firstly analyze the operating characteristics and dispatch costs of all units in the system, and then establish the day-ahead economic dispatch model of the system. Furthermore, an improved PSO algorithm is designed based on the idea of adaptive weight and genetic algorithm, and the appropriate algorithm is used to solve the work schedule of each unit in the system through a calculation example. Then the sensitivity analysis of the electric boiler capacity is carried out. Finally, the feasibility of the proposed model is verified through the results analysis, which provides a reference scheme for the electricity-heat integrated energy system including electric vehicles.

Document type: Article

Driver Monitoring for a Driver-Centered Design and Assessment of a Merging Assistance System Based on V2V Communications

Scipedia content — Fri, 12 Feb 2021 16:24:03 +0100

Merging is one of the most critical scenarios that can be found in road transport. In this maneuver, the driver is subjected to a high mental load due to the large amount of information he handles, while making decisions becomes a crucial issue for their safety and those in adjacent vehicles. In previous works, it was studied how the merging maneuver affected the cognitive load required for driving by means of an eye tracking system, justifying the proposal of a driver assistance system for the merging maneuver on highways. This paper presents a merging assistance system based on communications between vehicles, which allows vehicles to share internal variables of position and speed and is implemented on a mobile device located inside the vehicle. The system algorithm decides where and when the vehicle can start the merging maneuver in safe conditions and provides the appropriate information to the driver. Parameters and driving simulator tests are used for the interface definition to develop the less intrusive and demanding one. Afterward, the system prototype was installed in a real passenger car and tests in real scenarios were conducted with several drivers to assess usability and mental load. Comparisons among alternative solutions are shown and effectiveness is assessed.

Document type: Article

Integrated Optimization of Sustainable Transportation and Inventory with Multiplayer Dynamic Game under Carbon Tax Policy

Scipedia content — Mon, 15 Feb 2021 09:43:23 +0100

Growth in environmental sustainability has prompted the logistics industry to seek sustainable development, and carbon tax policies are considered an effective approach to reducing carbon emissions. This study investigates the optimization of sustainable transportation and inventory under a carbon tax policy and explores effective methods for coordinating the interests of governments and enterprises. The results can provide insights into sustainable logistics for decision-making by enterprises and policy-making by governments. We first examine a Stackelberg game model and design an iterative solution to optimize sustainable transportation and inventory under the carbon tax policy. We then establish a three-stage dynamic game model to optimize the wholesale price, carbon tax rate, and proportion of sustainable investment shared by the government. Furthermore, we perform a simulation to identify the optimal solution of the three-stage game, and we compare the simulation results with a numerical example. The results indicate that a carbon tax policy can improve social welfare and the sustainability of transportation and inventory but could hinder corporate profits. An appropriate sustainable investment-sharing strategy could compensate for the shortcomings of the carbon tax policy and result in positive outcomes for governments and enterprises.

Document type: Article

Simulating Crowd Evacuation in a Social Force Model with Iterative Extended State Observer

Scipedia content — Mon, 15 Feb 2021 09:46:13 +0100

Due to the interaction and external interference, the crowds will constantly and dynamically adjust their evacuation path in the evacuation process to achieve the purpose of rapid evacuation. The information from previous process can be used to modify the current evacuation control information to achieve a better evacuation effect, and iterative learning control can achieve an effective prediction of the expected path within a limited running time. In order to depict this process, the social force model is improved based on an iterative extended state observer so that the crowds can move along the optimal evacuation path. First, the objective function of the optimal evacuation path is established in the improved model, and an iterative extended state observer is designed to get the estimated value. Second, the above model is verified through simulation experiments. The results show that, as the number of iterations increases, the evacuation time shows a trend of first decreasing and then increasing.

Document type: Article

Parking Pricing vs. Congestion Pricing: A Macroscopic Analysis of their Impact on Traffic

Scipedia content — Mon, 15 Feb 2021 09:47:19 +0100

As traffic congestion gets worse year by year in metropolitan areas, cities search for solutions to improve their traffic performance and reduce their environmental impacts. This paper focuses on parking pricing and congestion pricing and their short-term effects not only on traffic congestion but also on the potential revenue for a city. We develop an easy to implement multimodal macroscopic traffic and parking search model for a central area based on aggregated data at the network level. Our methodology allows us to analyze how introducing parking pricing inside a network, or a congestion toll combined with a park and ride (P+R) scheme can affect the drivers’ decision between entering the network by car (private vehicle) or using P+R instead. This decision directly influences the number of drivers using P+R, and this impacts, in turn, the traffic performance. Based on such analysis, a city can get valuable insights to evaluate whether congestion pricing is a necessity or if the traffic improvements resulting from implementing parking pricing strategies are sufficient when combined with P+R facilities. A search algorithm is used to find the best trade-off between the parking fees and the congestion toll. Any additional revenue collected through these schemes can then be used to improve public transport or the P+R facilities themselves. With minor data collection efforts and little computational costs compared to most existing parking and congestion pricing models, we illustrate our proposed framework in a case study of an area with a high parking demand for public parking spaces within the city of Zurich, Switzerland. Results show that parking pricing combined with P+R is indeed a viable option compared to congestion pricing for improving traffic performance, even if parking pricing schemes do not target all the drivers.

Document type: Article

Optimization and Comparative Analysis of Traffic Restriction Policy by Jointly Considering Carpool Exemptions

Scipedia content — Mon, 15 Feb 2021 09:51:47 +0100

As a countermeasure to urban exhaust pollution and traffic congestion, traffic restriction policy (TRP) and carpooling strategy have been widely introduced throughout the world. However, their effects are largely determined by the rationality of implementing policies, and unreasonable policies make them controversial on the long-term implementation benefits. To more effectively manage traffic demand and maintain the sustainability of transportation system, it is necessary to make optimization for management policy before implementation. In this paper, the elastic demand model and equilibrium assignment model are developed under TRP. Considering the negative impact of the mandatory TRP on the public acceptance, we propose a novel TRP strategy, namely TRP with carpool exemptions (TRP-CE), that is, a proportion of high occupancy vehicles (HOV) are allowed to travel in the restricted district even if their license plate numbers are restricted. Then, a bi-level programming model is proposed to solve the optimal schemes by combining multi purposes of ensuring travel convenience, alleviating traffic congestion, and reducing the exhaust pollution. Finally, a numerical experiment is conducted to evaluate the effectiveness of proposed models and make comparative analysis between separate TRP and TRP-CE. The results indicate that TRP-CE has benefits in the following aspects: (1) Carpool exemptions provide an incentive to carpool for travelers by private cars; (2) the public acceptance of TRP is improved by introducing carpool exemptions as a compensatory mitigation strategy for mandatory TRP; (3) the implementation effect of demand management can be well achieved by joint optimization; and (4) there is no need to design and reconstruct HOV lanes for the implementation of TRP-CE, which is convenient for practical application.

Document type: Article

A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

Scipedia content — Mon, 15 Feb 2021 09:54:00 +0100

International audience; To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.

Document type: Article

Control of Dual-Output DC/DC Converters Using Duty Cycle and Frequency

Scipedia content — Mon, 15 Feb 2021 09:54:36 +0100

As part of the integration process of the auxiliary power systems of electric vehicles, plug-in hybrid vehicles and fuel cell vehicles, this study proposes a method to control two different voltage types using two control factors of the rectangular alternating waveforms contained in DC/DC converters, namely the duty cycle and frequency. A prototype circuit consisting of an H-bridge inverter, a transformer, two series resonant filters and two diode bridge circuits was constructed. The H-bridge inverter was connected to the primary side of the transformer and the diode bridge rectifier circuit was connected to the secondary side in parallel. Series resonant filters were inserted between one of the diode bridge circuits and the transformer. Thereafter, the proposed control method was applied to the transformer voltage of the prototype circuit. Although the circuit operation became complex owing to the circulating current flowing between the ground (GND) of the two output circuits, it exhibited ideal static and dynamic characteristics, thereby confirming the possibility of controlling two voltages with the duty cycle and frequency control factors. The results of the efficiency evaluation and loss analysis demonstrated a minimum efficiency of 68.3% and a maximum efficiency of 88.9%. As the output power of the circuit containing the resonant filters increased, the current peak value increased and the circuit became less efficient.

Document type: Article

The Reversible Lane Network Design Problem (RL-NDP) for Smart Cities with Automated Traffic

Scipedia content — Mon, 15 Feb 2021 09:55:04 +0100

With automated vehicles (AVs), reversible lanes could be a sustainable transportation solution once there is vehicle-to-infrastructure connectivity informing AVs about the lane configuration changes. This paper introduced the reversible lane network design problem (RL-NDP), formulated in mixed-integer non-linear mathematical programming&mdash

both the traffic assignment and the reversible lane decisions were embedded. The model was applied on an hourly basis in the case study of the city of Delft, the Netherlands. Reversible lanes are examined under no traffic equilibrium (former paths are maintained)

user-equilibrium (UE) assignment (AVs decide their own paths)

and system-optimum (SO) traffic assignment (AVs are forced to follow SO paths). We found out that reversible lanes reduce congested roads, total travel times, and delays up to 36%, 9%, and 22%, respectively. The SO scenario was revealed to be beneficial in reducing the total travel time and congested roads in peak hours, whereas UE is equally optimal in the remaining hours. A dual-scenario mixing SO and UE throughout the day reduced congested roads, total travel times, and delay up to 40%, 8%, and 19%, respectively, yet increased 1% in travel distance. The spatial analysis suggested a substantial lane variability in the suburbs, yet a strong presence of reversible lanes in the city center.

Document type: Article

Improved Photovoltaic Self-Consumption in Residential Buildings with Distributed and Centralized Smart Charging of Electric Vehicles

Scipedia content — Mon, 15 Feb 2021 09:58:00 +0100

The integration of photovoltaic (PV) and electric vehicle (EV) charging in residential buildings has increased in recent years. At high latitudes, both pose new challenges to the residential power systems due to the negative correlation between household load and PV power production and the increase in household peak load by EV charging. EV smart charging schemes can be an option to overcome these challenges. This paper presents a distributed and a centralized EV smart charging scheme for residential buildings based on installed photovoltaic (PV) power output and household electricity consumption. The proposed smart charging schemes are designed to determine the optimal EV charging schedules with the objective to minimize the net load variability or to flatten the net load profile. Minimizing the net load variability implies both increasing the PV self-consumption and reducing the peak loads. The charging scheduling problems are formulated and solved with quadratic programming approaches. The departure and arrival time and the distance covered by vehicles in each trip are specifically modeled based on available statistical data from the Swedish travel survey. The schemes are applied on simulated typical Swedish detached houses without electric heating. Results show that both improved PV self-consumption and peak load reduction are achieved. The aggregation of distributed smart charging in multiple households is conducted, and the results are compared to the smart charging for a single household. On the community level, both results from distributed and centralized charging approaches are compared.

Document type: Article

Impacts of increasing maximum truck weight – case Finland

Scipedia content — Mon, 15 Feb 2021 09:59:30 +0100

Finnish government allowed in October 2013 operating high capacity vehicles (HCV) with a maximum weight limit of 76 t on Finnish roads. An analysis on how HCVs have affected the Finnish road freight transport sector is presented here based on a continuous time series data from 2013 to 2017. The analysis shows a significant increase in the average payload weight and a transition from 7-axle to 8- and 9-axle articulated vehicle combinations, which allow the higher weights. Truck mileage of 225 million km has been avoided from October 2013 until the end of 2017 and avoided mileage corresponded in 2017 to approximately 4% of total truck mileage in Finland. This equals around 126 million € cost savings in 2017 and 0.1 Mt of CO2 emissions reduction in road freight, even after taking into account that there has been some modal shift from rail to road.

Document type: Article

Impact of Smart Charging for Consumers in a Real World Pilot

Scipedia content — Mon, 15 Feb 2021 09:59:46 +0100

smart charging profile was implemented on 39 public charging stations in Amsterdam on which the current level available for electric vehicle (EV) charging was limited during peak hours on the electricity grid (07:00&ndash

08:30 and 17:00&ndash

20:00) and was increased during the rest of the day. The impact of this profile was measured on three indicators: average charging power, amount of transferred energy and share of positively and negatively affected sessions. The results are distinguished for different categories of electric vehicles with different charging characteristics (number of phases and maximum current). The results depend heavily on this categorisation and are a realistic measurement of the impact of smart charging under real world conditions. The average charging power increased as a result of the new profile and a reduction in the amount of transferred energy was detected during the evening hours, causing outstanding demand which was solved at an accelerated rate after limitations were lifted. For the whole population, 4% of the sessions were positively affected (charged a larger volume of energy) and 5% were negatively affected. These numbers are dominated by the large share of plug-in hybrid electric vehicles (PHEVs) in Amsterdam which are technically not able to profit from the higher current levels. For new generation electric vehicles, 14% of the sessions were positively affected and the percentage of negatively affected sessions was 5%.

Document type: Article

A new program for the hydraulic calculation of steam-water mixture pipelines in geothermal fields

Scipedia content — Mon, 15 Feb 2021 09:59:59 +0100

A new mathematical model of steam-water flow in a pipeline, which takes into account the gravitational effect and satisfies new challenges in the development of geothermal fields with two-phase transportation of the heat carrier is presented. Taking into account the gravitational effect in the upstream flows, a method based on the “drift model”, which determines the steam velocity averaged over the crosssection was used. A similar method is proposed for downstream flows, but it determines the water velocity averaged over the cross-section. In this case, analogs of empirical coefficients were used. These coefficients determined from the condition of equality of parameters calculated using different approaches in a horizontal flow. The model was verified, which showed positive results. The proposed model significantly expands the possibilities of hydraulic calculation of steam-water mixture pipelines in geothermal fields.

Document type: Article

Location Design of Electrification Road in Transportation Networks for On-Way Charging

Scipedia content — Mon, 15 Feb 2021 10:00:37 +0100

Electric vehicles tend to be a great mobility option for the potential benefits in energy consumption and emission reduction. On-way charging (OWC) has been recognized to be a promising solution to extend driving range for electric vehicles. Location of the electrification road (ER) is a critical issue for future urban traffic management to accommodate the new mobility option. This paper proposes a mathematical program with equilibrium constraint (MPEC) approach to solve this problem, which minimizes the total travel time with a limited construction budget. To describe the drivers’ routing choice, a path-constrained network equilibrium model is proposed to minimize their travel time and prevent running out of charge. We develop a modified active set algorithm to solve the MPEC model. Numerical experiments are presented to demonstrate the performance of the model and the solution algorithm and analyze the impact of charging efficiency, battery size, and comfortable range.

Document type: Article

A Two-Class Stochastic Network Equilibrium Model under Adverse Weather Conditions

Scipedia content — Mon, 15 Feb 2021 10:00:52 +0100

Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes a novel stochastic traffic network equilibrium model considering impacts of adverse weather conditions on roadway capacity and route choice criteria of two-class mixed roadway travellers on demand modes, in which the two-class route choice criteria root in travelers’ different network information levels (NILs). The actual route travel time (ARTT) and perceived route travel time (PRTT) are considered as the route choice criteria of travelers with perfect information (TPI) and travelers with bounded information (TBI) under adverse weather conditions, respectively. We then formulate the user equilibrium (UE) traffic assignment model in a variational inequality problem and propose a solution algorithm. Numerical examples including a small triangle network and the Sioux Falls network are presented to testify the validity of the model and to clarify the inner mechanism of the two-class UE model under adverse weather conditions. Managerial implications and applications are also proposed based on our findings to improve the operation efficiency of urban roadway network under adverse weather conditions.

Document type: Article

The traffic signal control problem for intersections: a review

Scipedia content — Mon, 15 Feb 2021 10:01:20 +0100

"jats:sec" "jats:title"Background"/jats:title" "jats:p"The intersection traffic signal control problem (ITSCP) has become even more important as traffic congestion has been more intractable. The ITSCP seeks an efficient schedule for traffic signal settings at intersections with the goal of maximizing traffic flow while considering various factors such as real-time strategies, signal timing constraints, rapid developments in traffic systems, and practical implementation. Since the factors constituting the ITSCP exhibit stochastically complicated interactions, it is essential to identify these factors to propose solution methods that can address this complexity and still be practically implemented."/jats:p" "/jats:sec" "jats:sec" "jats:title"Objective"/jats:title" "jats:p"The objective of this review is to provide a survey of problems, methods, and practices in the evaluation of the ITSCP. In this paper, a unified terminology for the ITSCP and a citation network of the current body of relevant research are accordingly presented, and various assumptions, constraints, and solution approaches are summarized. A review across the entire body of knowledge throughout the history of the ITSCP is therefore provided. This review also highlights open issues and challenges that remain to be addressed by future research."/jats:p" "/jats:sec

Document type: Article

Containerships Sailing Speed and Fleet Deployment Optimization under a Time-Based Differentiated Freight Rate Strategy

Scipedia content — Mon, 15 Feb 2021 10:04:30 +0100

This paper investigates the problem of containership sailing speed and fleet deployment optimization in an intercontinental liner shipping network. Under the consideration of the time value of container cargo, three kinds of impact of sailing speed changes on long legs of each liner route are analysed, and a time-based freight rate strategy is proposed. Then, the optimization problem is formulated as a mixed-integer nonlinear programming. Its goal is to maximize the total profits of a container liner shipping. To find the optimal solution to the model and improve the efficiency of model solution, a discretization algorithm is proposed. Numerical results verify the applicability of the proposed model and the efficiency of the algorithm. In addition, the time-based freight rate strategy is able to achieve more profit compared to a fixed freight rate strategy.

Document type: Article

Benefits of Electrified Powertrains in Medium- and Heavy-Duty Vehicles

Scipedia content — Mon, 15 Feb 2021 10:06:05 +0100

The benefits of electrified powertrains for light-duty vehicles are well understood, however sufficient published information is not available on the benefits of advanced powertrains on the various types of medium and heavy duty vehicles. Quantifying the benefits of powertrain electrification will help fleet operators understand the advantages or limitations in adopting electrified powertrains in their truck fleets. Trucks vary in size and shape, as they are designed for specific applications. It is necessary to model each kind of truck separately to understand what kind of powertrain architecture will be feasible for their daily operations. This paper examines 11 types of vehicles and 5 powertrain technology choices to quantify the fuel saving potential of each design choice. This study uses the regulatory cycles proposed by the US Environmental Protection Agency (EPA) for measuring fuel consumption.

Document type: Article

Supply Chain Financial Risk Evaluation of Small- and Medium-Sized Enterprises under Smart City

Scipedia content — Mon, 15 Feb 2021 10:06:55 +0100

Prevention and control of risks are an eternal theme of financial institutions. Although, to some extent, the emergence of supply chain finance can enhance the financing capacity of small- and medium-sized enterprises (SMEs) and reduce financial risks of financial institutions, with the development of smart city and smart finance, the financial risks of SMEs are more complex, infectious, dormant, and difficult to accurately identify and measure. Facing this status, financial institutions have been required to understand and evaluate the financial risks of SMEs from a new perspective. Therefore, this paper, based on the study of financial risks assessment of SMEs under the smart city and smart finance, innovatively constructs a new index evaluation system for supply chain finance, based on improved hesitant fuzzy linguistic PROMETHEE method, and the effectiveness and advantages of the model have been verified through an example. To a certain degree, the SMEs financing the evaluation model and improved PROMETHEE method can not only help financial institutions reduce the risks in the specific financial transactions but also reduce the survival threat of financial institutions. Moreover, it is of positive significance to the stable operation of the financial system.

Document type: Article

Passenger Demand-Oriented High-Speed Train Stop Planning with Service-Node Features Analysis

Scipedia content — Mon, 15 Feb 2021 10:07:29 +0100

As a critical foundation for train traffic management, a train stop plan is associated with several other plans in high-speed railway train operation strategies. The current approach to train stop planning in China is based primarily on passenger demand volume information and the preset high-speed railway station level. With the goal of efficiently optimising the stop plan, this study proposes a novel method that uses machine learning techniques without a predetermined hypothesis and a complex solution algorithm. Clustering techniques are applied to assess the features of the service nodes (e.g., the station level). A modified Markov decision process (MDP) is conducted to express the entire stop plan optimisation process considering several constraints (service frequency at stations and number of train stops). A restrained MDP-based stop plan model is formulated, and a numerical experiment is conducted to demonstrate the performance of the proposed approach with real-world train operation data collected from the Beijing-Shanghai high-speed railway.

Document type: Article

Assessing Resources Management for Sharing Economy in Urban Logistics

Scipedia content — Mon, 15 Feb 2021 10:07:49 +0100

Sharing economy requires cities to redefine their management strategies. As a consequence of the development of new ideas, the main aim of modern cities should focus on achieving the sustainable use of resources. In the existing literature, only a partial analysis of resources management in cities can be found. For this reason, the authors decided to prepare the framework for empirical research about resources management in sharing economy in cities, especially in the urban logistics system. The main aim of the study is systematizing criteria related to the assessment of the management of urban resources in the era of sharing economy. To achieve the goal of the research, a systematic literature review was made according to chosen approaches and procedures. This resulted in creating a set of criteria for the analysis and evaluation of resources management in urban areas. It contains five areas with 26 criteria and a map of assumed correlations between them. Those outcomes can be used by local authorities or even other urban logistics stakeholders to define or improve their actions aimed at developing a sharing economy services portfolio on the local market. Additionally, they constitute a set of initial information for further scientific research.

Document type: Article

Deployment Optimization of Connected and Automated Vehicle Lanes with the Safety Benefits on Roadway Networks

Scipedia content — Mon, 15 Feb 2021 10:08:07 +0100

Reasonable deployment of connected and automated vehicle (CAV) lanes which separating the heterogeneous traffic flow consisting of both CAVs and human-driven vehicles (HVs) can not only improve traffic safety but also greatly improve the overall roadway efficiency. This paper simplified CAV lane deployment plan into the problem of traffic network design and proposed a comprehensive decision-making method for CAV lane deployment plan. Based on the traffic equilibrium theory, this method aims to reduce the travel cost of the traffic network and the management cost of CAV lanes using a bilevel primary-secondary programming model. In addition, the upper level is the decision-making scheme of the lane deployment, while the lower level is the traffic assignment model including CAV and HV modes based on the decision-making scheme of the upper level. After that, a genetic algorithm was designed to solve the model. Finally, a medium-scaled traffic network was selected to verify the effectiveness of the proposed model and algorithm. The case study shows that the proposed method obtained a feasible scheme for lane deployment considering from both the system travel cost and management cost of CAV lanes. In addition, a sensitivity analysis of the market penetration rate of CAVs, traffic demand, and the capacity of CAVLs further proves the applicability of this model, which can achieve better allocation of system resources and also improve the traffic efficiency.

Document type: Article

Assessing the Effects of Time Budget and Traffic Density with the Help of a Trajectory-Planning Method

Scipedia content — Mon, 15 Feb 2021 10:11:06 +0100

In"?tex id="Q1" staff-cmt="As per style “The Nertherlands” in country name should not contain, hence we ignored the authors corrections. Please check and confirm."?" highly automated driving, the driver can engage in a nondriving task but sometimes has to take over control. We argue that current takeover quality measures, such as the maximum longitudinal acceleration, are insufficient because they ignore the criticality of the scenario. This paper proposes a novel method of quantifying how well the driver executed an automation-to-manual takeover by comparing human behaviour to optimised behaviour as computed using a trajectory planner. A human-in-the-loop study was carried out in a high-fidelity 6-DOF driving simulator with 25 participants. The takeover required a lane change to avoid roadworks on the ego-lane while taking other traffic into consideration. Each participant encountered six different takeover scenarios, with a different time budget (5 s, 7 s, or 20 s) and traffic density level (low or medium). Results showed that drivers exhibited a considerably higher longitudinal and lateral acceleration than the optimised behaviour, especially in the short time budget scenarios. In scenarios of medium traffic density, the trajectory planner showed a moderate deceleration to let a vehicle in the left lane pass; many participants, on the other hand, did not decelerate before making a lane change, resulting in a dangerous emergency brake of the left-lane vehicle. In conclusion, our results illustrate the value of assessing human takeover behaviour relative to optimised behaviour. Using the trajectory planner, we showed that human drivers are unable to behave optimally in urgent scenarios and that, in some conditions, a medium deceleration, as opposed to a maximal or minimal deceleration, is optimal.

Document type: Article

Variations in Naturalistic Driving Behavior and Visual Perception at the Entrances of Short, Medium, and Long Tunnels

Scipedia content — Mon, 15 Feb 2021 10:11:24 +0100

Driver behavior and visual perception are very important factors in the management of traffic accident risk at tunnel entrances. This study was undertaken to analyze the differences in driving behavior and visual perception at the entrances of three types of tunnels, namely, short, medium-length, and long tunnels, under naturalistic driving conditions. Using three driving behavior indicators (speed, deceleration, and position) and two visual perception indicators (fixation and saccade), the driving performance of twenty drivers at six tunnels (two tunnels per condition) was comparatively analyzed. The results revealed that the speed maintained by the drivers prior to deceleration with braking under the short-tunnel condition was significantly larger than that under the medium- and long-tunnel conditions and that the drivers had a greater average and maximum deceleration rates under the short-tunnel condition. A similar general variation of driver visual perception appeared under the respective tunnel conditions, with the number of fixations gradually increasing and the maximum saccade amplitude gradually decreasing as the drivers approached the tunnel portal. However, the variation occurred approximately 60 m earlier under the short-tunnel condition than under the medium- and long-tunnel conditions. Interactive correlations between driving behavior and visual perception under the three conditions were established. The commencement of active deceleration was significantly associated (with correlation factors of 0.80, 0.77, and 0.79 under short-, medium-, and long-tunnel conditions, respectively) with the point at which the driver saccade amplitude fell below 10 degrees for more than 3 s. The results of this study add to the sum of knowledge of differential driver performance at the entrances of tunnels of different lengths.

Document type: Article

Assessment of the Condition of Pipelines Using Convolutional Neural Networks

Scipedia content — Mon, 15 Feb 2021 10:14:47 +0100

Pipelines are structural elements of many systems. For example, they are used in water supply and heat supply systems, in chemical production facilities, aircraft manufacturing, and in the oil and gas industry. Accidents in piping systems result in significant economic damage. An important factor for ensuring the reliability of energy transportation systems is the assessment of real technical conditions of pipelines. Methods for assessing the state of pipeline systems by their vibro-acoustic parameters are widely used today. Traditionally, the Fourier transform is used to process vibration signals. However, as a rule, the oscillations of the pipe-liquid system are non-linear and non-stationary. This reduces the reliability of devices based on the implementation of classical methods of analysis. The authors used neural network methods for the analysis of vibro-signals, which made it possible to increase the reliability of diagnosing pipeline systems. The present work considers a method of neural network analysis of amplitude-frequency measurements in pipelines to identify the presence of a defect and further clarify its variety.

Document type: Article

Shunting Strategy for Placing-In and Taking-Out Wagons on Branch-Shaped Freight Operation Network with Simulation Method

Scipedia content — Mon, 15 Feb 2021 10:16:54 +0100

Because of China’s vast territory, large population, and huge demand for bulk materials, the railway transportation mode has always received considerable attention. For long-haul transportation, railway transportation can provide a scheduled-based transport plan, all-weather transport service, and cheaper carry instead of other transport modes. The study described in this paper attempts to develop a simulation platform for optimizing the placing-in and taking-out wagons system on the branch-shaped freight operation network (PTWS-BSFON). The operation process of PTWS is thoroughly analyzed from three aspects of decoupling-coupling wagons subsystem, placing-in local wagons subsystem, and taking-out local wagons subsystem. And then the simulation platform encompassing two typically shunting modes of PTWS are developed by Arena software. Under scenarios of PTWS-SO and PTWS-SSMS, the hierarchical structure of the shunting strategies is, respectively, outlined in the simulation platform. Finally, the shunting strategies based on the simulation platform are carried out by concrete examples, which prove the rationality of the methodology in applying different strategies and enhancing the performances of the PTWS-BSFON.

Document type: Article

Lane-Change Model and Tracking Control for Autonomous Vehicles on Curved Highway Sections in Rainy Weather

Scipedia content — Mon, 15 Feb 2021 10:18:12 +0100

In this study, we propose an adaptive path planning model and tracking control method for collision avoidance and lane-changing manoeuvres on highways in rainy weather. Considering the human-vehicle-road interaction, we developed an adaptive lane change system that consists of an intelligent trajectory planning and tracking controller. Gaussian distribution was introduced to evaluate the impact of rain on the pavement characteristics and deduce adaptive lane-change trajectories. Subsequently, a score-based decision mechanism and multilevel autonomous driving mode that considers safety, comfort, and efficiency were proposed. A tracking controller was designed using a linearised model predictive control method. Finally, using simulated scenarios, the feasibility and effectiveness of the proposed method were demonstrated. The results obtained herein are a valuable resource that can be used to develop an intelligent lane change system for autonomous vehicles and can help improve highway traffic safety and efficiency in adverse weather conditions.

Document type: Article

Between fairness, welfare and feasibility: an approach for applying different distributive principles in transport evaluation

Scipedia content — Mon, 15 Feb 2021 10:23:14 +0100

Background For assessing the desirability and feasibility of major transport projects decision makers often recur to ex-ante evaluation methods such as cost-benefit analysis or multi-criteria analysis. In these methods projects are evaluated for their impacts on the welfare of society as one indivisible entity. The use of these methods is limited for assessing socio-spatial equity, as costs and benefits of transport are unequally spread over space and society. Moreover, in projects that cross political borders these methods poorly represent the spatially differentiated interests of the decision makers. Methods This article proposes a novel evaluation approach, applied in a study on the possible demolition of a motorway linking the three Belgian regions of Brussels, Flanders and Wallonia. Results The application demonstrates how the social and spatial differentiation of effects can be evaluated, allowing to differentiate impacts for crucial stakeholders or criteria, but also to aggregate evaluation results in cases where pursuing supra-local or common interests is appropriate. Conclusions Whether and where decision making in transport should follow utilitarian or egalitarian distributive principles depends on context and political considerations. The presented approach allows decision makers to apply both principles where they are deemed appropriate, transparently, in a single project.

Document type: Article

Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models

Scipedia content — Mon, 15 Feb 2021 10:23:56 +0100

The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.

Document type: Article

Social efficiency deficit deciphers social dilemmas

Scipedia content — Mon, 15 Feb 2021 10:24:55 +0100

"jats:p"What do corruption, resource overexploitation, climate inaction, vaccine hesitancy, traffic congestion, and even cancer metastasis have in common? All these socioeconomic and sociobiological phenomena are known as social dilemmas because they embody in one form or another a fundamental conflict between immediate self-interest and long-term collective interest. A shortcut to the resolution of social dilemmas has thus far been reserved solely for highly stylised cases reducible to dyadic games (e.g., the Prisoner’s Dilemma), whose nature and outcome coalesce in the concept of dilemma strength. We show that a social efficiency deficit, measuring an actor’s potential gain in utility or fitness by switching from an evolutionary equilibrium to a social optimum, generalises dilemma strength irrespective of the underlying social dilemma’s complexity. We progressively build from the simplicity of dyadic games for which the social efficiency deficit and dilemma strength are mathematical duals, to the complexity of carcinogenesis and a vaccination dilemma for which only the social efficiency deficit is numerically calculable. The results send a clear message to policymakers to enact measures that increase the social efficiency deficit until the strain between what is and what could be incentivises society to switch to a more desirable state.

Document type: Article

Health and Structural Integrity of Monitoring Systems: The Case Study of Pressurized Pipelines

Scipedia content — Mon, 15 Feb 2021 10:26:46 +0100

In the operation of some structures, particularly in energy or chemical industry where pressurized pipeline systems are employed, certain unexpected critical situations may occur, which must be definitely avoided. Otherwise, such situations would result in undesirable damage to the environment or even the endangerment of human life. For example, the occurrence of such nonstandard states can significantly affect the safety of high-pressure pipeline systems. The following paper discusses basic physical prerequisites for assembling the systems that can sense loading states and monitor the operational safety conditions of pressure piping systems in the long-run. The appropriate monitoring system hardware with cost-effective data management was designed in order to enable the real-time monitoring of operational safety parameters. Furthermore, the paper presents the results obtained from the measurements of existing real-time safety monitoring systems for selected pipeline systems.

Document type: Article

Valve Location Method for Evaluating Drain Efficiency in Water Transmission Pipelines

Scipedia content — Mon, 15 Feb 2021 10:28:49 +0100

Water transmission pipelines, which transport bulk water into storage facilities, usually have a tree-type configuration with large dimensions; thus, the breakage of a pipeline may cause a catastrophic service interruption to customers. Although drain efficiency is closely related to the number of washout and control valves and their locations, there is no useful guideline. This paper proposes a valve locating method by introducing numerical analyses to enumerate drainage time and zone. A time integration method, combined with the Newton–Raphson algorithm, is suggested to resolve drainage time, while considering the friction loss in gravitational flow. A drain direction matrix, which shows drain direction and coverage, is derived using a network searching algorithm. Furthermore, a feasible practical approach is presented by introducing a critical horizontal slope, a major washout valve, drainage indices, and control valve embedment. The developed method is first applied to simple pipes to validate the drainage time module. Subsequently, the model is expanded to the CY transmission line, which is one of the BR water supply systems in South Korea currently in operation. The results reveal that three drain valve locations have been neglected, and the addition of control valves guarantees consistent drain time below the operational criteria.

Document type: Article

Audio-Based Event Detection at Different SNR Settings Using Two-Dimensional Spectrogram Magnitude Representations

Scipedia content — Mon, 15 Feb 2021 10:32:27 +0100

Audio-based event detection poses a number of different challenges that are not encountered in other fields, such as image detection. Challenges such as ambient noise, low Signal-to-Noise Ratio (SNR) and microphone distance are not yet fully understood. If the multimodal approaches are to become better in a range of fields of interest, audio analysis will have to play an integral part. Event recognition in autonomous vehicles (AVs) is such a field at a nascent stage that can especially leverage solely on audio or can be part of the multimodal approach. In this manuscript, an extensive analysis focused on the comparison of different magnitude representations of the raw audio is presented. The data on which the analysis is carried out is part of the publicly available MIVIA Audio Events dataset. Single channel Short-Time Fourier Transform (STFT), mel-scale and Mel-Frequency Cepstral Coefficients (MFCCs) spectrogram representations are used. Furthermore, aggregation methods of the aforementioned spectrogram representations are examined; the feature concatenation compared to the stacking of features as separate channels. The effect of the SNR on recognition accuracy and the generalization of the proposed methods on datasets that were both seen and not seen during training are studied and reported.

Document type: Article

Road Traffic Safety Risk Estimation Method Based on Vehicle Onboard Diagnostic Data

Scipedia content — Mon, 15 Feb 2021 10:32:50 +0100

Currently, research on road traffic safety is mostly focused on traffic safety evaluations based on statistical indices for accidents. There is still a need for in-depth investigation on preaccident identification of safety risks. In this study, the correlations between high-incidence locations for aberrant driving behaviors and locations of road traffic accidents are analyzed based on vehicle OBD data. A road traffic safety risk estimation index system with road traffic safety entropy (RTSE) as the primary index and rapid acceleration frequency, rapid deceleration frequency, rapid turning frequency, speeding frequency, and high-speed neutral coasting frequency as secondary indices is established. A calculation method of RTSE is proposed based on an improved entropy weight method. This method involves three aspects, namely, optimization of the base of the logarithm, processing of zero-value secondary indices, and piecewise calculation of the weight of each index. Additionally, a safety risk level determination method based on two-step clustering (density and "jats:italic"k"/jats:italic"-means clustering) is also proposed, which prevents isolated data points from affecting safety risk classification. A risk classification threshold calculation method is formulated based on "jats:italic"k"/jats:italic"-mean clustering. The results show that high-incidence locations for aberrant driving behaviors are consistent with the locations of traffic accidents. The proposed methods are validated through a case study on four roads in Chongqing with a total length of approximately 38 km. The results show that the road traffic safety trends characterized by road safety entropy and traffic accidents are consistent.

Document type: Article

Assessing the Contribution of Data Mining Methods to Avoid Aircraft Run-Off from the Runway to Increase the Safety and Reduce the Negative Environmental Impacts

Scipedia content — Mon, 15 Feb 2021 10:34:54 +0100

The Single Europe Sky Air Traffic Management Research (SESAR) program develops and implements innovative technological and operational solutions to modernize European air traffic management and to eliminate the negative environmental impacts of aviation activity. This article presents our developments within the SESAR Solution &ldquo

Safety Support Tools for Avoiding Runway Excursions&rdquo

. This SESAR Solution aims to mitigate the risk of runway excursion, to optimize airport operation management by decreasing the number of runway inspections, to make chemical treatment effective with respect to the environment, and to increase resilience, efficiency and safety in adverse weather situations. The proposed approach is based on the enhancement of runway surface condition awareness by integrating data from various sources. Dangerous windy conditions based on Lidar measurements are also discussed as another relevant factor in relation to runway excursions. The paper aims to explore four different data mining methods to obtain runway conditions from the available input data sources, examines their performance and discusses their pros and cons in comparison with a rule-based algorithm approach. The output of the SESAR Solution is developed in compliance with the new Global Reporting Format of the International Civil Aviation Organization for runway condition description to be valid from 2020. This standard is expected to provide concerned stakeholders with more precise information to enhance flight safety and environmental protection.

Document type: Article

Understanding Electric Bikers’ Red-Light Running Behavior: Predictive Utility of Theory of Planned Behavior vs Prototype Willingness Model

Scipedia content — Mon, 15 Feb 2021 10:36:49 +0100

To date, electric bikers’ (e-bikers’) red-light running (RLR) behavior is often viewed as one of the main contributors to e-bike-related accidents, especially for traffic scenarios with high e-bike ridership. In this paper, we aim to understand e-bikers’ RLR behavior based on structural equation modeling. Specifically, the predictive utility of the theory of planned behavior (TPB), prototype willingness model (PWM), and their combined form, TPB-PWM model, is used to analyze e-bikers’ RLR behavior, and a comparison analysis is made. The analyses of the three modeling approaches are based on the survey data collected from two online questionnaires, where more than 1,035 participant-completed questionnaires are received. The main findings in this paper are as follows: (i) Both PWM and TPB-PWM models could work better in characterizing e-bikers’ RLR behavior than the TPB model. The former two models explain more than 80% (81.3% and 81.4%, respectively) of the variance in e-bikers’ RLR behavior, which is remarkably higher than that of the TPB model (only 74.3%). (ii) It is also revealed that RLR willingness contributes more on influencing the RLR behavior than RLR intention, which implies that such behavior is dominated by social reactive decision-making rather than the reasoned one. (iii) Among the examined psychological factors, attitude, perceived behavioral control, past behavior, prototype perceptions (favorability and similarity), RLR intention, and RLR willingness were the crucial predictors of e-bikers’ RLR behavior. Our findings also support designing of more effective behavior-change interventions to better target e-bikers’ RLR behavior by considering the influence of the identified psychological factors.

Document type: Article

Simulation-Based Research on Driver Visibility of Black-and-White Striped Vehicles

Scipedia content — Mon, 15 Feb 2021 10:37:08 +0100

The vehicle color is considered to be a significant factor affecting driver visibility. The primary objective of this study is therefore to determine the impact of black-and-white striped vehicles (BWVs) on driver visibility through simulation-based experiments. In these experiments, subjects were asked to perform front and rear target identification tasks under daylight and twilight conditions. Then, a 2 (lighting conditions) × 2 (vehicle size) × 5 (vehicle color) analysis of variance was conducted for each task. Under the front identification scenario, the main factors affecting visibility were found to be lighting conditions, vehicle size, vehicle color, and the interactions between these factors. Under the rear identification scenario, lighting conditions and vehicle color were found to be the main factors. The results of this study demonstrate that driver visibility of BWVs is poorer than that of other colors of vehicles and that BWV visibility is susceptible to lighting conditions.

Document type: Article

Optimization and Simulation of Carsharing under the Internet of Things

Scipedia content — Mon, 15 Feb 2021 10:39:30 +0100

Internet of Things devices are popular in civilian and military applications, including smart device cities, smart grids, smart pipelines, and medical Internet of Things. Among them, carsharing supported by the Internet of Things is developing rapidly due to their advantages in environmental protection and reducing traffic congestion. The optimization of the carsharing system needs to consider the uncertainty of demand and the coupling relationship of multiple decision variables, which brings difficulties to the establishment of mathematical models and the design of efficient algorithms. Existing studies about carsharing optimization are mainly divided into four subproblems: the operation mode selection, vehicle type selection, demand analysis, or decision-making, rather than comprehensive consideration. This paper summarizes the four subproblems from the perspective of mathematical models, solving algorithms, and statistical methods and provides references for more comprehensive research in the future.

Document type: Article

Moving a Taxi Sector to Become Electric: Characterizing Taxi Drivers Interested in Purchasing a Full Electric Vehicle

Scipedia content — Mon, 15 Feb 2021 10:39:59 +0100

Electrification of mobility exceeds personal transport to increasingly focus on particular segments such as city logistics and taxis. These commercial mobility segments have different motives to purchase a full electric vehicle and require a particular approach to incentivize and facilitate the transition towards electric mobility. A case where a municipality was successful in stimulating the transition to electric mobility is the taxi sector in the city of Amsterdam. Using results from a survey study (n = 300), this paper analyses the differences in characteristics between taxi drivers that either have or do not have interest in purchasing a full electric taxi vehicle. Results show a low intention across the sample to adopt a full electric vehicle and no statistically significant differences in demographics between the two groups. Differences were found between the level of acceptability of the covenant, the rated attractiveness of the incentives, the ratings of full electric vehicle attributes and the consultation of objective and social information sources. These results can be used by policy makers to develop new incentives that target specific topics currently influencing the interest in a full electric taxi vehicle.

Document type: Article

The Situation and Development Strategies for Environmental Protection Standardization in Transportation Industry of China

Scipedia content — Mon, 15 Feb 2021 10:40:14 +0100

Standardization for environmental protection in the transportation industry is an important driving force for the development of green transportation. This study introduces the current status and main problems of environmental protection standardization in transportation. In addition, major countermeasures, such as strengthening the system construction and basic support, are studied and proposed to provide theoretical support and research basis for future standardization in related areas.

Document type: Article

Driving Simulator Validity of Driving Behavior in Work Zones

Scipedia content — Mon, 15 Feb 2021 10:40:57 +0100

Driving simulation is an efficient, safe, and data-collection-friendly method to examine driving behavior in a controlled environment. However, the validity of a driving simulator is inconsistent when the type of the driving simulator or the driving scenario is different. The purpose of this research is to verify driving simulator validity in driving behavior research in work zones. A field experiment and a corresponding simulation experiment were conducted to collect behavioral data. Indicators such as speed, car-following distance, and reaction delay time were chosen to examine the absolute and relative validity of the driving simulator. In particular, a survival analysis method was proposed in this research to examine the validity of reaction delay time. The result indicates the following: (1) most indicators are valid in driving behavior research in the work zone. For example, spot speed, car-following distance, headway, and reaction delay time show absolute validity. (2) Standard deviation of the car-following distance shows relative validity. Consistent with previous researches, some driving behaviors appear to be more aggressive in the simulation environment.

Document type: Article

Fatigue Driving Prediction on Commercial Dangerous Goods Truck Using Location Data: The Relationship between Fatigue Driving and Driving Environment

Scipedia content — Mon, 15 Feb 2021 10:44:03 +0100

The approaches monitoring fatigue driving are studied because of the fact that traffic accidents caused by fatigue driving often have fatal consequences. This paper proposes a new approach to predict driving fatigue using location data of commercial dangerous goods truck (CDT) and driver’s yawn data. The proposed location data are from an existing dataset of a transportation company that was collected from 166 vehicles and drivers in an actual driving environment. Six different categories of the predictor set are considered as fatigue-related indexes including travel time, day of week, road type, continuous driving time, average velocity, and overall mileage. The driver’s yawn data are used as a proxy for ground truth for the classification algorithm. From the six different categories of the predictor set, we obtain a set of 17 predictor variables to train logistic regression, neural network, and random forest classifiers. Then, we evaluate the predictive performance of the classifiers based on three indexes: accuracy, F1-measure, and area under the ROC curve (AUROC). The results show that the random forest is more suitable for predicting fatigue driving using location data according to its best accuracy (74.18%), F1-measure (62.02%), and AUROC (0.8059). Finally, we analyze the relationship between fatigue driving and driving environment according to variable importance described by random forest. In summary, our results obviously exhibit the potential of location data for reducing the accident rate caused by fatigue driving in practice.

Document type: Article

Internal versus external European air market realities: the competitive divide

Scipedia content — Mon, 15 Feb 2021 10:44:55 +0100

Background This paper looks at how ongoing attempts to improve air market competitiveness in Europe are challenged by the differing internal and external realities that exist. Europe’s internal multilateral single air market has encouraged the proliferation of pan-European airlines unhindered by national borders, which have stimulated increased competition and driven down airfare prices. Meanwhile, externally the bilateral system continues to dominate the wider global airline industry and a number of countries still prefer to negotiate air access with individual European countries. Methods Data from a five stage mixed-method Delphi study underpin the paper. Qualitative data, collected at a first stage brainstorming workshop and during final stage in-depth interviews, were thematically analysed to locate key and sub-themes. Quantitative survey data were collected across the remaining stages and were statistically analysed with mostly t-tests and chi-square tests of association to a 95% confidence level. Results The key theme transferability of the European regional single air market emerged from the study data; supported by the three sub-themes EU regional model, extraterritoriality and North Atlantic single air market. Conclusions Europe remains the multilateral exception to the general rule in international aviation that bilateralism is the norm. Despite efforts to address this competitive divide, aeropowers like China and Russia are reluctant to embrace extensive change, while major European flag carriers resist unfettered competition from outside the bloc.

Document type: Article

A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting

Scipedia content — Mon, 15 Feb 2021 10:45:52 +0100

Short-term traffic speed prediction is a promising research topic in intelligent transportation systems (ITSs), which also plays an important role in the real-time decision-making of traffic control and guidance systems. However, the urban traffic speed has strong temporal, spatial correlation and the characteristic of complex nonlinearity and randomness, which makes it challenging to accurately and efficiently forecast short-term traffic speeds. We investigate the relevant literature and found that although most methods can achieve good prediction performance with the complete sample data, when there is a certain missing rate in the database, it is difficult to maintain accuracy with these methods. Recent studies have shown that deep learning methods, especially long short-term memory (LSTM) models, have good results in short-term traffic flow prediction. Furthermore, the attention mechanism can properly assign weights to distinguish the importance of traffic time sequences, thereby further improving the computational efficiency of the prediction model. Therefore, we propose a framework for short-term traffic speed prediction, including data preprocessing module and short-term traffic prediction module. In the data preprocessing module, the missing traffic data are repaired to provide a complete dataset for subsequent prediction. In the prediction module, a combined deep learning method that is an attention-based LSTM (ATT-LSTM) model for predicting short-term traffic speed on urban roads is proposed. The proposed framework was applied to the urban road network in Nanshan District, Shenzhen, Guangdong Province, China, with a 30-day traffic speed dataset (floating car data) used as the experimental sample. Results show that the proposed method outperforms other deep learning algorithms (such as recurrent neural network (RNN) and convolutional neural network (CNN)) in terms of both calculating efficiency and prediction accuracy. The attention mechanism can significantly reduce the error of the LSTM model (up to 12.4%) and improves the prediction performance.

Document type: Article

The Relationship between Bus Drivers’ Improper Driving Behaviors and Abnormal Vehicle States Based on Advanced Driver Assistance Systems in Naturalistic Driving

Scipedia content — Mon, 15 Feb 2021 10:47:24 +0100

In order to improve the adaptation of driver to the advanced driver assistance system (ADAS) and optimize the active safety control technology of vehicle under man-computer cooperative driving, this paper investigated the correlation between driver’s improper driving behaviors and abnormal vehicle states under the ADAS. Based on the warning data collected from the driver’s assistance warning system equipped on buses, the interaction between improper behaviors, between abnormal vehicle states, and between improper behaviors and abnormal vehicle states were quantitatively analyzed through the hierarchical clustering method and improved Apriori algorithm. The results showed that eye closure and yawn were high in concurrency (probability: 0.888) and interaction (average probability: 0.946); the interaction among lane departure, rapid acceleration, and rapid deceleration are frequent (average probability: 0.7224); eye closure (average probability: 0.452) and yawn (average probability: 0.444) are likely to induce abnormal vehicle states such as rapid acceleration and rapid deceleration. Some suggestions proposed based on the results are as follows. First, it is suggested that the ADAS should combine the warning modes of eye closure and yawn; second, when the driver closes eyes or yawns, the control of the ADAS over the lateral and longitudinal performance of vehicle should be enhanced; third, the extent of control by the ADAS should be determined according to the relationship probability; finally, the lateral control over the vehicle by the ADAS should be strengthened when there is a forward collision warning.

Document type: Article

A computational framework for revealing competitive travel times with low carbon modes based on smartphone data collection

Scipedia content — Mon, 15 Feb 2021 10:48:41 +0100

Evaluating potential of shifting to low-carbon transport modes requires considering limited travel-time budget of travelers. Despite previous studies focusing on time-relevant modal shift, there is a lack of integrated and transferable computational frameworks, which would use emerging smartphone-based high-resolution longitudinal travel datasets. This research explains and illustrates a computational framework for this purpose. The proposed framework compares observed trips with computed alternative trips and estimates the extent to which alternatives could reduce carbon emission without a significant increase in travel time.. The framework estimates potential of substituting observed car and public-transport trips with lower-carbon modes, evaluating parameters per individual traveler as well as for the whole city, from a set of temporal and spatial viewpoints. The illustrated parameters include the size and distribution of modal shifts, emission savings, and increased active-travel growth, as clustered by target mode, departure time, trip distance, and spatial coverage throughout the city. Parameters are also evaluated based on the frequently repeated trips. We evaluate usefulness of the method by analyzing door-to-door trips of a few hundred travelers, collected from smartphone traces in the Helsinki metropolitan area, Finland, during several months. The experiment’s preliminary results show that, for instance, on average, 20% of frequent car trips of each traveler have a low-carbon alternative, and if the preferred alternatives are chosen, about 8% of the carbon emissions could be saved. In addition, it is seen that the spatial potential of bike as an alternative is much more sporadic throughout the city compared to that of bus, which has relatively more trips from/to city center. With few changes, the method would be applicable to other cities, bringing possibly different quantitative results. In particular, having more thorough data from large number of participants could provide implications for transportation researchers and planners to identify groups or areas for promoting mode shift. Finally, we discuss the limitations and lessons learned, highlighting future research directions.

Document type: Article

A Deep Cycle Limit Learning Machine Method for Urban Expressway Traffic Incident Detection

Scipedia content — Mon, 15 Feb 2021 10:49:19 +0100

In Beijing, Shanghai, Hangzhou, and other cities in China, traffic congestion caused by traffic incidents also accounts for 50% to 75% of the total traffic congestion on expressways. Therefore, it is of great significance to study an accurate and timely automatic traffic incident detection algorithm for ensuring the operation efficiency of expressways and improving the level of road safety. At present, many effective automatic event detection algorithms have been proposed, but the existing algorithms usually take the original traffic flow parameters as input variables, ignoring the construction of feature variable sets and the screening of important feature variables. This paper presents an automatic event detection algorithm based on deep cycle limit learning machine. The traffic flow, speed, and occupancy of downstream urban expressway are extracted as input values of the deep-loop neural network. The initial connection weights and output thresholds of the deep-loop neural network are optimized by using the improved particle swarm optimization (PSO) algorithm for global search. The higher classification accuracy of the extreme learning machine is trained, and the generalization performance of the extreme learning machine is improved. In addition, the extreme learning machine is used as a learning unit for unsupervised learning layer by layer. Finally, the microwave detector data of Tangqiao viaduct in Hangzhou are used to verify the experiment and compared with LSTM, CNN, gradient-enhanced regression tree, SVM, BPNN, and other methods. The results show that the algorithm can transfer low-level features layer by layer to form a more complete feature representation, retaining more original input information. It can save expensive computing resources and reduce the complexity of the model. Moreover, the detection accuracy of the algorithm is high, the detection rate is higher than 98%, and the false alarm rate is lower than 3%. It is better than LSTM, CNN, gradient-enhanced regression tree, and other algorithms. It is suitable for urban expressway traffic incident detection.

Document type: Article

Real-Time Incident Detection and Capacity Estimation Using Loop Detector Data

Scipedia content — Mon, 15 Feb 2021 10:50:34 +0100

Given the fact that the existing literature lacks the real-time estimation of road capacity and incident location using data from inductance loop detectors, a data-driven framework is proposed in this study for real-time incident detection, as well as road capacity and incident location estimation. The proposed algorithm for incident detection is developed based on the variation in traffic flow parameters acquired from inductance loop detectors. Threshold values of speed and occupancy are determined for incident detection based on the PeMS database. The detection of the incident is followed by the real-time road capacity and incident location estimation using a Cell Transmission Model (CTM) based approach. The data of several incidents were downloaded from PeMS and used for the development of the proposed framework presented in this study. Results show that the developed framework detects the incident and estimates the reduced capacity accurately. The location of the incident is estimated with an overall accuracy of 92.5%. The performance of the proposed framework can be further improved by incorporating the effect of the on-ramps, off-ramps, and high-occupancy lanes, as well as by modeling each lane separately.

Document type: Article

Passenger Volume Prediction by a Combined Input-Output and Distributed Lag Model and Data Analytics of Industrial Investment

Scipedia content — Mon, 15 Feb 2021 10:51:56 +0100

In order to sketch the transport infrastructure construction in an economy or a region, the government has to predict the passenger volume, under the local policy of industrial investment. In this paper, we propose a combined input-output and distributed lag prediction model of passenger volume in a province in P. R. China, under a certain policy of industrial investment called Silk Road Economic Belt. Specifically, the relationships between the passenger volume, GDP (gross domestic product), gross output, and transportation consumption are analyzed, and then the industrial development speed analysis and classification are used to calculate the average development speeds and the GDP contributions of 42 industries. Combining the input-output table, the provincial transportation consumption under the Silk Road Economic Belt policy is predicted, and the passenger volumes of the cities and the province in the future are predicted by the distributed lag models. Considering the uncertainty of the investment, the elastic ranges of the cities and the province’s passenger volumes are determined. The results show that the correlation between the passenger volume and transportation consumption is the highest, and it is equal to 0.975. In 2020, the passenger volume in Shaanxi is 1,641,305 thousands, and the error between the predicted value and the value obtained by summing the cities’ passenger volumes is smaller than 0.002%.

Document type: Article

Energy-Efficient Direct Yaw Moment Control for In-Wheel Motor Electric Vehicles Utilising Motor Efficiency Maps

Scipedia content — Mon, 15 Feb 2021 10:54:43 +0100

An active energy-efficient direct yaw moment control (DYC) for in-wheel motor electric vehicles taking motor efficiency maps into consideration is proposed in this paper. The potential contribution of DYC to energy saving during quasi-steady-state cornering is analysed. The study in this paper has produced promising results which show that DYC can be used to reduce the power consumption while satisfying the same cornering demand. A controller structure that includes a driver model and an offline torque distribution law during continuous driving and cornering is developed. For comparison, the power consumption of stability DYC is also analysed. Simulations for double lane change manoeuvres are performed and driving conditions either with a constant velocity or with longitudinal acceleration are designed to verify the effectiveness of the proposed controller in different driving situations. Under constant velocity cornering, since the total torque demand is not high, two rear wheels are engaged and during cornering it is beneficial to distribute more torque to one wheel to improve energy efficiency. In the simulated driving manoeuvres, up to 10% energy can be saved compared to other control methods. During acceleration in cornering, since the total torque demand is high, it is energy-efficient to use all the four in-wheel motors during cornering.

Document type: Article

Quantifying the Impact of Rainfall on Taxi Hailing and Operation

Scipedia content — Mon, 15 Feb 2021 10:55:50 +0100

Adverse weathers are well-known to impact the operation of transportation systems, including taxis. This paper utilizes taxi GPS waypoint data to investigate the quantitative impact of rainfall on taxi hailing and taxi operations to help improve service quality on rainy days. Through statistical analysis, the study proves that it is more difficult to hail taxis on rainy days, especially during morning peak hours. By modelling the difference value of factors for rainfall and nonrainfall conditions in a multivariate regression model and attaining the significance and elasticity of each factor, passenger demand, taxi supply, search time and velocity are proved to be the significant factors that lower the taxis’ level of service on rainy days. Among them, the number of passengers and taxis are two factors that have the greatest impact. It is also shown that there is no significant difference in the total taxi supply and passenger demand between rainfall and nonrainfall conditions, but a dramatic change in the spatial distribution is discovered. The results suggest that instead of simply providing more taxis on rainy days, optimally dispatching taxicabs to high demand regions can be a more effective solution.

Document type: Article

The influence of economic barriers and drivers on energy efficiency investments in maritime shipping, from the perspective of the principal-agent problem

Scipedia content — Mon, 15 Feb 2021 10:56:54 +0100

[Abstract:] Maritime transport stands out as a strategic sector; the increasing trend in maritime traffic makes it essential to reduce energy consumption and emissions through investment in energy efficiency. However, investments can be hindered by barriers, and drivers are necessary to reduce or overcome them and promote investment. Consequently, the purpose of this study is to analyze what factors influence investment decisions—and how they do so—when there are principal-agent problems in the shipowner–charterer relationship. The methodology is based on the following process: model and hypotheses formulation, variable definition, the creation of a study sample and statistical treatment through a descriptive analysis of variables and a binomial logistic regression model, all based on a state-of-the-art application. The results corroborate the hypotheses and indicate that principal-agent problems and split incentives, especially in time charter contracts, and a lack of verified information make the shipowners less likely to invest. Moreover, energy efficiency measures are less likely to be implemented in older vessels, possibly due to the difficulty associated with recovering the investment; they are more likely in larger and newer vessels, and regulation encourage their adoption. Furthermore, investment is more likely in vessels with verified information and high levels of both activity and harmful emissions. Improved knowledge in this field could help businesses and governments to act in a more sustainable manner, without detriment to an innovative and competitive sector. Consellería de Cultura, Educación e Ordenación Universitaria; ED481A-2015/224 Ministerio de Ciencia, Innovación y Universidades; RTI2018-100702-B-I00

Document type: Article

Research on Consumers’ Preferences for the Self-Service Mode of Express Cabinets in Stations Based on the Subway Distribution to Promote Sustainability

Scipedia content — Mon, 15 Feb 2021 11:00:56 +0100

With the explosive growth in the express delivery business, last-mile delivery issues have come to the forefront in China. Subway-based distribution has been demonstrated and practiced. The self-service mode of express cabinets in stations based on the subway distribution can effectively reduce the last-mile delivery costs, increase the utilization rate of public transportation resources, and reduce traffic congestion and carbon emissions. This paper designed self–service mode of express cabinets in stations and discussed the feasibility by investigating consumers’ preferences. The consumers’ preferences and influencing factors were examined by using the multicategorical logit model. The results show that consumers’ gender, education level and number of online purchases per month have an impact on consumers’ preferences. The majority of consumers are willing to actively engage in green consumer behavior. Meanwhile, consumers are more concerned about whether the express mode is convenient to conduct and the queuing of an express cabinet. Some suggestions and recommendations on promoting this self-service mode were put forward, such as pushing different advertisements for different groups of consumers, designing efficient and multi-function express cabinets, and adopting a reward system. This research provides guidance for decision making regarding the promotion of a new self–service mode based on the subway distribution, which can promote sustainable consumption and improve the efficient operation of urban last-mile delivery and the low-carbon development of urban transportation.

Document type: Article

Modeling Drivers’ Stopping Behaviors during Yellow Intervals at Intersections considering Group Heterogeneity

Scipedia content — Mon, 15 Feb 2021 11:02:29 +0100

Stopping behavior during yellow intervals is one of the critical driver behaviors correlated with intersection safety. As the main index of stopping behavior, stopping time is typically described by Accelerated Failure Time (AFT) model. In this study, the comparison of survival curves of stopping time confirms the existence of group specific effects on drivers. However, the AFT model is developed based on the homogeneity assumption. To overcome this drawback, shared frailty survival models are developed for stopping time analysis, which consider the group heterogeneity of drivers. The results show that log-logistic based frailty model with age as a grouping variable has the best goodness of fit and prediction accuracy. Analysis of the models’ parameters indicates that phone status, maximum deceleration, vehicles’ speed, and the distance to stopping line at the onset of the yellow signal have significant impacts on stopping time. Additionally, heterogeneity analysis illustrates that young, middle-aged, and female drivers are more likely to brake harshly and stop past the stop line, which may block the intersection. Furthermore, drivers, who are more familiar with traffic environments, are more possible to make reasonable stopping decisions approaching intersections. The results can be utilized by traffic authorities to implement road safety strategies, which will help reduce traffic incidents caused by improper stopping behavior at intersections.

Document type: Article

Defining Highway Node Acceptance Capacity (HNAC): Theoretical Analysis and Data Simulation

Scipedia content — Mon, 15 Feb 2021 11:04:39 +0100

A new concept of Highway Node Acceptance Capacity (HNAC) is proposed in this paper inspired by a field data observation. To understand HNAC in microscopic view, boundary condition of successful merging is found using car-following behaviours and lane-changing rules, which could also explain traffic oscillations. In macroscopic view, linear positive relationship between HNAC and background traffic volume is obtained based on moving bottleneck. To determine the explicit form of the relationship, data simulation considering car-following behaviours and traffic flow theory is used. In the results, the synchronization phenomenon of oscillation in on-ramp (with respect to main road) and intersected road is found. The explicit equation of HNAC is determined based on standard deviation and correlation coefficient analysis, and also proved to be accurate with model validation, which is helpful in studies related to propagation mechanism of traffic emergencies on highway network.

Document type: Article

Understanding how city networks are leveraging climate action: experimentation through C40

Scipedia content — Mon, 15 Feb 2021 11:05:02 +0100

"jats:p"Climate change is one of the most challenging environmental and social problems for contemporary urban planning. In response to this phenomenon, city networks have emerged as new configurations of urban climate governance that encourage the implementation of experiments such as testing new solutions regarding sustainable transport. While city networks are gaining momentum and influence as effective platforms to transform and scale up pilot experiments into city-wide schemes, little is known regarding their role in conditioning and leveraging such urban experiments Our paper investigates the underexplored nature of urban experiments within city networks and provides a better understanding of how these networks condition urban experiments. To this end an analytical model has been developed and applied to the case of the C40 Climate Leadership Group (C40) and its "jats:italic"Climate Positive Development Good Practice Guide."/jats:italic" Our findings suggest that the C40 encourages variation in local climate experiments and the generation of new and innovative climate solutions in member cities. In particular they reveal that the implementation of climate positive experiments has passed the ‘variation’ stage, is currently in the ‘selection’ stage, and likely to move towards the ‘retention’ stage in the near future. Potential experimentation outputs of the case are identified as built environment change, new citizen practices, policy change, infrastructural change and new technology. Noticeably, we consider that the C40 plays an important role in providing fundamental institutional support to implement and leverage climate projects within its member cities.

Document type: Article

Research on the Electromagnetic-Heat-Flow Coupled Modeling and Analysis for In-Wheel Motor

Scipedia content — Mon, 15 Feb 2021 11:05:40 +0100

In this paper, a 15 KW in-wheel motor (IWM) is taken as the research object, and the coupling factors among the electromagnetic field, temperature field and flow field are analyzed, and the strong and weak coupling factors between the three fields are clarified, and by identifying the strong and weak coupling factors between the three fields, a three-field coupling analysis model for IWM with appropriate complexity is established, and the validity of the model is verified. In a certain driving condition, the electromagnetic field, temperature field and flow field characteristics of IWM are analyzed with the multi-field coupling model. The result shows that, after the IWM runs 8440 s under driving conditions, in this paper, the IWM electromagnetic torque of the rated working condition is 134.2 Nm, and IWM the electromagnetic torque of the peak working condition is 451.36 Nm, and the power requirement of the motor can be guaranteed. The highest temperature of the IWM is 150 °

C, which does not exceed the insulation grade requirements of the motor (155 °

C), the highest temperature of the permanent magnet (PM) is 65.6 °

C, and it does not exceed the highest operating temperature of the PM, and ensures the accurate calculation of components loss and the temperature of the motor. It can be found, through research, that the electromagnetic torque difference between unidirectional coupling and bidirectional coupling is 3.2%, the maximum temperature difference is 7.98% in the three-field coupling analysis of IWM under rated working conditions. Therefore, it is necessary to consider the influence of coupling factors on the properties of motor materials when analyzing the electromagnetic field, temperature field and flow field of IWM

it also provides some reference value for the simulation analysis of IWM in the future.

Document type: Article

A Correlative Analysis of Modern Logistics Industry to Developing Economy Using the VAR Model: A Case of Pakistan

Scipedia content — Mon, 15 Feb 2021 11:07:22 +0100

The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap has become a policy issue considering ever-increasing factors and their influence on this relation. Most existing studies have explored this interaction from a general perspective, or for developed countries. This paper explores time-series analysis of the dynamic variables and their inter-related influence in both the short and long run on the relationship between modern logistic industry and economic growth—a more specific perspective, particularly for developing countries. Accordingly, we exemplify our analysis by employing the vector autoregression (VAR) model to the most updated time series data of investment in the logistics industry and the economic growth of Pakistan from 1990 to 2018. The empirical findings endorse the previous studies’ outcomes and recognize the importance of sustainable economic development concerning continuously improving the logistics industry. However, a unidirectional relation is observed that economic growth leads to developing the logistics industry—economic growth exerts a significant demand-pull effect on Pakistan’s logistics. It implies that logistic industrial development is comparatively quicker in the geographical areas where economic growth is higher than those areas where economic growth is low. To conclude this study’s findings, logistics industry reforms should prioritize the selected geographical areas in improving the economy that would lead to the modern logistics industry’s development. As the model adopts Pakistan’s context, the overall statistical analysis can be generalized to other developing economies. These results would be of particular interest to strategy makers working in developing countries and help them design and develop modern transportation and logistics, coupled with interlinked technological factors, which would attract investment in the logistics industry for sustainable economic development.

Document type: Article

Seasonality Effect Analysis and Recognition of Charging Behaviors of Electric Vehicles: A Data Science Approach

Scipedia content — Mon, 15 Feb 2021 11:07:40 +0100

Electric vehicles (EVs) presence in the power grid can bring about pivotal concerns regarding their energy requirements. EVs charging behaviors can be affected by several aspects including socio-economics, psychological, seasonal among others. This work proposes a case study to analyze seasonal effects on charging patterns, using a public real-world based dataset that contains information from the aggregated load of the total charging stations of Boulder, Colorado. Our approach targets to forecast and recognize EVs demand considering seasonal factors. Principal component analysis (PCA) was used to provide a visual representation of the variables and their contribution and the correlation among them. Then, twelve classification models were trained and tested to discriminate among seasons the charging load of electric vehicles. Later, a benchmark stage is presented for regression as well as for classification results. For regression models, examined through Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE), the random Forest provides better prediction than quasi-Poisson model widely. However, it was observed that for large variations in electric vehicles’ charging load, quasi-Poisson fits better than random forest. For the classification models, evaluated through Accuracy and the Area under the Curve, the Lasso and elastic-net regularized generalized linear (GLMNET) model provided the best global performance with accuracy up to 100% when evaluated on the test dataset. The results of this work offer great insights for enhancing demand response strategies that involve PEV charging regarding charging habits across seasons.

Document type: Article

An Application of Cluster Analysis Method to Determine Vietnam Airlines’ Ground Handling Service Quality Benchmarks

Scipedia content — Mon, 15 Feb 2021 11:27:45 +0100

This paper recommends that Vietnam Airlines use a pro-offered model to both evaluate and improve its current service network being operated at international airports. The model includes cluster analysis, ANOVA, and Scheffé post hoc to provide service performance insights and to serve as a complementary corporate benchmark for evaluating service potential and for identifying deficient service areas. By means of this model, the managerial board can designate a potent strategy for ground handling service. Additionally, the given model provides expatriate station managers with a clearer viewpoint of the localized productivity level as performed in relation to other airports concomitant within their own clusters.

Document type: Article

Efficiency Evaluation of Bus Transport Operations Given Exogenous Environmental Factors

Scipedia content — Mon, 15 Feb 2021 11:28:31 +0100

As a mode of green transport that can effectively alleviate urban traffic congestion and improve air quality, bus transport is highly subsidized by governments at all levels in China. Thus, measuring efficiency in the bus transport sector is particularly important. However, few reports in the literature have taken exogenous environmental factors into consideration to evaluate public transport operation efficiency. This may lead to inaccurate evaluation results. This study employs the three-stage DEA model, which can eliminate the impacts of exogenous environmental factors on public bus transport operation to gain real efficiency results. Meanwhile, to further explore how exogenous environmental factors affect bus transport operations, a tobit model is used to analyse the results. The main results of this paper reveal the following: first, exogenous environmental factors have a significant impact on the operational efficiency of bus transport. It is reasonable and necessary to select the three-stage method to eliminate environmental factors for real bus operation efficiency. Second, the fluctuations of the bus transport efficiency of 30 cities decreased during 2010–2016. The western region has the highest operation efficiency, followed by the eastern and the middle regions. Third, the economic, taxi transport, and urban rail transport have a marked impact on the operational efficiency of bus transport. This paper confirms the important influence of exogenous environmental factors on the efficiency of public transport operations. In addition, this article could help improve the efficiency of urban public transport operations and promote the attractiveness of urban public transport and the amount of green travel.

Document type: Article

Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data

Scipedia content — Mon, 15 Feb 2021 11:28:49 +0100

In order to improve the driver’s physiological and psychological state, the driver’s mental load which is caused by sight distance, lighting, and other factors in the tunnel environment should be quantified via modeling the spatiotemporal data. The experimental schemes have been scientifically designed based on methods of traffic engineering and human factor engineering, which aims to test the driver’s spatiotemporal data of eye movement and ECG (electrocardiogram) index in the tunnel environment. Firstly, the changes in the driver’s spatiotemporal data are analyzed to judge the changing trend of the driver’s workload in the tunnel environment. The results show that the cubic spline interpolation function model can fit the dynamic changes of average pupil diameter and heart rate (HR) growth rate well, and the goodness of fit for the model group is above 0.95. So, tunnel environment makes the driver’s typical physiological indicators fluctuate in the coordinates of time and space, which can be modeled and quantified. Secondly, in order to analyze the classification of tunnel risk level, a fusion model has been built based on the functions of average pupil diameter and HR growth rate. The tunnel environmental risk level has been divided into four levels via the fusion model, which can provide a guidance for the classification of tunnel risk level. Furthermore, the fusion model allows tunnel design and construction personnel to adopt different safety design measures for different risk levels, and this method can effectively improve the economy of tunnel operating safety design.

Document type: Article

Recognition of Functional Areas Based on Call Detail Records and Point of Interest Data

Scipedia content — Mon, 15 Feb 2021 11:29:10 +0100

With the recent emergence of big data, there has been significant progress in the study of big data mining and rapid developments in urban computing. With the integration of planning and management in urban areas, there is an urgent need to focus on the identification of urban functional areas (UFAs) based on big data. This paper describes the concept of communication activity intensity, which is more meaningful than the number of communication activities or the user density in identifying UFAs. The impact of diverse geographical area subdivisions on the accuracy of UFA recognition is discussed, and a "jats:italic"k"/jats:italic"-means clustering method for dynamic call detail record data and kernel density estimation technique for static point of interest data are established at the traffic analysis zone level. A case study on the region within Beijing’s 3rd Ring Road is conducted, and the results of UFA identification are qualitatively and quantitatively verified. The causes of large passenger flows on certain metro lines in Beijing are also analyzed. The highest identification accuracy is obtained for park and scenery areas, followed by residential areas and office areas. In conclusion, the proposed method offers a significant improvement over the identification accuracy of previous techniques, which verifies the reliability of the method.

Document type: Article

Nowcast models for train delays based on the railway network status

Scipedia content — Mon, 15 Feb 2021 11:29:42 +0100

Switches and crossings (S&C) or turnouts are one of the important systems in the Swedish railway traffic maintenance planning. For immediate diverting of the trains, they need to be predict the working condition for short time duration, also known as nowcasting and for long time duration, also known as forecasting. The prediction of the condition of turnout is useful for traffic planning without disrupting to the traffic. Hence, the main purpose of this paper is to predict the condition of S&Cs for shorter and longer duration. In order to achieve it, at first, statistical analysis is carried out to find the root causes of failures. Secondly, non-homogenous Poisson process is applied to nowcast and forecast the working condition. The results of this study will guide the train dispatchers to plan the train timetable according the present traffic.

Document type: Article

Assessing Sustainable Mobility Measures Applying Multicriteria Decision Making Methods

Scipedia content — Mon, 15 Feb 2021 11:30:45 +0100

n increasing number of recent discussions have focused on the need for designing transport systems in consonance with the importance of the environment, thus promoting investment in the growth of non-motorized transport infrastructure. Under such conditions, the demand for implementing the most effective infrastructure measures has a profoundly positive impact, and requires the least possible financial and human resources. The development of the concept of sustainable mobility puts emphasis on the integrated planning of transport systems, and pays major attention to the expansion of non-motorized and public transport, and different sharing systems, as well as to effective traffic management involving intelligent transport systems. The development of transport infrastructure requires massive investment, and hence the proper use of mobility measures is one of the most important objectives for the rational planning of sustainable transport systems. To achieve this established goal, this article examines a compiled set of mobility measures and identifies the significance of the preferred tools, which involve sustainable mobility experts. The paper also applies multicriteria decision making methods in assessing urban transport systems and their potential in terms of sustainable mobility. Multicriteria decision making methods have been successfully used for assessing the effectiveness of sustainable transport systems, and for comparing them between cities. The proposed universal evaluation model is applied to similar types of cities. The article explores the adaptability of the model by assessing big Lithuanian cities.

This article belongs to the Special Issue SUMP for Cities’ Sustainable Development

This research was funded by Vilnius Gediminas Technical University

Document type: Article

Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation

Scipedia content — Mon, 15 Feb 2021 11:31:04 +0100

As the penetration of electric vehicles (EVs) accelerates according to eco-friendly policies, the impact of electric vehicle charging demand on a power distribution network is becoming significant for reliable power system operation. In this regard, accurate power demand or load forecasting is of great help not only for unit commitment problem considering demand response but also for long-term power system operation and planning. In this paper, we present a forecasting model of EV charging station load based on long short-term memory (LSTM). Besides, to improve the forecasting accuracy, we devise an imputation method for handling missing values in EV charging data. For the verification of the forecasting model and our imputation approach, performance comparison with several imputation techniques is conducted. The experimental results show that our imputation approach achieves significant improvements in forecasting accuracy on data with a high missing rate. In particular, compared to a strategy without applying imputation, the proposed imputation method results in reduced forecasting errors of up to 9.8%.

Document type: Article

A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems

Scipedia content — Mon, 15 Feb 2021 11:32:08 +0100

A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

Document type: Article

The Dynamical Decision Model of Intersection Congestion Based on Risk Identification

Scipedia content — Mon, 15 Feb 2021 11:32:31 +0100

The paper focuses on the problem of traffic congestion at intersection based on the mechanism of risk identification. The main goal of this study is to explore a new methodology for identifying and predicting the intersection congestion. Considering all the factors influencing the traffic status of intersection congestion, an integrated evaluation index system is constructed. Then, a detailed dynamic decision model is proposed for identifying the risk degree of the traffic congestion and predicting its influence on future traffic flow, which combines the traffic flow intrinsic properties with the basic model of the Risking Dynamic Multi-Attribute Decision-Making theory. A case study based on a real-world road network in Baoji, China, is implemented to test the efficiency and applicability of the proposed modeling. The evaluation result is in accord with the actual condition and shows that the approach proposed can determine the likelihood and risk degree of the traffic congestion occurring in the intersection, which can be used as a tool to help transport managers make some traffic control measures in advance.

Document type: Article

Effect of High-Altitude Environment on Driving Safety: A Study on Drivers’ Mental Workload, Situation Awareness, and Driving Behaviour

Scipedia content — Mon, 15 Feb 2021 11:33:21 +0100

This study aims to analyze the effect of high-altitude environment on drivers’ mental workload (MW), situation awareness (SA), and driving behaviour (DB), and to explore the relationship among those driving performances. Based on a survey, the data of 356 lowlanders engaging in driving activities at Tibetan Plateau (high-altitude group) and 341 lowlanders engaging in driving activities at low altitudes (low-altitude group) were compared and analyzed. The results suggest that the differences between the two groups are noteworthy. Mental workload of high-altitude group is significantly higher than that of low-altitude group, and their situation awareness is lower significantly. The possibility of risky driving behaviours for high-altitude group, especially aggressive violations, is higher. For the high-altitude group, the increase of mental workload can lead to an increase on aggressive violations, and the situation understanding plays a full mediating effect between mental workload and aggressive violations. Measures aiming at the improvement of situation awareness and the reduction of mental workload can effectively reduce the driving risk from high-altitude environment for lowlanders.

Document type: Article

Performance evaluation of lossy quality compression algorithms for RNA-seq data

Scipedia content — Mon, 15 Feb 2021 11:33:37 +0100

Background Recent advancements in high-throughput sequencing technologies have generated an unprecedented amount of genomic data that must be stored, processed, and transmitted over the network for sharing. Lossy genomic data compression, especially of the base quality values of sequencing data, is emerging as an efficient way to handle this challenge due to its superior compression performance compared to lossless compression methods. Many lossy compression algorithms have been developed for and evaluated using DNA sequencing data. However, whether these algorithms can be used on RNA sequencing (RNA-seq) data remains unclear. Results In this study, we evaluated the impacts of lossy quality value compression on common RNA-seq data analysis pipelines including expression quantification, transcriptome assembly, and short variants detection using RNA-seq data from different species and sequencing platforms. Our study shows that lossy quality value compression could effectively improve RNA-seq data compression. In some cases, lossy algorithms achieved up to 1.2-3 times further reduction on the overall RNA-seq data size compared to existing lossless algorithms. However, lossy quality value compression could affect the results of some RNA-seq data processing pipelines, and hence its impacts to RNA-seq studies cannot be ignored in some cases. Pipelines using HISAT2 for alignment were most significantly affected by lossy quality value compression, while the effects of lossy compression on pipelines that do not depend on quality values, e.g., STAR-based expression quantification and transcriptome assembly pipelines, were not observed. Moreover, regardless of using either STAR or HISAT2 as the aligner, variant detection results were affected by lossy quality value compression, albeit to a lesser extent when STAR-based pipeline was used. Our results also show that the impacts of lossy quality value compression depend on the compression algorithms being used and the compression levels if the algorithm supports setting of multiple compression levels. Conclusions Lossy quality value compression can be incorporated into existing RNA-seq analysis pipelines to alleviate the data storage and transmission burdens. However, care should be taken on the selection of compression tools and levels based on the requirements of the downstream analysis pipelines to avoid introducing undesirable adverse effects on the analysis results.

Document type: Article

A New Production-Splitting Method for the Multi-Well-Monitor System

Scipedia content — Mon, 15 Feb 2021 11:56:29 +0100

In order to reduce the cost of wellheads, the production rate of the gas wells in the Hechuan Gas Field are mostly measured in groups, which raises a stringent barrier for industries to determine the production rate of each single well. The technique for determining the production of a single well from the production of the well-group can be called the production splitting method (PSM). In this work, we proposed a novel PSM for the multi-well-monitor system (MWMS) on the basis of the Beggs and Brill (BB) correlation. This proposed method can account for the multi-phase flow together with the features of the pipelines. Specifically, we discretize the pipeline into small segments and recognize the flow pattern in each segment. The pressure drop along the pipeline is calculated with the Beggs and Brill correlation, and the production of each well is subsequently determined with a trial method. We also applied this proposed method to a field case, and the calculated results show that the results from this work undergo an excellent agreement with the field data.

Document type: Article

MPP: A Novel Algorithm for Estimating Vehicle Space Headways from a Single Image

Scipedia content — Mon, 15 Feb 2021 11:57:45 +0100

Vehicle space headway, also called spacing, is an important and basic traffic parameter. Traditional space headway calculation methods are facing the problems of large errors and high costs. This paper presents a novel algorithm based on measurement point pairs (MPPs) to estimate the real-time microcosmic vehicle space headway from single images in existing traffic surveillance videos and images without any additional equipment. First, the camera is calibrated with road markings to obtain the relationship between the image coordinates and the world coordinates. Second, vehicle pairs of two successive vehicles in the image are established, measurement points on each vehicle are selected by video intelligence analysis technologies, and their world coordinates are calculated by camera calibration results. Finally, the measurement points of the preceding and following vehicles are matched to obtain the MPPs, followed by the calculation of the weighted space headway. By using the measurement point information, one of the most difficult problems in image distance measurement, the lack of height information, is solved. The main factors causing estimation errors are fully addressed and the range and trend of errors under certain conditions are given by virtual simulation. Two real-world experiments are used to prove the accuracy and usability of the MPP in common video scenes: the simulation experiment indicates that the MPP algorithm achieves a high accuracy with estimation error less than ±0.1 m and the relative error within 1.1%; the application experiment shows that the MPP-based calculation is more accurate and stable than the state-of-the-art distance measurement algorithm and that the convenience of the proposed MPP algorithm is higher than that of traditional methods of space headway estimation.

Document type: Article

Effects of Vehicle Restriction Policies on Urban Travel Demand Change from a Built Environment Perspective

Scipedia content — Mon, 15 Feb 2021 11:58:11 +0100

License plate restriction (LPR) policy presents the most straightforward way to reduce road traffic and emissions worldwide. However, in practice, it has aroused great controversy. This policy broke the original structure of the urban transportation mode, which needed some matching strategies to adapt to this change. Investigating this travel demand change is a challenging task because it is greatly influenced by features of the local built environment. Fourteen variables from four dimensions, location, land-use diversity, distance to transit, and street design, are used to depict the built environment; moreover, the severe collinearity underlies these feature variables. To solve the multicollinearity among the variables and high-dimensional problem, this study utilizes two different penalization-based regression models, the LASSO (least absolute shrinkage and selection operator) and Elastic Net regression algorithms, to achieve the variable selection and explore the impacts of the built environment on the change of travel demand triggered by the LPR policy. Travel demand changes are assessed by the relative variation in taxi ridership in each traffic analysis zone based on the taxi GPS data. Built environment variables are measured using the transportation network data and the Baidu Map Service points of interest (POI) data. The results show that regions with a higher level of public transportation service and a higher degree of the land mix have a stronger resilience to the vehicle restriction policy. Besides, the contribution rate of public transportation is stable as a whole, while the contribution rate of richness depends on specific types of land use. The conclusions in this study can provide in-depth insights into the influence of the LPR policy and underpin traffic complementary policies to ensure the effectiveness of LPR.

Document type: Article

Macroscopic Traffic Flow Characterization at Bottlenecks

Scipedia content — Mon, 15 Feb 2021 12:00:37 +0100

Traffic congestion is a significant issue in urban areas. Realistic traffic flow models are crucial for understanding and mitigating congestion. Congestion occurs at bottlenecks where large changes in density occur. In this paper, a traffic flow model is proposed which characterizes traffic at the egress and ingress to bottlenecks. This model is based on driver response which includes driver reaction and traffic stimuli. Driver reaction is based on time headway and driver behavior which can be classified as sluggish, typical or aggressive. Traffic stimuli are affected by the transition width and changes in the equilibrium velocity distribution. The explicit upwind difference scheme is used to evaluate the Lighthill, Whitham, and Richards (LWR) and proposed models with a continuous injection of traffic into the system. A stability analysis of these models is given and both are evaluated over a road of length 10 km which has a bottleneck. The results obtained show that the behavior with the proposed model is more realistic than with the LWR model. This is because the LWR model cannot adequately characterize driver behavior during changes in traffic flow.

Document type: Article

Research on Creating Ecological Highway for Serving Construction of Powerful Transportation Country

Scipedia content — Mon, 15 Feb 2021 12:01:51 +0100

Green transportation is an important feature and intrinsic requirement of a powerful transportation country. Therefore, we shall fully implement the spirit of the 19th National Congress of the Communist Party of China, effectively implement the new development concept, further promote the development of green transportation and serve the construction of a powerful transportation country. An important part of green transportation system is the ecological highway. Therefore, this paper firstly clarifies the concept, connotation and characteristics of ecological highway, defines the whole life cycle of ecological highway construction, that is, different control points in each stage from planning, design, construction to operation, management and maintenance, introduces the built ecological highway in China, proposes the implementation scheme of ecological highway construction based on the specific requirements and key technologies and finally elaborates the safeguard measures for ecological highway construction. Besides, this paper also provides a reference for clarifying the idea and development of ecological highway construction.

Document type: Article

Effect of Concentric Annular Gap Flow on Wall Shear Stress of Stationary Cylinder Pipe Vehicle under Different Reynolds Numbers

Scipedia content — Mon, 15 Feb 2021 12:02:11 +0100

The tube-contained raw material pipeline hydraulic transportation technology is an optimization and improvement of traditional hydraulic capsule pipeline (HCP) transport. It has the advantages of lower resource consumption, environmental protection, and less demand for human resources and has the ability to directly transport solids, liquids, and gases. The cylinder pipe vehicle is the core component of tube-contained raw material pipeline hydraulic transportation; its motion characteristics and energy consumption are affected by wall shear stress. When the cylinder pipe vehicle is stationary, the annular gap flow will affect the wall shear stress. This paper studies the wall shear stress and annular flow field distribution of a stationary cylinder pipe vehicle under different Reynolds numbers. The results show that as the Reynolds number increases, both the wall shear stress and the annular gap flow velocity show a gradually increasing trend. The wall shear stress and the velocity of the annular gap flow show some correlation, but there are differences in the trend of axial and circumferential wall shear stress along the length of the cylinder pipe vehicle. The research in this article will further improve the theoretical system of hydraulic conveyance of barrel-loading pipelines and provide a theoretical basis for the realization of industrial applications as soon as possible.

Document type: Article

Dynamic Model for Scheduling Crew Shifts

Scipedia content — Mon, 15 Feb 2021 12:02:29 +0100

In regular as well as nonscheduled air transport, extraordinary situations occasionally occur, which may fundamentally disrupt the flight schedule. Fundamental disruptions of flight schedules affect not only passengers but also the airline. One of the areas that are negatively affected by the disruption is the crew plan. Due to extraordinary events, it happens that a flight is delayed, and the crew will not be at the destination airport at the prescribed time and the airline will not be able to assign it on further flights according to the original plan. Such situations can be resolved either by deploying any other available crew or by delaying the flight appropriately until the previously planned crew is available. Assigning a new crew entails additional costs for the airline, as it has to assign more flight staff than had been originally planned. Furthermore, delayed flights lead to paying passengers financial compensation, incurring additional costs for airlines. Therefore, it is important that the airline is able to resolve any irregularity situations so that the additional costs incurred to deal with the irregularity situations are kept at a minimum. The paper presents one possible approach, a mathematical model that can be used to solve such a situation. The presented mathematical model may be the basis for the decision support system of the operations center worker who is responsible for the operational management of flight crews. The model will primarily aim at smaller airlines that cannot afford expensive software and often rely on manual solutions. However, a manual solution may not always be the best, as the operator, who plans the processes, may not consider all the constraints. Another important factor that makes the decision processes more difficult is that it is usually necessary to decide in a short period of time. The solution proposed in this paper will allow the operator to make a quick decision that will also be the most advantageous for the airline. This is because the proposed method is an exact approach, which guarantees finding the optimum solution. In this article, we are only dealing with pilot crews. Web of Science 2020 art. no. 5372567

Document type: Article

Sociodemography, Geography, and Personality as Determinants of Car Driving and Use of Public Transportation

Scipedia content — Mon, 15 Feb 2021 12:03:03 +0100

To address the sustainability challenges related to travel behavior, technological innovations will not be enough. Behavioral changes are also called for. The aim of the present study is to examine the influence of sociodemography, geography, and personality on car driving and use of public transportation. Sociodemographic factors have been defined by age, gender, income, and education. Geographic factors have been studied through residential area (e.g., rural and urban areas). Personality has been studied through the Five-Factor-Model of personality&mdash

degree of Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The analysis is based on a survey with 1812 respondents, representative for the Swedish population. Regarding sociodemographic factors, car driving is explained by being male, higher age, higher income, while use of public transportation is explained by lower age and higher education. The user profile of a car driver is the opposite to that of a public transport passenger when it comes to geographic factors

urban residential area explains public transportation while rural area explains car driving. Some personality factors are also opposites

a low degree of Openness and a high degree of Extraversion explain car driving, while a high degree of Openness and a low degree of Extraversion explain use of public transportation. Moreover, car driving is explained by a low degree of Neuroticism, while use of public transportation is explained by a low degree of Conscientiousness and a high degree of Agreeableness. Since sociodemography, geography, and personality influence how people process information and evaluate market propositions (e.g., products and services), the findings presented here are useful for policymakers and transportations planners who would like to change behavior from car driving to public transportation use. Caution should be taken in interpreting the relationship between personality traits and transportation modes, since the personality traits are measured by a short scale (i.e., Big Five Inventory (BFI)-10), with limitations in the factor structure for a representative sample of the Swedish population.

Document type: Article

Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model

Scipedia content — Mon, 15 Feb 2021 12:03:22 +0100

The economic and health impacts resulting from the greenhouse effect is a major concern in many countries. The transportation sector is one of the major contributors to greenhouse gas (GHG) emissions worldwide. Almost 15 percent of the global GHG and over 20 percent of energy-related CO"sub"2"/sub" emissions are produced by the transportation sector. Quantifying GHG emissions from the road transport sector assists in assessing the existing vehicles’ energy consumptions and in proposing technological interventions for enhancing vehicle efficiency and reducing energy-supply greenhouse gas intensity. This paper aims to develop a model for the projection of GHG emissions from the road transport sector. We consider the Vehicle-Kilometre by Mode (VKM) to Number of Transportation Vehicles (NTV) ratio for the six different modes of transportation. These modes include motorcycles, passenger cars, tractors, single-unit trucks, buses and light trucks data from the North American Transportation Statistics (NATS) online database over a period of 22 years. We use multivariate regression and double exponential approaches to model the projection of GHG emissions. The results indicate that the VKM to NTV ratio for the different transportation modes has a significant effect on GHG emissions, with the coefficient of determination adjusted R"sup"2"/sup" and R"sup"2"/sup" values of 89.46% and 91.8%, respectively. This shows that VKM and NTV are the main factors influencing GHG emission growth. The developed model is used to examine various scenarios for introducing plug-in hybrid electric vehicles and battery electric vehicles in the future. If there will be a switch to battery electric vehicles, a 62.2 % reduction in CO"sub"2"/sub" emissions would occur. The results of this paper will be useful in developing appropriate planning, policies, and strategies to reduce GHG emissions from the road transport sector.

Document type: Article

Assessment of Priorities of Construction of High-Speed Rail in the Czech Republic in Terms of Impacts on Internal and External Integration

Scipedia content — Mon, 15 Feb 2021 12:07:56 +0100

The priorities assessment for the planned construction of high-speed rail/HSR in the Czech Republic in terms of impacts on internal and external integration is a though-provoking topic not only from the technical and economic, but also from the social and geographical point of view. Its primary basis is the application of the gravity model, according to which the planned route C Prague-Wien has the most significant potential in passenger transport. Then following routes are A Prague-Berlin, B Prague-München, and D Brno-Katowice. Subsequently, the likely impacts generated by a significant improvement in the quality parameters and hence the competitive position of rail transport were assessed, including the potential for shifting part of the demand from the road and air transport to HSR. Overall, however, it can be stated that the potential impacts of the HSR on the growth of passenger transport in the Czech Republic will not be essential. To perceive the regional impacts of HSR construction, analyses of selected indicators (population density per km"jats:sup"2"/jats:sup", GDP per capita, unemployment rate) by NUTS 3 regions for the period 2007-2017 were also carried out. From the strategic point of view, the research results did not confirm that the planned construction of the HSR primarily stimulates convergence tendencies in regional development as the main priority of EU regional policy. Rather, it seems more likely that the HSR will stimulate the extraction of economic activity from “rural” regions in favour of metropolitan regions.

Document type: Article

The Impact of E-Commerce-Related Last-Mile Logistics on Cities: A Systematic Literature Review

Scipedia content — Mon, 15 Feb 2021 12:08:25 +0100

E-commerce-related last-mile logistics have a great impact on cities. Recent years have seen sustained growth in e-commerce in most developed countries, a trend that has only been reinforced by the COVID-19 pandemic. The perceived impact of this phenomenon varies depending upon the perspective of the players involved: individual members of the public, companies, or the public administrations. Tackling the issue from these perspectives, the goal of this article is to explore the kinds of impact this phenomenon has and will have. We use as the basis for their classification the so-called triple bottom line (TBL) of sustainability, encompassing people, planet, and profit; we complement this with the impact classification used by the European Science Foundation’s impact assessment working group. After performing a systematic review of the literature following PRISMA guidelines, our results show that, albeit to different degrees, the four impact dimensions analyzed (economic, social, environmental, and technological) have only received incipient coverage in the existing literature. Given its ever-growing importance, we believe that greater attention needs to be paid to this phenomenon, especially with regard to those aspects having the greatest impact upon urban systems and the different stakeholders involved. Only in this way can the public policies needed to mitigate these externalities be properly implemented.

Document type: Article

Sustainability of the Air Cargo Handling Process in the Context of Safety and Environmental Aspects

Scipedia content — Mon, 15 Feb 2021 12:08:41 +0100

In addition to passenger traffic, air cargo business is an important business for a global air transport industry. This means that Air Cargo Handling Process (ACHP) is important for any airport or cargo handling agent who provides cargo handling services. To qualitatively manage the ACHP, certain prerequisites must be met, such as competent cargo staff, procedures, cargo information system, infrastructure with enough capacity, and process management. The objective of research presented in this paper is ACHP and its complex structure but in the context of safety and sustainability. Using of several scientific methods of cognition, the authors research the structure of ACHP and safety, and ecological aspects of the process, too. The result of this research is the safety and environmental aspects of the process which are of significant importance for process functionality as well as for the quality level of service that meets customer requirements and to the sustainability of process. Results show that there is a significant impact of the environmental and safety aspects specific to particular activities in ACHP and that they affect the reliability and functionality of the whole process, its profitability, and competitiveness. This points to the need for ACHP to be viewed in context and to understand ACHP sustainability matters and sustainability components.

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An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

Scipedia content — Mon, 15 Feb 2021 12:09:38 +0100

n insufficient functional relationship between adjustment factors and saturation flow rate (SFR) in the U.S. Highway Capacity Manual (HCM) method increases an additional prediction bias. The error of SFR predictions can reach 8%&ndash

10%. To solve this problem, this paper proposes a comprehensive adjusted method that considers the effects of interactions between factors. Based on the data from 35 through lanes in Beijing and 25 shared through and left-turn lanes in Washington, DC, the interactions between lane width and percentage of heavy vehicles and proportion of left-turning vehicles were analyzed. Two comprehensive adjustment factor models were established and tested. The mean absolute percentage error (MAPE) of model 1 (considering the interaction between lane width and percentage of heavy vehicles) was 4.89% smaller than the MAPE of Chinese National Standard method (Standard Number is GB50647) at 13.64%. The MAPE of model 2 (considering the interaction between lane width and proportion of left-turning vehicles was 33.16% smaller than the MAPE of HCM method at 14.56%. This method could improve the accuracy of SFR prediction, provide support for traffic operation measures, alleviate the traffic congestion, and improve sustainable development of cities.

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Investigation of the frequency of free vibrations for pipelines with different physical and mechanical properties of the material

Scipedia content — Mon, 15 Feb 2021 12:11:04 +0100

This paper raises the question of a new approach to the dynamic calculation of thin-walled underground pipelines of large diameter, which is based on the application of the Vlasov-Novozhilov half-time theory of medium-bend shells, which ignores the M1 moments that bend the cylindrical shell in the longitudinal direction, since they are much smaller than the M2 moments that bend it in the transverse direction. The resolving equation for this approach is a homogeneous 4th-order differential equation that uses two boundary conditions at each end to solve it. The resulting equation takes into account the parameter of the longitudinal force, the value of the internal pressure, the coefficient of elastic resistance of the soil, the parameter of thinness, as well as the attached mass of the soil. Based on the data obtained from the derived formulas, the frequency characteristics of thin-walled underground pipelines of large diameter with different physical and mechanical properties are determined depending on the length of the element, as well as ground conditions. It is established that the minimum frequencies for the shell form of vibrations in various ground conditions are realized only for steel pipes, and for polyethylene and fiberglass pipes, depending on the coefficient of elastic resistance of the soil, they can be realized both in the rod and shell form. At the same time, using a dynamic stability criterion, derived expressions to determine the critical external pressure, taking into account the pipe length and the number of half waves in the cross section in which there is a constructive denial of the pipeline. Based on this expression, a formula for determining the critical depth of laying for thin-walled pipelines is obtained.

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A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems

Scipedia content — Mon, 15 Feb 2021 12:14:33 +0100

The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system have to be addressed and evaluated at a sufficient level of fidelity before implementation. Therefore, a collaborative system of systems modeling approach for UAM is presented. To quickly identify physical effects and cross-disciplinary influences of UAM, a pool of low-fidelity physical analysis components is developed and integrated into the Remote Component Environment (RCE) workflow engine. This includes, i. a., the disciplines of demand forecast, trajectory, vertiport, and cost modeling as well as air traffic flow and capacity management. The definition and clarification of technical interfaces require intensive cooperation between specialists with different areas of expertise. To reduce this communication effort, the Common Parametric Aircraft Configuration Schema (CPACS) is adapted and used as central data exchange format. The UAM system module is initially applied for a 24-hour simulation of three generic networks in Hamburg City. After understanding the basic system-level behavior, higher level analysis components and feedback loops must be integrated in the UAM system module for evaluation and optimization of explicit operating concepts. Document type: Article

Causes and Treatment Measures of Submarine Pipeline Free-Spanning

Scipedia content — Mon, 15 Feb 2021 12:16:38 +0100

Submarine pipelines, as arteries for offshore oil and gas transportation, play a particularly important role in the exploitation of offshore oil and gas resources. Since the world’s first submarine pipelines were laid in the Gulf of Mexico, numerous failures have been caused by pipeline free-spanning. This paper provides a review of the causes and treatment measures for the free span of submarine pipeline. Various factors cause the free span of submarine pipelines, including wave flow scouring, fluctuations in seabed topography, residual stress or thermal stress of pipelines, and human activities. The scour of the wave current is the main factor affecting free span; the research on sediment starting and equilibrium depth during scour is reviewed in-depth. For the span treatment of submarine pipelines, the main measures available at present include the re-digging trench burying, structural support, covering bionic water plants, and choke plate self-burying. For each, the principle, advantages, disadvantages, and research are discussed. This review provides a convenient resource for understanding the causes of submarine free-spanning pipelines and choosing suitable treatment measures.

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Gender-Responsive Public Transportation in the Dammam Metropolitan Region, Saudi Arabia

Scipedia content — Mon, 15 Feb 2021 12:17:04 +0100

The limited availability of public transportation in Saudi Arabia leads to an increased demand for private vehicles. An increase in using private cars does not meet the global sustainability goals, e.g., reducing energy consumption and improving the air quality. Road users should be encouraged to use sustainable mobility modes, particularly public transportation, equally accessible to both men and women However, women’s mobility has been somewhat limited and challenged in spatio-temporal terms, and partly due to socio-cultural barriers. This study attempts to understand the gender experience of a sample of public transport users and consider their aspirations and needs into daily mobility. A survey campaign (structured interviews and online questionnaires) was launched in the Dammam Metropolitan Region (DMR), taking four different types of respondents into account. The results suggest a predominant preference for taxis for shopping and leisure activities due to a poor public transport service, pivotally characterized by limited operational routes, hours, and infrastructure. This study ponders upon the adequacy of the supporting infrastructures and interior design of the public buses to women’s needs and compare them with global best practices. The results suggest that, due to the absence of a gender-responsive design and infrastructure, women are forced to use taxis, although privacy and a sense of insecurity often become concerns when traveling alone or with children. The study results allow future research to be expanded, considering women’s mobility patterns, needs, and embedded barriers by comparing the results with current transport policies, plans, and practices.

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Intelligent Driving Assistant Based on Road Accident Risk Map Analysis and Vehicle Telemetry

Scipedia content — Mon, 15 Feb 2021 12:17:39 +0100

Through the application of intelligent systems in driver assistance systems, the experience of traveling by road has become much more comfortable and safe. In this sense, this paper then reports the development of an intelligent driving assistant, based on vehicle telemetry and road accident risk map analysis, whose responsibility is to alert the driver in order to avoid risky situations that may cause traffic accidents. In performance evaluations using real cars in a real environment, the on-board intelligent assistant reproduced real-time audio-visual alerts according to information obtained from both telemetry and road accident risk map analysis. As a result, an intelligent assistance agent based on fuzzy reasoning was obtained, which supported the driver correctly in real-time according to the telemetry data, the vehicle environment and the principles of secure driving practices and transportation regulation laws. Experimental results and conclusions emphasizing the advantages of the proposed intelligent driving assistant in the improvement of the driving task are presented.

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Railway Polygonized Wheel Detection Based on Numerical Time-Frequency Analysis of Axle-Box Acceleration

Scipedia content — Mon, 15 Feb 2021 12:19:41 +0100

The increasing need for repairs of polygonized wheels on high-speed railways in China is becoming problematic. At high speeds, polygonized wheels cause abnormal vibrations at the wheel-rail interface that can be detected via axle-box accelerations. To investigate the quantitative relationship between axle-box acceleration and wheel polygonization in both the time and frequency domains and under high-speed conditions, a dynamics model was developed to simulate the vehicle-track coupling system and that considers both wheel and track flexibility. The calculated axle-box accelerations were analyzed by using the improved ensemble empirical mode decomposition and Wigner-Ville distribution time-frequency method. The numerical results show that the maximum axle-box accelerations and their frequencies are quantitatively related to the harmonic order and out-of-roundness amplitude of polygonized wheels. In addition, measuring the axle-box acceleration enables both the detection of wheel polygonization and the identification of the degree of damage.

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A Hybrid Approach for Turning Intention Prediction Based on Time Series Forecasting and Deep Learning

Scipedia content — Mon, 15 Feb 2021 12:20:28 +0100

At an intersection with complex traffic flow, the early detection of the intention of drivers in surrounding vehicles can enable advanced driver assistance systems (ADAS) to warn the driver in advance or prompt its subsystems to assess the risk and intervene early. Although different drivers show various driving characteristics, the kinematic parameters of human-driven vehicles can be used as a predictor for predicting the driver’s intention within a short time. In this paper, we propose a new hybrid approach for vehicle behavior recognition at intersections based on time series prediction and deep learning networks. First, the lateral position, longitudinal position, speed, and acceleration of the vehicle are predicted using the online autoregressive integrated moving average (ARIMA) algorithm. Next, a variant of the long short-term memory network, called the bidirectional long short-term memory (Bi-LSTM) network, is used to detect the vehicle’s turning behavior using the predicted parameters, as well as the derived parameters, i.e., the lateral velocity, lateral acceleration, and heading angle. The validity of the proposed method is verified at real intersections using the public driving data of the next generation simulation (NGSIM) project. The results of the turning behavior detection show that the proposed hybrid approach exhibits significant improvement over a conventional algorithm; the average recognition rates are 94.2% and 93.5% at 2 s and 1 s, respectively, before initiating the turning maneuver.

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Transferring Urban Mobility Studies in Tehran, Istanbul, and Cairo to Other Large MENA Cities: Steps toward Sustainable Transport

Scipedia content — Mon, 15 Feb 2021 12:20:55 +0100

The number of urban mobility studies and projects in the three large metropoles of the Middle East and North Africa (MENA) region, Tehran, Istanbul, and Cairo, is growing while other large cities do not enjoy a large share. It would be efficient for those other large cities to adapt the experiences, projects, and studies of Tehran, Istanbul, and Cairo to their own contexts. This paper can help facilitate that adaptation. It investigates the transferability and generalisability of the findings of a recent publication by the lead author on mobility choices in Tehran, Istanbul, and Cairo to some other large cities of more than one million inhabitants in the MENA region. The discussion provided here can provide decision-makers in the MENA region with guidance on how to utilise the findings from a recent study on Tehran/Istanbul/Cairo in their own contexts. T-tests were conducted to test the comparability of the three base cities with a sample 57 others with populations of over one million people. The results show that it would be possible to adapt the urban mobility studies of the three base megacities to 3 to 27 cities based on different criteria. Key suggestions identified by this study include providing local accessibility, neighbourhood facilities, and cycling facilities as well as removing social and legal constraints to cycling, advertising cycling, informing people about the harm arising from the overuse of cars, and increasing street connectivity by adding intersections. According to the findings, these evidence-based recommendations can enhance sustainable mobility for the inhabitants of up to 27 large cities.

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Corrigendum: A Systems Thinking Approach to Exploring the Influence of the Media on How Publics Engage With and Develop Dialogues Relating to Electric Vehicles

Scipedia content — Mon, 15 Feb 2021 12:21:45 +0100

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Design and Experimental Investigation of a Hybrid Rotor Permanent Magnet Modular Machine with 3D Flux Paths Accounting for Recyclability of Permanent Magnet Material

Scipedia content — Mon, 15 Feb 2021 12:25:32 +0100

Rare-earth metals used for manufacturing Permanent Magnets (PMs) remain classified as critical raw materials by the European Commission. In order to secure the supply of electrical machines due to the increasing demand of Hybrid and Full Electrical Vehicles ((H)EVs), recycling has emerged as a valuable alternative. Hence, this paper presents the concept of a modular PM machine with a hybrid rotor and 3D flux paths, for application in ((H)EVs). The proposed machine topology is intended to facilitate the extraction of PM material towards a recycling process. The selection of a machine for prototyping is carried out by investigating the effect of the variation of the number of rotor teeth and stator modules on various parameters, with models developed in Finite Element (FE). Finally, the models developed of the selected combination were validated with a detailed experimental evaluation of the prototype.

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Prospects of Electric Vehicles in the Developing Countries: A Literature Review

Scipedia content — Mon, 15 Feb 2021 12:26:19 +0100

Electric mobility offers a low cost of travel along with energy and harmful emissions savings. Nevertheless, a comprehensive literature review is missing for the prospects of electric vehicles in developing countries. Such an overview would be instrumental for policymakers to understand the barriers and opportunities related to different types of electric vehicles (EVs). Considering the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a systematic review was performed of the electronic databases Google Scholar and Web of Science for the years 2010–2020. The electric four-wheelers, hybrid electric vehicles and electric two-wheeler constituted the electric vehicles searched in the databases. Initially, 35 studies identified in the Web of Science that matched the criteria were studied. Later, 105 other relevant reports and articles related to barriers and opportunities were found by using Google Scholar and studied. Results reveal that electric four-wheelers are not a feasible option in developing countries due to their high purchase price. On the contrary, electric two-wheelers may be beneficial as they come with a lower purchase price.

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A Regression Tree Approach for Investigating the Impact of High Speed Rail on Tourists’ Choices

Scipedia content — Mon, 15 Feb 2021 12:28:13 +0100

This paper provides a contribution to the international literature by applying regression tree methods to the analysis of the expected effects of the High Speed Rail project in Italy on the tourism market. This approach, as far as the author knows, has never been applied in this context. Tourism and transport information have been gathered for 99 Italian provinces during the 2006&ndash

2016 period. Tree-structured methods have been chosen as an application of regression models in which some explanatory variables are used as covariates to predict the dependent variable values on the basis of some decision rules. This approach establishes a casual effect between dependent and independent variables. The dependent variables chosen are the Italian and foreign tourists, and the number of overnights spent by Italians and foreigners. Among the independent variables are the presence of HSR, the presence of first-level airport hubs and the number of operating bases of low-cost airlines

among the attractiveness variables are the GDP, the number of attractions in a given province, the presence of the sea, the population and the percentage of unemployment. The main outcome of this study is that HSR affects the tourism market.

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Taxi Demand Prediction Based on a Combination Forecasting Model in Hotspots

Scipedia content — Mon, 15 Feb 2021 12:29:18 +0100

Accurate taxi demand prediction can solve the congestion problem caused by the supply-demand imbalance. However, most taxi demand studies are based on historical taxi trajectory data. In this study, we detected hotspots and proposed three methods to predict the taxi demand in hotspots. Next, we compared the predictive effect of the random forest model (RFM), ridge regression model (RRM), and combination forecasting model (CFM). Thereafter, we considered environmental and meteorological factors to predict the taxi demand in hotspots. Finally, the importance of indicators was analyzed, and the essential elements were the time, temperature, and weather factors. The results indicate that the prediction effect of CFM is better than those of RFM and RRM. The experiment obtains the relationship between taxi demand and environment and is helpful for taxi dispatching by considering additional factors, such as temperature and weather.

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Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles

Scipedia content — Mon, 15 Feb 2021 12:29:36 +0100

The last mile travelling problem is the most challenging part when using public transit. This study designs a high-freedom responsive feeder transit (HFRFT) system to serve at the transfer station, given vehicle routes, departure time, and service area based on demand. The proposed feeder transit system employs a travelling mode with multitype vehicles. In order to improve the operation of the HFRFT system, the optimization design methods are suggested for vehicle routes, scheduling, and service area. A mixed integer programming model and its hybrid of a metaheuristic algorithm are proposed to efficiently and integrally solve the vehicle routes and scheduling parameters according to the reservation requirements. A heuristic method is proposed to optimize the service area based on the equilibrium of system supply and demand. Case studies show that the mixed running mode of multiple models can significantly improve the seat utilization, which can also significantly reduce the number of departures and the average travel distance per passenger. The proposed service area optimization method is proved to be feasible to improve the last mile travel.

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Multiclock Constraint System Modelling and Verification for Ensuring Cooperative Autonomous Driving Safety

Scipedia content — Mon, 15 Feb 2021 12:31:03 +0100

CADS (cooperative autonomous driving systems) are software-intensive and safety-critical reactive systems and give great promise to our daily life, but system errors may not be identified in the design stage until the implement stage, and the cost to correct them will be more expensive later than the early stage. For designing trustworthy autonomous software systems, we have to deal with multiclock constraint models. SysML (System Modeling Language) meets increasing adoption in order to carry out system-level modelling and verification against abstract representations, but it suffers from semantic ambiguities in the design of safety-critical autonomous systems. The main objective is to investigate methods for coping with the design and analysis models simultaneously and to achieve semantic consistency based on mathematical foundations and formal model transformation. In this paper, we propose a method to combine the requirement modelling process with analysis process together for CADS safety and reliability guarantee. Firstly, we extend SysML metamodels and construct SysML profile for the CADS domain that could improve modelling correctness and enhance reusability. An instantiated CADS model has been designed by means of adopting a profile containing different key functional and nonfunctional attributes and behaviors. Secondly, we define formal syntax and semantic notations for modelling elements in the SysML state machine diagram and show transformation rules between the state machine diagram and the CCSL (Clock Constraint Specification Language) model. Semantic preservation is also proved using the bisimulation relation between them for rigorous mapping correctness. Thirdly, a cooperative autonomous overtaking driving case study on the highway scenario is used for illustration, and we use the tool TimeSquare to simulate CCSL specification execution traces at the system design stage.

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Structural Behavior of Pipelines Buried in Expansive Soils under Rainfall Infiltration (Part I: Transverse Behavior)

Scipedia content — Mon, 15 Feb 2021 12:32:18 +0100

Landslides, fault movements as well as shrink/swell soil displacements can exert important additional loadings on soil buried structures such as pipelines. These loadings may damage the buried structures whenever they reach the strength limits of the structure material. This paper presents a two-dimensional plane-strain finite element analysis of an 800 mm diameter water supply pipeline buried within the expansive clay of the Ain-Tine area (Mila, Algeria), considering the unsaturated behavior of the soil under a rainfall infiltration of 4 mm/day intensity and which lasts for different time durations (8, 15 and 30 days). The simulations were carried out using the commercial software module SIGMA/W and considering different initial soil suction conditions P1, P2, P3 and P4. The soil surface heave and the radial induced forces on the pipeline ring (i.e., Axial , Shear forces and bending moments ) results indicated that following the changes of suction the rainfall infiltration can cause considerable additional loads on the buried pipeline. Moreover, these loads are proportionally related to the initial soil suction conditions as well as to the rainfall infiltration time duration. The study highlighted that the unsaturated behavior of expansive soils because of their volume instability are very sensitive to climatic conditions and can exert adverse effects on pipelines buried within such soils. As a result, consistent pipeline design should seriously consider the study of the effect of the climatic conditions on the overall stability of the pipeline structure.

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Train Type Identification at S&C

Scipedia content — Mon, 15 Feb 2021 12:32:52 +0100

The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such system requires a robust and efficient train type identification. Given the complex and unique dynamical response of any vehicle track interaction, the machine learning was chosen as a suitable tool. For design and validation of the system, real on-site acceleration data were used. The resulting theoretical and practical challenges are discussed.

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Development of Micro-Mobility Based on Piezoelectric Energy Harvesting for Smart City Applications

Scipedia content — Mon, 15 Feb 2021 12:33:17 +0100

This study investigates the use of an alternative energy source in the production of electric energy to meet the increasing energy requirements, encourage the use of clean energy, and thus reduce the effects of global warming. The alternative energy source used is a mechanical energy by piezoelectric material, which can convert mechanical energy into electrical energy, that can convert mechanical energy from pressure forces and vibrations during activities such as walking and traveling into electrical energy. Herein, a pilot device is designed, involving the modification of a bicycle into a stationary exercise bike with a piezoelectric generator, to study energy conversion and storage generated from using the bike. Secondly, the piezoelectric energy harvesting system is used on bicycles as a micro-mobility, light electric utility vehicle with smart operation, providing a novel approach to smart city design. The results show that the energy harvested from the piezoelectric devices can be stored in a 3200 mAh, 5 V battery and power sensors on the bicycle. Moreover, 13.6 mW power can be generated at regular cycling speed, outputting 11.5 V and 1.2 mA. Therefore, the piezoelectric energy harvesting system has sufficient potential for application as a renewable energy source that can be used with low power equipment.

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The Challenge of Transdisciplinary Research: A Case Study of Learning by Evaluation for Sustainable Transport Infrastructures

Scipedia content — Mon, 15 Feb 2021 12:34:38 +0100

While transdisciplinary (TD) research is desired in order to solve real world sustainability issues, this may be challenging for both academic and non-academic participants. Supporting learning through evaluation, we analyzed a project aiming at sustainable transport infrastructures. After developing a TD research framework as a benchmark, two external independent evaluators interviewed all project researchers, representatives for end-users, and donors. The evaluators compared results with the framework, and evaluators and participants critically reflected on the results together. There were three inconsistencies relative to the framework: (1) limited understanding of TD research among project management, end-users, and most of the researchers; (2) no structured learning process among end-users; instead, they expressed very diverse opinions about what they expected from the project; (3) project leaders had limited understanding of the special challenges of TD research, did not fully understand the status of the project’s social system, and thus did not act as facilitators of the required collaborative learning process. Non-academic participants saw themselves as customers and not as partners in the knowledge production process. We conclude that TD problem-solving research requires much time and needs facilitation and training. A preparatory phase with a lower level of funding would be helpful in preparing for TD processes.

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Control of air flow temperature and pressure in the pipelines with PID

Scipedia content — Fri, 12 Feb 2021 12:51:32 +0100

Today, the use of proportional-integral-derivative (PID) control units continues in many control applications due to their simple structure. In areas such as pressure, temperature, flow control, PID control element is used and many new methods are applied in adjusting control parameters. In this study, the LTR 701 Controlled Airflow and Temperature Experimental System was used to study the temperature and pressure control at different flow rates in the pipelines. In this control system, temperature was controlled with PID control element, pressure was controlled with PI control element, and reaction of control parameters at different temperatures and pressures were investigated. Also, temperature was controlled as cascade with PI element in elementary controller and P element in secondary controller. The manual adjustment method has been applied to adjust the control parameters. In addition, the experimental system is modelled in MATLAB-SIMULINK. On this model, simulation results showed that it is matching the experimental results.

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Sustainable Transport Infrastructure and Economic Returns: A Bibliometric and Visualization Analysis

Scipedia content — Mon, 22 Mar 2021 19:14:51 +0100

Sustainable transport infrastructure can determine the effect of countries&rsquo

transport-driven economic returns. Considering the economic, environmental, and social relevance and growing issues of CO 2 in the countries concerned, this study aims to examine sustainable transport infrastructure related to economic return through a bibliometric and visualization analysis from 2000 to 2019. First, to measure the status of sustainable transport infrastructure literature, we determine the number of publications produced per year. Second, we determine the most frequently cited articles and prominent journals on sustainable transport infrastructure. Third, we examine the co-occurrence of the author&rsquo

s keywords below the abstract. Fifth, we describe the bibliometric details in clusters and analyze the network link between reference, sources, and authors&rsquo

co-citations, and discuss the characteristics and structures of clusters. Sixth, we discuss the bibliographic relationship between authors, and finally, determine the country and the institutional network of co-authors. The obtained results identify that the most influential articles, journals, and authors that make a significant contribution to sustainable transport infrastructure studies and present the research sub-areas or themes related to sustainable transport infrastructure. Overall, the study found the paradigms of today, key research areas, and the link between the fields of sustainable transport infrastructure studies. In the meantime, this study also reveals the improvements in the main topics and sub-sections over the last 20 years and shows the changes in future areas of research. The study concluded that the findings could provide researchers with some insights and help to advance studies on sustainable transport systems.

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Welfare consequences of request stops at transport services with low demand

Scipedia content — Mon, 22 Mar 2021 19:15:31 +0100

Background Demand-responsive transport is an alternative to fixed-route, fixed-scheduled transport services in low-demand areas. Objective This paper discusses the welfare and distributional consequences of the implementation of request stops (RSs) on a scheduled fixed-stop transport service. Method The discussion is based on a general welfare model. The focus is on discussing how the magnitudes of the welfare effects on different groups of travellers are influenced by travel patterns and the characteristics of the travellers involved. Results The effects of implementing RSs are critically dependent on the booking procedure, the variation in demand throughout the day, and the travellers’ time values per hour when on the mode and when arriving at the destinations before having any appointments. Moreover, the benefits for the operators and the authorities depend strongly on the risk profile in the tendering contract.

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Fuel Economy of Plug-In Hybrid Electric and Hybrid Electric Vehicles: Effects of Vehicle Weight, Hybridization Ratio and Ambient Temperature

Scipedia content — Mon, 22 Mar 2021 19:16:24 +0100

Hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are evolving rapidly since the introduction of Toyota Prius into the market in 1997. As the world needs more fuel-efficient vehicles to mitigate climate change, the role of HEVs and PHEVs are becoming ever more important. While fuel economies of HEVs and PHEVs are superior to those of internal combustion engine (ICE) powered vehicles, they are partially powered by batteries and therefore they resemble characteristics of battery electric vehicles (BEVs) such as dependence of fuel economy on ambient temperatures. It is also important to understand how different extent of hybridization (a.k.a., hybridization ratio) affects fuel economy under various driving conditions. In addition, it is of interest to understand how HEVs and PHEVs compare with BEVs at a similar vehicle weight. This study investigated the relationship between vehicle mass and vehicle performance parameters, mainly fuel economy and driving range of PHEVs focused on 2018 and 2019 model years using the test data available from fuel economy website of the US Environmental Protection Agency (EPA). Previous studies relied on modeling to understand mass impact on fuel economy for HEV as there were not enough number of HEVs in the market to draw a trendline at the time. The study also investigated the effect of ambient temperature for HEVs and PHEVs and kinetic energy recovery of the regenerative braking using the vehicle testing data for model year 2013 and 2015 from Idaho National Lab (INL). The current study assesses current state-of-art for PHEVs. It also provides analysis of experimental results for validation of vehicle dynamic and other models for PHEVs and HEVs.

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An ETA Prediction Model for Intermodal Transport Networks Based on Machine Learning

Scipedia content — Mon, 22 Mar 2021 19:19:12 +0100

"jats:p"Transparency in transport processes is becoming increasingly important for transport companies to improve internal processes and to be able to compete for customers. One important element to increase transparency is reliable, up-to-date and accurate arrival time prediction, commonly referred to as estimated time of arrival (ETA). ETAs are not easy to determine, especially for intermodal freight transports, in which freight is transported in an intermodal container, using multiple modes of transportation. This computational study describes the structure of an ETA prediction model for intermodal freight transport networks (IFTN), in which schedule-based and non-schedule-based transports are combined, based on machine learning (ML). For each leg of the intermodal freight transport, an individual ML prediction model is developed and trained using the corresponding historical transport data and external data. The research presented in this study shows that the ML approach produces reliable ETA predictions for intermodal freight transport. These predictions comprise processing times at logistics nodes such as inland terminals and transport times on road and rail. Consequently, the outcome of this research allows decision makers to proactively communicate disruption effects to actors along the intermodal transportation chain. These actors can then initiate measures to counteract potential critical delays at subsequent stages of transport. This approach leads to increased process efficiency for all actors in the realization of complex transport operations and thus has a positive effect on the resilience and profitability of IFTNs.

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A Novel RC-Based Architecture for Cell Equalization in Electric Vehicles

Scipedia content — Mon, 22 Mar 2021 19:19:56 +0100

Nowadays, research on electric vehicles is increasing because they have the potential to decrease greenhouse-gas emissions dramatically in the transport sector. For these types of vehicles, the battery is one of the main components. The traction system needs a cell series connection to fulfill the energy requirements. Nevertheless, batteries differ from each other due to a normal dispersion in their capacity, internal resistance, and self-discharge rate. This paper presents a novel battery equalizer circuit using an RC-based topology to equalize two adjacent cells of a battery pack. It has the advantage of merging a resistor-based equalizer, a capacitor-based equalizer, and an RC-based equalizer in one circuit. In this way, it is possible to limit the current stress in the components of the circuit. The proposed method increases the equalization time by 35% for a threshold current of 4 A. However, it is possible design the system for another threshold current. Finally, the complexity of the controller is not compromised in the proposed architecture. The operation, analysis, and design of the architecture are presented and compared to the classic schemes. The theoretical analysis is validated through simulation results.

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Environmental Sustainability in City Logistics Measures

Scipedia content — Mon, 22 Mar 2021 19:20:40 +0100

Sustainable urban transport is fundamental not only for economic growth but also for the environmental protection, thus all logistics activities within the cities should be organized in a way to be environmentally friendly. The article aims at presenting the environmental sustainability of city logistics measures from different stakeholder perspectives. In the paper, a multi-method approach was implemented: literature review, text analysis, text mining, and statistical analysis. The paper presents how the stakeholders perceive urban logistics, if they see the need for coordination of its elements, who should be responsible for it, and what areas are the most important for them. The main task of this study is to recognize the priorities of different stakeholders. In consequence, the final effect of this article is an insight that is valuable not only for the local authorities but for many stakeholders, groups operating within the city that are and in many cases cooperating within the framework of creating sustainable urban mobility plans.

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A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)

Scipedia content — Mon, 22 Mar 2021 19:25:01 +0100

The deployment of solar photovoltaics (PV) and electric vehicles (EVs) is continuously increasing during urban energy transition. With the increasing deployment of energy storage, the development of the energy sharing concept and the associated advanced controls, the conventional solar mobility model (i.e., solar-to-vehicles (S2V), using solar energy in a different location) and context are becoming less compatible and limited for future scenarios. For instance, energy sharing within a building cluster enables buildings to share surplus PV power generation with other buildings of insufficient PV power generation, thereby improving the overall PV power utilization and reducing the grid power dependence. However, such energy sharing techniques are not considered in the conventional solar mobility models, which limits the potential for performance improvements. Therefore, this study conducts a systematic review of solar mobility-related studies as well as the newly developed energy concepts and techniques. Based on the review, this study extends the conventional solar mobility scope from S2V to solar-to-buildings, vehicles and storage (S2BVS). A detailed modeling of each sub-system in the S2BVS model and related advanced controls are presented, and the research gaps that need future investigation for promoting solar mobility are identified. The aim is to provide an up-to-date review of the existing studies related to solar mobility to decision makers, so as to help enhance solar power utilization, reduce buildings’ and EVs’ dependence and impacts on the power grid, as well as carbon emissions.

Document type: Article

An Approach for Handling Uncertainties Related to Behaviour and Vehicle Mixes in Traffic Simulation Experiments with Automated Vehicles

Scipedia content — Mon, 22 Mar 2021 19:26:47 +0100

The introduction of automated vehicles is expected to affect traffic performance. Microscopic traffic simulation offers good possibilities to investigate the potential effects of the introduction of automated vehicles. However, current microscopic traffic simulation models are designed for modelling human-driven vehicles. Thus, modelling the behaviour of automated vehicles requires further development. There are several possible ways to extend the models, but independent of approach a large problem is that the information available on how automated vehicles will behave is limited to todays partly automated vehicles. How future generations of automated vehicles will behave will be unknown for some time. There are also large uncertainties related to what automation functions are technically feasible, allowed, and actually activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. This article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. The driving logics are also linked to assumptions on which logic that could operate in which environment at which part of the transition period. Simulation results for four different types of road facilities are also presented to illustrate potential effects on traffic performance of the driving logics. The simulation results show large variations in throughput, from large decreases to large increases, depending on driving logic and penetration rate. "p"Funding Agencies|European UnionEuropean Union (EU) [H2020-ART-2016-2017, 723201]

Document type: Article

Public Transport Quality, Safety, and Perceived Accessibility

Scipedia content — Mon, 22 Mar 2021 19:28:14 +0100

Service quality in public transport is proposed as a key determinant of perceived accessibility, the ease to live the life one wants with the help of the transport system, as low service quality may be a barrier for use, decreasing the ease to participate in daily activities. The first aim was to validate the direct relationship between public transport quality and perceived accessibility. Secondly, we analyzed the mediating role of safety perceptions to better explain the link between service quality and perceived accessibility. Public transport travelers (n = 4944) from five northern European cities were surveyed. Results from PLS-SEM modeling show that service quality has a significant and direct relationship with perceived accessibility, especially regarding functionality. An indirect relationship through travel safety perceptions was also observed, highlighting information and comfort as main drivers. High car use, low public transport use, increasing age, and being a woman were also associated with greater perceived accessibility. City comparisons yielded a number of significant differences. Our results contribute to the research literature by highlighting the importance of service quality in public transport for perceptions of accessibility in daily travel. In particular, we argue that functionality is the core attribute to focus on, and that attributes related to travel safety perceptions should be carefully considered when planning for sustainable transport.

Document type: Article

Initial Rotor Position Detection for Permanent Magnet Synchronous Motor Based on High-Frequency Voltage Injection without Filter

Scipedia content — Mon, 22 Mar 2021 19:30:10 +0100

The accurate initial rotor position of a permanent magnet synchronous motor (PMSM) is necessary for starting the motor, and for the position sensorless control method adopted by a PMSM control system under some working conditions. This paper presents a new method to detect the initial rotor position of a permanent magnet synchronous motor (PMSM). The method does not need a low-pass filter, and has strong robustness and a simple calculation method. According to the relationship between high-frequency current response and rotor position angle θ, the rotor position angle can be obtained by arctangent and linear formulae. Finally, the magnetic polarity of the rotor is distinguished according to the change of inductance. In this method, the arctangent function is used to eliminate the filtering process and reduce the influence of the parameter deviation of the motor system on the detection accuracy of the initial position. The experimental results verify the correctness of the theoretical analysis and the effectiveness of the method.

Document type: Article

Pedidos y transporte: Una unidad estratégica de estudio en indicadores logísticos de la nueva era

Scipedia content — Mon, 22 Mar 2021 19:34:27 +0100

La presente investigación tiene como objetivo analizar las tendencias principales que comprende los pedidos y el transporte, para ello se ha considerado como referencia tres fuentes de análisis: 1) Investigación de Campo, en el sector comercial de la zona 3 del Ecuador. 2) Análisis gráfico descriptivo del mercado 3) Análisis estadístico inferencial mediante la prueba de Friedman. La metodología se enmarcó en un análisis descriptivo explicativo, el instrumento de investigación fue una encuesta aplicado a una muestra conformada de 373 empresas comerciales. Los resultados obtenidos reflejaron un nivel de significancia asintótica de 0.092 mediante la prueba de Friedman para las variables consideradas en comparación con el nivel crítico de 0.05 por lo cual se indica que no hay diferencias estadísticas significativas entre las empresas en relación a las dimensiones pedidos y transporte en las 4 provincias seleccionadas.

Document type: Article

Revisiting Accessibility in a Context of Sustainable Transport: Capabilities and Inequalities in Bogotá

Scipedia content — Mon, 22 Mar 2021 19:37:51 +0100

This research sets out to examine the interaction between accessibility, social inequalities and sustainability by revisiting a well-documented case of inequalities in access in Global South cities: Bogotá

. Our analysis builds on the concept of accessibility, focusing on the role of transport as an enabler of opportunities for social interactions, healthcare and leisure, which are essential to the full participation in society. The research applies a methodological framework for accessibility developed and tested in the Latin American context, though it has not been previously applied to non-commuting travel. Our paper contributes to the existing evidence base showing the relevance of non-commuting travel to sustainable transport assessment in contexts of high inequality, which can be scaled up and applied in other contexts with various levels of social and environmental inequalities. The empirical analysis is based on data from Bogotá

&rsquo

s household travel survey. Using this dataset, we measure accessibility using a gravitational type of metric that is calibrated based on observed travel behavior. Accessibility levels were estimated by car and public transport for every zonal planning unit in the Bogotá

Region. Accessibility indices are analyzed from an equity perspective using metrics such as the Palma ratio for differences of income and socioeconomic positions. Results show that on average, low- and middle-income areas have higher accessibility than high-income areas by both private and public transport. Accessibility conditions are discussed considering a framework of transitions to sustainable urban mobility, reflecting on various drivers and consequences of barriers to access in different areas and social groups. Our findings provide insights to support actions that redistribute accessibility of opportunities beyond the job market, questioning the applicability of accessibility measures to discuss equity and sustainability in cities such as Bogotá

Document type: Article

Analysis of Factors Affecting the Severity of Automated Vehicle Crashes Using XGBoost Model Combining POI Data

Scipedia content — Mon, 22 Mar 2021 19:38:21 +0100

The research and development of autonomous vehicle (AV) technology have been gaining ground globally. However, a few studies have performed an in-depth exploration of the contributing factors of crashes involving AVs. This study aims to predict the severity of crashes involving AVs and analyze the effects of the different factors on crash severity. Crash data were obtained from the AV-related crash reports presented to the California Department of Motor Vehicles in 2019 and included 75 uninjured and 18 injured accident cases. The points-of-interest (POI) data were collected from Google Map Application Programming Interface (API). Descriptive statistics analysis was applied to examine the features of crashes involving AVs in terms of collision type, crash severity, vehicle movement preceding the collision, and degree of vehicle damage. To compare the classification performance of different classifiers, we use two different classification models: eXtreme Gradient Boosting (XGBoost) and Classification and Regression Tree (CART). The result shows that the XGBoost model performs better in identifying the injured crashes involving AVs. Compared with the original XGBoost model, the recall and G-mean of the XGBoost model combining POI data improved by 100% and 11.1%, respectively. The main features that contribute to the severity of crashes include weather, degree of vehicle damage, accident location, and collision type. The results indicate that crash severity significantly increases if the AVs collided at an intersection under extreme weather conditions (e.g., fog and snow). Moreover, an accident resulting in injuries also had a higher probability of occurring in areas where land-use patterns are highly diverse. The knowledge gained from this research could ultimately contribute to assessing and improving the safety performance of the current AVs.

Document type: Article

Bottleneck Based Gridlock Prediction in an Urban Road Network Using Long Short-Term Memory

Scipedia content — Mon, 22 Mar 2021 19:38:51 +0100

The traffic bottlenecks in urban road networks are more challenging to investigate and discover than in freeways or simple arterial networks. A bottleneck indicates the congestion evolution and queue formation, which consequently disturb travel delay and degrade the urban traffic environment and safety. For urban road networks, sensors are needed to cover a wide range of areas, especially for bottleneck and gridlock analysis, requiring high installation and maintenance costs. The emerging widespread availability of GPS vehicles significantly helps to overcome the geographic coverage and spacing limitations of traditional fixed-location detector data. Therefore, this study investigated GPS vehicles that have passed through the links in the simulated gridlock-looped intersection area. The sample size estimation is fundamental to any traffic engineering analysis. Therefore, this study tried a different number of sample sizes to analyze the severe congestion state of gridlock. Traffic condition prediction is one of the primary components of intelligent transportation systems. In this study, the Long Short-Term Memory (LSTM) neural network was applied to predict gridlock based on bottleneck states of intersections in the simulated urban road network. This study chose to work on the Chula-Sathorn SUMO Simulator (Chula-SSS) dataset. It was calibrated with the past actual traffic data collection by using the Simulation of Urban MObility (SUMO) software. The experiments show that LSTM provides satisfactory results for gridlock prediction with temporal dependencies. The reported prediction error is based on long-range time dependencies on the respective sample sizes using the calibrated Chula-SSS dataset. On the other hand, the low sampling rate of GPS trajectories gives high RMSE and MAE error, but with reduced computation time. Analyzing the percentage of simulated GPS data with different random seed numbers suggests the possibility of gridlock identification and reports satisfying prediction errors.

Document type: Article

Collective Risk Ranking of Highway Segments on the Basis of Severity-Weighted Crash Rates

Scipedia content — Mon, 22 Mar 2021 19:39:50 +0100

This study is intended to focus on the major factors affecting traffic crash rates and severity levels, in addition to identifying crash-prone locations (i.e., black spots) based on the two indicators. The available crash data for different road segments used for the analysis were obtained from the Washington state database provided by the Highway Safety Information System (HSIS) for the years 2006 to 2011. A Random Forest (RF) classifier was used to predict the outcome level of crash severity, while crash rates were predicted by applying RF regressor. Certain features were selected for each model besides the abstraction of new features to check if there are unobserved correlations affecting the independent variables, such as accounting for the number and weight of crashes within 1 km2 area by implementing the Getis-Ord Gi∗ index. Moreover, to calculate the collective risk (CR) score, crash rates were adjusted to incorporate crash severity weights (cost per severity type) and regression-to-the-mean (RTM) bias via Empirical Bayes (EB) method. Finally, segments were ranked according to their CR score.

Document type: Article

Risk Prediction for Ship Encounter Situation Awareness Using Long Short-Term Memory Based Deep Learning on Intership Behaviors

Scipedia content — Mon, 22 Mar 2021 19:41:48 +0100

Encounter risk prediction is critical for safe ship navigation, especially in congested waters, where ships sail very near to each other during various encounter situations. Prior studies on the risk of ship collisions were unable to address the uncertainty of the encounter process when ignoring the complex motions constituting the dynamic ship encounter behavior, which may seriously affect the risk prediction performance. To fill this gap, a novel AIS data-driven approach is proposed for ship encounter risk prediction by modeling intership behavior patterns. In particular, multidimensional features of intership behaviors are extracted from the AIS trace data to capture spatial dependencies between encountering ships. Then, the challenging task of risk prediction is to discover the complex and uncertain relationship between intership behaviors and future collision risk. To address this issue, we propose a deep learning framework. To represent the temporal dynamics of the encounter process, we use the sliding window technique to generate the sequences of behavioral features. The collision risk level at a future time is taken as the class label of the sequence. Then, the long short-term memory network, which has a strong ability to model temporal dependency and complex patterns, is extended to establish the relationship. The benefit of our approach is that it transforms the complex problem for risk prediction into a time series classification task, which makes collision risk prediction reliable and easier to implement. Experiments were conducted on a set of naturalistic data from various encounter scenarios in the South Channel of the Yangtze River Estuary. The results show that the proposed data-driven approach can predict future collision risk with high accuracy and efficiency. The approach is expected to be applied for the early prediction of encountering ships and as decision support to improve navigation safety.

Document type: Article

Experimental and Numerical Analyses on Mixing Uniformity of Water and Saline in Pipe Flow

Scipedia content — Mon, 22 Mar 2021 19:46:59 +0100

Liquid—liquid mixing is commonly observed in many applications such as the chlorination of water supplies and the agricultural fertigation. In order to study the mixing law of water-chlorine or water-fertilizer in a turbulent pipeline, saline was selected as a tracer injected into the pipeline. In this paper, the computational fluid dynamics (CFD) software was employed to study flow fields in water-saline pipelines. Four variates (mixing ratio "i"δ"/i", pipe diameter "i"D"/i", volume flow rate in the main pipe "i"Q, "/i"saline density "i"ρ"sub"s"/sub""/i") were considered to investigate the effects of multiple variates on mixing uniformity. The coefficient of variation (COV) was selected as the evaluation index of mixing uniformity, effective mixing length ("i"L"sub"EML"/sub""/i", the distance from the saline inlet to the fully mixed position) was chosen to quantitatively analyze the fully mixed position of water and saline in pipelines. The results of this numerical model agree well with experimental measurements and it shows that this model can effectively predict the concentration field of water and saline in the pipeline. Based on the experimental and simulated results, it was found that for the fixed mixing ratio, saline density and volume flow rate, the values of "i"L"sub"EML"/sub""/i" increased significantly with increasing pipe diameters. Furthermore, dimensional analysis (D-A) was adopted to examine the influences of the four variates on "i"L"sub"EML"/sub""/i", and their correlation coefficient of the curve-fitting equation was calculated to be 0.996.

Document type: Article

An Adaptive Approach for Multi-National Vehicle License Plate Recognition Using Multi-Level Deep Features and Foreground Polarity Detection Model

Scipedia content — Mon, 22 Mar 2021 19:49:34 +0100

License plate recognition system (LPR) plays a vital role in intelligent transport systems to build up smart environments. Numerous country specific methods have been proposed successfully for an LPR system, but there is a need to find a generalized solution that is independent of license plate layout. The proposed architecture is comprised of two important LPR stages: (i) License plate character segmentation (LPCS) and (ii) License plate character recognition (LPCR). A foreground polarity detection model is proposed by using a Red-Green-Blue (RGB) channel-based color map in order to segment and recognize the LP characters effectively at both LPCS and LPCR stages respectively. Further, a multi-channel CNN framework with layer aggregation module is proposed to extract deep features, and support vector machine is used to produce target labels. Multi-channel processing with merged features from different-level convolutional layers makes output feature map more expressive. Experimental results show that the proposed method is capable of achieving high recognition rate for multinational vehicles license plates under various illumination conditions.

Document type: Article

Data for Heuristic Optimization of Electric Vehicles’ Charging Configuration Based on Loading Parameters

Scipedia content — Mon, 22 Mar 2021 19:53:05 +0100

This dataset includes multiple files related to optimization of electric vehicles to minimize overloading in low voltage grids by varying the locations available to charge the EVs. The data include lognormally sampled hourly sorted scenarios across 11 charging locations for a stochastics-based Monte Carlo simulation. This simulation runs through 2 million scenarios based on actual probabilities to incorporate most possible situations. It also includes samples from normally distributed household electricity use scenarios based on agent-based modeling. The article includes the test grid parameters for simulation, which were used to create a benchmark grid in DigSilent Powerfactory software, as well as intermediate outputs defining worst case scenarios when electric vehicles were charged and results from three different optimization approaches involving a reduction in voltage drops, cable overloading and total line losses. The outputs from the benchmark grid were used to train a machine learning algorithm, the weights and codes for which are also attached. This trained network acted as the grid for subsequent iterative optimization procedures. Outputs are presented as a comparison between pre-optimization and post-optimization scenarios. The above dataset and procedure were repeated while varying the number of EVs between 0 and 100 in increments of 20, data for which are also attached. The data article supports a related submission titled “Minimization of Overloading Caused by Electric Vehicle (EV) Charging in Low Voltage Networks”.

Document type: Article

A Study on Public Adoption of Robo-Taxis in China

Scipedia content — Mon, 22 Mar 2021 19:59:06 +0100

Autonomous vehicles (AVs) have been reported to improve road safety, reduce traffic congestion, and increase urban mobility. However, the high price of AVs is currently a challenge for most consumers. Robo-taxi services, with ride-sharing services and AVs, are regarded as a good approach to solving this problem. As some companies have started testing Robo-taxis on the actual road, it has become important to investigate public adoption of Robo-taxi services before they are more widely introduced to the market. This study aims to explain and predict users’ acceptance of Robo-taxis by extending the Technology Acceptance Model by including the construct of social influence. Data were collected from an online survey in China and analyzed using linear regression models. The results indicate that perceived usefulness, perceived ease of use, and social influence have significant positive correlations with people’s behavior intentions to use Robo-taxis. Perceived ease of use further has an indirect effect on intention to use via perceived usefulness. The results of this study can serve as good references for policymakers, operators, and future transport researchers.

Document type: Article

Does Information on Automated Driving Functions and the Way of Presenting It before Activation Influence Users’ Behavior and Perception of the System?

Scipedia content — Mon, 22 Mar 2021 20:01:15 +0100

Information on automated driving functions when automation is not activated but is available have not been investigated thus far. As the possibility of conducting non-driving related activities (NDRAs) is one of the most important aspects when it comes to perceived usefulness of automated cars and many NDRAs are time-dependent, users should know the period for which automation is available, even when not activated. This article presents a study (N = 33) investigating the effects of displaying the availability duration before&mdash

versus after&mdash

activation of the automation on users&rsquo

activation behavior and on how the system is rated. Furthermore, the way of addressing users regarding the availability on a more personal level to establish &ldquo

sympathy&rdquo

with the system was examined with regard to acceptance, usability, and workload. Results show that displaying the availability duration before activating the automation reduces the frequency of activations when no NDRA is executable within the automated drive. Moreover, acceptance and usability were higher and workload was reduced as a result of this information being provided. No effects were found with regard to how the user was addressed.

Document type: Article

Artificial Neural Networks to Estimate the Influence of Vehicular Emission Variables on Morbidity and Mortality in the Largest Metropolis in South America

Scipedia content — Mon, 22 Mar 2021 20:02:34 +0100

The emission of pollutants from vehicles is presented as a prime factor deteriorating air quality. Thus, seeking public policies encouraging the use and the development of more sustainable vehicles is paramount to preserve populations&rsquo

health. To better understand the health risks caused by air pollution and exclusively by mobile sources urges the question of which input variables should be considered. Therefore, this research aims to estimate the impacts on populations&rsquo

health related to road transport variables for Sã

o Paulo, Brazil, the largest metropolis in South America. We used three Artificial Neural Networks (ANN) (Multilayer Perceptron&mdash

MLP, Extreme Learning Machines&mdash

ELM, and Echo State Neural Networks&mdash

ESN) to estimate the impacts of carbon monoxide, nitrogen oxides, ozone, sulfur dioxide, and particulate matter on outcomes for respiratory diseases (morbidity&mdash

hospital admissions and mortality). We also used unusual inputs, such as road vehicles fleet, distributed and sold fuels amount, and vehicle average mileage. We also used deseasonalization and the Variable Selection Methods (VSM) (Mutual Information Filter and Wrapper). The results showed that the VSM excluded some variables, but the best performances were reached considering all of them. The ELM achieved the best overall results to morbidity, and the ESN to mortality, both using deseasonalization. Our study makes an important contribution to the following United Nations Sustainable Development Goals: 3&mdash

good health and well-being, 7&mdash

affordable and clean energy, and 11&mdash

sustainable cities and communities. These research findings will guide government about future legislations, public policies aiming to warranty and improve the health system.

Document type: Article

Project O2 - Macroscopic Fundamental Diagram Based Discrete Transportation Network Design

Scipedia content — Mon, 22 Mar 2021 20:07:21 +0100

The presence of demand uncertainty brings challenges to network design problems (NDP), because fluctuations in origin-destination (OD) demand have a prominent effect on the corresponding total travel time, which is usually adopted as an index to evaluate the network design problem. Fortunately, the macroscopic fundamental diagram (MFD) has been proved to be a property of the road network itself, independent of the origin-destination demand. Such characteristics of an MFD provide a new theoretical basis to assess the traffic network performance and further appraise the quality of network design strategies. Focusing on improving network capacity under the NDP framework, this paper formulates a bi-level programming model, where at the lower level, flows are assigned to the newly extended network subject to user equilibrium theory, and the upper level determines which links should be added to achieve the maximum network capacity. To solve the proposed model, we design an algorithm framework, where traffic flow distribution of each building strategy is calculated under the dynamic user equilibrium (DUE), and updated through the VISSIM-COM-Python interaction. Then, the output data are obtained to shape MFDs, and "jats:italic"k"/jats:italic"-means clustering algorithm is employed to quantify the MFD-based network capacity. Finally, the methodology is implemented in a test network, and the results show the benefits of using the MFD-based method to solve the network design problem under stochastic OD demands. Specifically, the capacity paradox is also presented in the test results.

Document type: Article

Effect of Synthetic Fibers and Hydrated Lime in Porous Asphalt Mixture Using Multi-Criteria Decision-Making Techniques

Scipedia content — Mon, 22 Mar 2021 20:19:22 +0100

Porous asphalt is a type of mixture characterized by having high air void percentages that offers multiple benefits when used in wearing courses in terms of driving safety, water flow management, and noise reduction. However, the durability of porous asphalt (PA) mixtures is significantly shorter when compared to dense-graded asphalt mixtures. This study investigated the impact of polyolefin-aramid fibers and hydrated lime in the functional and mechanical performance of porous asphalt mixtures. A parametric study based on the concept of design of experiments was carried out through the Taguchi methodology. Accordingly, an experimental design was conducted based on the L18 full factorial orthogonal array. Three control factors-fiber content, binder content, and filler type- were included at various levels, and multiple responses including total air voids, interconnected air voids, particle loss in dry conditions, particle loss in wet conditions, and binder drainage were assessed experimentally. Signal-to-noise ratios were calculated to determine the optimal solution levels for each control factor for the multiple responses. In the second phase of the research, multi-criteria decision-making techniques -namely, criteria importance through inter-criteria correlation and weighted aggregated sum product assessment- were used to transform the multiple-response optimization problem into a single-unique optimization problem and to elaborate a preference ranking among all the mixture designs. The most significant levels for acquiring the optimum overall response value were found to be 0.05% for fiber content and 5.00% for binder content and mixed filler with hydrated lime Funding: TheFORESEEproject has received funding from the European Union?s Horizon 2020 research and innovation program under grant agreement No769373.

Document type: Article

Identification of distinguishing characteristics of intersections based on statistical analysis and data from video cameras

Scipedia content — Mon, 22 Mar 2021 20:20:08 +0100

The article discusses the issues of improving the collection of traffic information using video cameras and the statistical processing of collected data. The aim of the article was to identify the main patterns of traffic at intersections in traffic congestion and to develop an analysis technique to improve traffic management at intersections. In modern conditions, there is a sharp increase in the number of vehicles, which leads to negative consequences, such as an increase in travel time, additional fuel consumption, increased risk of traffic accidents and others. To solve the problem of improving traffic control at intersections, it is necessary to have a reliable information collection system and apply modern effective methods of processing the collected information. The purpose of this article is to determine the most important traffic characteristics that affect the throughput of intersections. As a criterion for the cross-pass ability of the intersection, the actual number of passing cars during the permission signal of the torch light is taken. Using multivariate regression analysis, a model was developed to predict intersection throughput taking into account the most important traffic characteristics. Analysis of the throughput of intersections using the fuzzy logic method confirmed the correctness of the developed model. In addition, based on the results of processing information collected at 20 intersections and including 597 observations, a methodology was developed for determining the similarity of traffic intersections. This allows us to identify homogeneous types of intersections and to develop typical traffic management techniques in the city, instead of individually managing each node of the city’s transport network individually. The results obtained lead to a significant reduction in costs for the organization of rational traffic flows.

Document type: Article

Operators’ Load Monitoring and Management

Scipedia content — Mon, 22 Mar 2021 20:22:43 +0100

Due to the introduction of highly automated vehicles and systems, the tasks of operators (drivers, pilots, air traffic controllers, production process managers) are in transition from “active control” to “passive monitoring” and “supervising”. As a result of this transition, the roles of task load and workload are decreasing while the role of the mental load is increasing, thereby the new type of loads might be defined as information load and communication load. This paper deals with operators’ load monitoring and management in highly automated systems. This research (i) introduces the changes in the role of operators and requirements in load management, (ii) defines the operators’ models, (iii) describes the possible application of sensors and their integration into the working environment of operators, and (iv) develops the load observation and management concept. There are some examples of analyses of measurements and the concept of validation is discussed. This paper mainly deals with operators, particularly pilots and air traffic controllers (ATCOs).

Document type: Article

Intra-City Mobility and Characterization in a Fast-growing City of Lagos, Nigeria

Scipedia content — Mon, 22 Mar 2021 20:23:27 +0100

Effective urban transportation no doubt serves as engine room and catalyst for driving national economic development. Significantly, the purpose of urban transport is to provide both passenger and freight mobility over specific parts of urban areas including cities, and its efficiency is characterized upon transporting effectively and achieving economies of scale. Hence, this study examined intra-city mobility and characterization in Lagos, Nigeria. The data was sourced from both primary and secondary sources. Primary data detailed the use of two sets of questionnaires administered to commuters and motorists. 182 copies of questionnaire were randomly administered to commuters, while 60 units of the questionnaire were purposively and conveniently administered to motorists. Descriptive and inferential techniques were used for data analysis. Major findings revealed obvious variations in socio-economic parameters of intra-city trip makers and factors influencing trip making. It was observed that journey to work, school, shopping cum business constituted the major trips characterizing in Lagos. Findings also revealed that high patronage priority was given to most used and preferred means due to vehicle travel speed, trip purpose, and availability than safety and comfortability of modal choice. Regression analysis result revealed that commuters’ modal choice and patronage is statistically influenced by operational attributes of mode (e.g. transit time, delay duration, safety, vehicle condition and transit fare etc.) at Sig. p=0.000 and F"jats:sup"14"/jats:sup""jats:sub"165"/jats:sub" 15.667 which is greater than table value at 5% significant level. The study recommended among others the formulation and implementation of effective policy for urban transport activities; standardization of service operations and expansion of infrastructural facilities including the last-mile in the city.

Document type: Article

Substantiating The Logistics Chain Structure while Servicing The Flow of Requests for Road Transport Deliveries

Scipedia content — Mon, 22 Mar 2021 20:29:59 +0100

The selection of the delivery scheme is one of the most complicated problems and the results of its solution condition the sustainable development of the whole market of transportation services. Freight forwarders should consider numerous random parameters characterizing demand and technological processes to choose the proper structure of the logistics chain. The paper aims to propose a method for choosing the logistics chain structure, based on the analysis of the total expenses as a function from the demand parameters characterizing stochastic variables of the consignment weight, the delivery distance, and the time interval between the requests in the flow of queries for cargo delivery. Four basic logistics chain structures, widely used on road transport, are described to demonstrate the selection process. The areas of the most efficient use of the logistics chain structures can be defined for the flow of requests for cargo deliveries. The paper shows such areas on the example of goods delivery by automobile transport. Determining the areas of the most efficient use of the specific logistics chain structures contributes to the effective choice of correct delivery variants by freight forwarders.

Document type: Article

Potential for, and drivers of, private voluntary initiatives for the decarbonisation of short sea shipping: evidence from a Swedish ferry line

Scipedia content — Mon, 22 Mar 2021 20:31:35 +0100

The aim of this paper is to analyse shipping firms’ reactions to environmental challenges and identify how significant reductions in energy consumption and air emissions can come about by implementing a variety of voluntary initiatives. The paper focuses on the various sustainability initiatives implemented by the Swedish short sea shipping operator, Stena Line, either on a purely voluntary basis as part of their corporate social responsibility (CSR) strategy or as their chosen route for compliance with regulations. A conceptual model is developed based on stakeholder theory, the theory of planned behaviour and resource dependence theory to understand the main drivers of the firm’s adoption of sustainability initiatives and the factors affecting the integration of CSR in maritime companies. According to our findings, the company operates within a strongly enforced regulatory environmental framework and needs to exceed this framework to differentiate its service and strengthen its relationships with its customers by addressing their social and environmental concerns. As the firm’s competitive strategy focuses on service differentiation, a large pool of complementary resources is available for CSR and the implementation of sustainability practices. The results of this paper bring new insights to the potential of local private voluntary initiatives for the reduction of maritime air emissions. These include the provision of onshore power supply, the conversion of vessels to use methanol, ferry electrification, the construction of larger RoPax vessels and the implementation of an energy-saving program that focuses on crew involvement and continuous training. The environmental outcomes derived from a combination of local operational and technical energy efficiency measures are found to be significant and can contribute to the efforts for the achievement of sustainable maritime transport undertaken by international and regional organisations. The main barriers for the adoption of voluntary sustainability initiatives in the maritime sector are economic and technological. To encourage the wider adoption of these initiatives, the provision of economic incentives at national or regional level is crucial, as such initiatives usually imply high initial installation costs that should be somehow compensated for both vessels and terminals.

Document type: Article

Aberrant Driving Behaviours on Risk Involvement among Drivers in China

Scipedia content — Mon, 22 Mar 2021 20:33:08 +0100

The purpose of this study is to validate the version of Driver Behaviour Questionnaire (DBQ) by considering distractions, fatigue, and drunk driving, the main reasons for accidents in China, as independent parts of violations and errors and further explore the effects of demographic/driving variables and all factors on risk involvement (accident involvement and penalized points). 241 drivers filled in a self-completion questionnaire with 28 items conducted in Xi’an in August 2018. Exploratory factor analysis confirmed a five-factor structure, including violations, distracted driving, errors, drunk driving, and fatigued driving. The frequency of aberrant driving behaviours indicated that distractions were the most prevalent behaviours followed by fatigue. The results showed that drivers with lower education and longer annual mileages were positive with accident involvement while there was no significance in penalized points. Violations and distractions were important factors causing both accidents and penalized points. Therefore, it is effective to reduce accident involvement by establishing educational training and related laws or installing intelligent monitor vehicle equipment to warn drivers to improve safety.

Document type: Article

The Influence of Jam Density and Merging Cyclists on the Queue Discharge Rate

Scipedia content — Mon, 22 Mar 2021 20:39:41 +0100

An increasing number of people use the bicycle for urban trips resulting in local congestion at intersections, especially during peak hours. Understanding the queue dynamics is key to find the correct measures that can reduce the delays for cyclists without affecting other traffic modes. To this end, the discharge process of bicycle queues is studied, focusing on the impact of jam density on the queue discharge rate and how this process is affected by cyclists that merge into the queue during the discharge phase. The impact of merging cyclists is captured by a newly introduced bicycle equivalent (BE) value. This direction-specific BE value is used to convert a merging cyclist into a cyclist that is waiting in the original queue. Results show that the queue discharge rate increases with increasing density of the queue. Furthermore, cyclists that merge by overtaking contribute to the queue discharge rate, while cyclists who merge from a perpendicular direction hinder the discharge process, thereby decreasing the bicycle flow at the intersection. The insights can be used to develop measures which minimise delay at intersections and to design efficient infrastructure for bicyclists.

Document type: Article

Assessment of the Economic and Social Impact of Shared Parking in Residential Areas

Scipedia content — Mon, 22 Mar 2021 20:40:32 +0100

Shared parking schemes are not commonly implemented in residential areas due to the uncertainty and conflicts associated with the benefits of such schemes for stakeholders, namely, parking suppliers, parking managers, and the public. To evaluate the economic and social impacts of shared parking in residential areas on its stakeholders, the risk and benefit factors were determined through influential analysis and a questionnaire. A risk–benefit model was established to quantify the risks and benefits for stakeholders. The social return on investment and sensitivity analysis were applied to estimate the economic feasibility of shared parking in residential areas. The methodology combined the use of qualitative, quantitative, and financial information gathered and analyzed to estimate the “value” of shared parking, including its risks, benefits, management pressure, and social benefit. The model was calibrated using the survey data collected from the city of Ningbo in China. The results showed that: (1) The net present value was negative, indicating that the benefits of shared parking were lower than the risks, and thus this scheme would not be economically feasible in residential areas. (2) The cost of purchasing new equipment and rebuilding parking lots had the greatest impact on the benefits of shared parking in residential areas, with a sensitivity coefficient of 4.396, followed by the income from shared parking charges (3.885), and the salary of parking managers (3.619). (3) If the income from parking charges and the salary of parking managers were more than 69,408.5 and 31,091.1 yuan per month, respectively, and the cost of improving parking infrastructure was less than 14,003.2 yuan per month, residential areas could obtain additional benefits due to the acceptance of a shared parking scheme. This study provides theoretical support for the reasonable determination of the costs, risks, and benefits associated with participating in a shared parking scheme in a residential area.

Document type: Article

Acceptable Automobility through Automated Driving. Insights into the Requirements for Different Mobility Configurations and an Evaluation of Suitable Use Cases

Scipedia content — Mon, 22 Mar 2021 20:48:21 +0100

It is hoped that Automated Driving (AD) will make alternatives to the private car more attractive and facilitate the transition to sustainable transport. However, this expectation may underestimate both the resistance of private automobility and the unintended consequences of automated driving. Whether AD will contribute to sustainable mobility depends largely on its implementation and how its risks are prevented. This paper provides empirical insights into the design of acceptable forms of AD by investigating specific use cases with respect to the requirements of different mobility configurations. We pay special attention to people who travel with children. Our use cases comprise three probable types, covering the spectrum from demand-responsive transport (DRT) to private vehicles. Our results include the identification of mobility configurations and an analysis of AD use cases considering several empirically derived criteria: improved accessibility, ease of daily life and well-being, and improvement of the traffic situation and the transport system. Our analysis is based on a qualitative study in the Berlin area, Germany. The discussion focuses on the usefulness of AD against the background of different user perspectives, sustainability, and societal requirements, as well as an evaluation of AD in terms of its acceptability. We conclude that automated mobility use cases should meet the requirements of different mobility configurations to promote the transformation from private to shared automobility and, eventually, less automobility overall.

Document type: Article

Urban Electric Vehicle Fast-Charging Demand Forecasting Model Based on Data-Driven Approach and Human Decision-Making Behavior

Scipedia content — Mon, 22 Mar 2021 20:49:38 +0100

Electric vehicles (EVs) have attracted growing attention in recent years. However, most existing research has not utilized actual traffic data and has not considered real psychological decision-making of owners in analyzing the charging demand. On this basis, an urban EV fast-charging demand forecasting model based on a data-driven approach and human decision-making behavior is presented in this paper. In this methodology, Didi ride-hailing order trajectory data are firstly taken as the original dataset. Through data mining and fusion technology, the regenerated data and rules of traffic operation are obtained. Then, the single EV model with driving and charging behavior parameters is established. Furthermore, a human behavior decision-making model based on Regret Theory is introduced, which comprises the utility of time consumption and charging cost to plan driving paths and recommend fast-charging stations for vehicles. The rules obtained from data mining together with established models are combined to construct the &lsquo

Electric Vehicles&ndash

Power Grid&ndash

Traffic Network&rsquo

fusion architecture. At last, the actual urban traffic network in Nanjing is selected as an example to design the fast-charging demand load experiments in different scenarios. The results demonstrate that this proposed model is able to effectively predict the spatio-temporal distribution characteristics of urban fast-charging demands, and it more realistically simulates the decision-making psychology of owners&rsquo

charging behavior.

Document type: Article

A Proposal for Modeling Indoor–Outdoor Spaces through IndoorGML, Open Location Code and OpenStreetMap

Scipedia content — Mon, 22 Mar 2021 20:59:55 +0100

Traditionally, the standards of spatial modeling are oriented to represent the quantitative information of space. However, in recent years an increasingly common challenge is appearing: flexibly and appropriately integrating quantitative information that goes beyond the purely geometric. This problem has been aggravated due to the success of new paradigms such as the Internet of Things. This adds an additional challenge to the representation of this information due to the need to represent characteristic information of the space from different points of view in a model, such as WiFi coverage, dangerous surroundings, etc. While this problem has already been addressed in indoor spaces with the IndoorGML standard, it remains to be solved in outdoor and indoor&ndash

outdoor spaces. We propose to take the advantages proposed in IndoorGML, such as cellular space or multi-layered space model representation, to outdoor spaces in order to create indoor&ndash

outdoor models that enable the integration of heterogeneous information that represents different aspects of space. We also propose an approach that gives more flexibility in spatial representation through the integration of standards such as OpenLocationCode for the division of space. Further, we suggest a procedure to enrich the resulting model through the information available in OpenStreetMap.

Document type: Article

Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect

Scipedia content — Mon, 22 Mar 2021 21:08:04 +0100

The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and active vehicle-to-vehicle (V2V) communications based on field experimental data. Data mining results show that the correlation between the jerk effect and the driving behavior increases by 50.6% on average when V2V messages are received. In light of the data analysis results, a new car-following model is proposed to explore the jerk effect in a connected environment. The model parameters are calibrated, and the results show that the standard deviation between the new model simulation data and the observed data decreases by 38.2% compared to that of the full velocity difference (FVD) model. Linear and nonlinear analyses of the calibrated model are then carried out to evaluate the connected traffic flow stability. Finally, the theoretical analysis is verified by simulation experiments. Both the theoretical and simulation results show that the headway amplitude and velocity fluctuations are reduced when considering the jerk effect in a connected environment, and the traffic flow stability is improved.

Document type: Article

Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania

Scipedia content — Mon, 22 Mar 2021 21:19:45 +0100

Abstract. Due to their widespread and continuous expansion, transportation networks are considerably exposed to natural hazards such as earthquakes, floods, landslides or hurricanes. The vulnerability of specific segments and structures among bridges, tunnels, pumps or storage tanks can translate not only into direct losses but also into significant indirect losses at the systemic level. Cascading effects such as post-event traffic congestion, building debris or tsunamis can contribute to an even greater level of risk. To support the effort of modeling the natural hazards' implications at the full transportation network scale, we developed a new applicable framework, relying on (i) GIS to define, analyze and represent transportation networks; (ii) methods for determining the probability of network segments to fail due to natural-hazard effects; (iii) Monte Carlo simulation for multiple scenario generation; (iv) methods to analyze the implications of connectivity loss on emergency intervention times and transit disruption; and (v) correlations with other vulnerability and risk indicators. Currently, the framework is integrated into ArcGIS Desktop as a toolbox entitled “Network-risk”, which makes use of the ModelBuilder functions and is free to download and modify. Network-risk is an attempt to bring together interdisciplinary research with the goal of creating an automated solution to deliver insights on how a transportation network can be affected by natural hazards, directly and indirectly, assisting in risk evaluation and mitigation planning. In this article we present and test Network-risk at the full urban scale for the road network of Bucharest. This city is one of Europe's most exposed capitals to earthquakes, with high seismic-hazard values and a vulnerable building stock but also significant traffic congestion problems not yet accounted for in risk analyses and risk reduction strategies.

Document type: Article

Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

Scipedia content — Mon, 22 Mar 2021 21:30:43 +0100

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle&ndash

vehicle collision scenario and a vehicle&ndash

pedestrian collision scenario.

Document type: Article

Evaluating Active Traffic Management (ATM) Strategies under Non-Recurring Congestion: Simulation-Based with Benefit Cost Analysis Case Study

Scipedia content — Mon, 22 Mar 2021 21:32:48 +0100

Dynamic hard shoulder running and ramp closure are two active traffic management (ATM) strategies that are used to alleviate highway traffic congestion. This study aims to evaluate the effects of these two strategies on congested freeways under non-recurring congestion. The study’s efforts can be considered in two parts. First, we performed a detailed microsimulation analysis to quantify the potential benefits of these two ATM strategies in terms of safety, traffic operation, and environmental impact. Second, we evaluated the implementation feasibility of these two strategies. The simulation results indicated that the implementation of the hard shoulder showed a 50%–57% reduction in delay, a 41%–44% reduction in fuel consumption and emissions, and a 15%–18% increase in bottleneck throughput. By contrast, the implementation of ramp closure showed a 20%–34% decrease in travel time, a 6%–9% increase in bottleneck throughput, and an 18%–32% reduction in fuel consumption and emissions. Eventually, both strategies were found to be economically feasible.

Document type: Article

Efficiency of Telematics Systems in Management of Operational Activities in Road Transport Enterprises

Scipedia content — Mon, 22 Mar 2021 21:35:03 +0100

Implemented in road transport enterprises (RTEs) on a large scale, telematics systems are dedicated both to the particular aspects of their operation and to the integrated fields of the total operational functioning of such entities. Hence, a research problem can be defined as the identification of their efficiency levels in the context of operational activities undertaken by RTEs (including more holistic effects, e.g., lowering fuel/energy consumption and negative environmental impacts). Current research studies refer to the efficiency of some particular modules, but there have not been any publications focused on describing the efficiency of telematics systems in a more integrated (holistic) way, due to the lack of a universal tool that could be applied to provide this type of measurement. In this paper, an attempt at filling the identified cognitive gap is presented through empirical research analysing the original matrix developed by the authors that refers to the efficiency rates of organisational activities undertaken by RTEs. The purpose of this paper is to present a tool that has been designed to provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The results are presented in a form of an individual (ontogenetic) matrix of the analysed companies, for which a determinant was calculated with the use of Sarrus’ rule. Obtained in such a way, the set of values identified for the determinants of the subsequent ontogenetic matrices came as an arithmetic progression that characterised the scope and the level of the influence exerted by the implemented IT (information technology) systems on the organisational efficiency of operational activities undertaken by the analysed RTEs. We present a hypothesis stating that the originally developed matrix can be viewed as a reliable tool used for comparative analysis in the field of efficiency of telematics systems in RTEs, and this hypothesis was positively verified during the research. The obtained results prove the significant potential for the wide application of the discussed matrix, which can be used as a universal tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by RTEs.

Document type: Article

A Theoretical Research Framework of Future Sustainable Urban Freight Transport for Smart Cities

Scipedia content — Mon, 22 Mar 2021 21:38:16 +0100

This paper aims to construct a theoretical research framework for sustainable urban freight transport (SUFT) from the perspectives of future urban development and distribution innovations, and appropriate research methods are discussed, as well. Urban freight transport plays a critical role in the promotion of sustainable and livable cities. According to the literature review, considerable research on SUFT has focused on resolving some specific problems with a short-term perspective. The existence of an urban freight transport strategy is noted, which should be embedded in an overall sustainable development strategy with a long-term perspective (approximately 20&ndash

30 years). Nevertheless, considerable research has paid scant attention to the long-term planning of SUFT. Given this, this paper contributes to the closure of this gap. First, this paper presents a systematic literature review (SLR) to highlight published papers involving foresight research within the past 16 years (2003&ndash

2018). This step contributes to the understanding of research methods that can be used in foresight research. Subsequently, this paper discusses the impacts of both urban development and distribution innovations on future SUFT, and these effects are used to select the appropriate methods to construct the theoretical research framework. Finally, the theoretical research framework of long-term planning for SUFT is developed on the basis of two future perspectives: the trends of urban development and the application of urban distribution innovations. This framework is intended to provide an approach to designing sustainable urban logistics, taking into account urban development and distribution innovations.

Document type: Article

A Cost and Passenger Responsible Optimization Method for the Operation Plan of Additional High-Speed Trains in a Peak Period

Scipedia content — Mon, 22 Mar 2021 21:55:21 +0100

In the peak period of a railway system, operators typically add additional trains to provide increased capacity to satisfy the increasing passenger demand. The paper proposes a new optimization framework for designing the operation plan, which includes the number of additional trains, train type, stop plan, and timetable, for additional trains in a peak period. A space-time network representation is used to obtain a feasible primary operation plan by finding a set of feasible space-time paths in the space-time network. Considering simultaneously the passenger demand and the trains’ total travel times, we formulate a biobjective integer programming model for generating a cost and passenger responsible primary operation plan. A set of loading capacity constraints are formulated in the model to guarantee a suitable loading capacity for each station’s passenger demand and better service for passengers. The CPLEX solver is used to solve the proposed model and to generate the optimal operation plan. Two sets of numerical experiments are conducted on a small-scale rail corridor and on the Wuhan-Guangzhou rail corridor to evaluate the performance of the proposed method. The results of the experiments show that the primary operation plan can be obtained within an acceptable computation time.

Document type: Article

Optimization of a physical internet based supply chain using reinforcement learning

Scipedia content — Mon, 22 Mar 2021 21:57:41 +0100

Physical Internet based supply chains create open, global logistics systems that enable new types of collaboration among participants. The open system allows the logistical examination of vehicle technology innovations such as the platooning concept. This article explores the multiple platoon collaboration. For the reconfiguration of two platoons a heuristic and a reinforcement learning (RL) based models have been developed. To our knowledge, this work is the first attempt to apply an RL-based decision model to solve the problem of controlling platoon cooperation. Vehicle exchange between platoons is provided by a virtual hub. Depending on the various input parameters, the efficiency of the model was examined through numerical examples in terms of the target function based on the transportation cost. Models using platoon reconfiguration are also compared to the cases where no vehicle exchange is implemented. We have found that a reinforcement learning based model provides a more efficient solution for high incoming vehicle numbers and low dispatch interval, although for low vehicle numbers heuristics model performs better.

Document type: Article

A Brief Analysis of the Current Situation and Development Trend on Green Transportation Standard System

Scipedia content — Mon, 22 Mar 2021 22:06:16 +0100

It is great significance to improve green transportation standards system for promoting the construction of ecological civilization and the sustainable development of recycling and low carbon of transportation. This paper summarizes the status of green transportation standards system and the progress of standard publication and revision. According to the key areas and links of green transportation development, the development trends of green transportation and the requirement of green transportation standards were analysed, and policy recommendations for improving the construction of green transportation standards system was proposed. The paper is trying to provide decisive support for the industry to promote the development of green transportation standardization.

Document type: Article

A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China

Scipedia content — Mon, 22 Mar 2021 22:10:24 +0100

An airport gate is the core resource of an airport operation, which is an important place for passengers to get on and off the aircraft and for maintaining aircraft. It is the prerequisite for other related dispatch. Effective and reasonable allocation of gates can reduce airport operating costs and increase passenger satisfaction. Therefore, an airport gate assignment problem (AGAP) needs to be urgently solved in the actual operation of the airport. In this paper, considering the actual operation of the airport, we formulate an integer programming model for AGAP by considering multiple constraints. The model aims to maximize the number of passengers on flights parked at the gate. A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. A unique neighborhood structure and search strategy for tabu search are designed. The algorithm can adapt to the dynamic scheduling of airports. Finally, tests are performed using actual airport data selected from Kunming Changshui International Airport in China. The experimental results indicate that the proposed method can enhance the local search ability and global search ability and get satisfactory results in a limited time. These results provide an effective support for the actual gate assignment in airport operations.

Document type: Article

Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms

Scipedia content — Mon, 22 Mar 2021 22:14:05 +0100

The recent trend for vehicles to be connected to unspecified devices, vehicles, and infrastructure increases the potential for external threats to vehicle cybersecurity. Thus, intrusion detection is a key network security function in vehicles with open connectivity, such as self-driving and connected cars. Specifically, when a vehicle is connected to an external device through a smartphone inside the vehicle or when a vehicle communicates with external infrastructure, security technology is required to protect the software network inside the vehicle. Existing technology with this function includes vehicle gateways and intrusion detection systems. However, it is difficult to block malicious code based on application behaviors. In this study, we propose a machine learning-based data analysis method to accurately detect abnormal behaviors due to malware in large-scale network traffic in real time. First, we define a detection architecture, which is required by the intrusion detection module to detect and block malware attempting to affect the vehicle via a smartphone. Then, we propose an efficient algorithm for detecting malicious behaviors in a network environment and conduct experiments to verify algorithm accuracy and cost through comparisons with other algorithms.

Document type: Article

Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China

Scipedia content — Mon, 22 Mar 2021 22:18:29 +0100

Since the number of bicycles is critical to the sustainable development of dockless PBS, this research practiced the introduction of a machine learning approach to quantity management using OFO bike operation data in Shenzhen. First, two clustering algorithms were used to identify the bicycle gathering area, and the available bike number and coefficient of available bike number variation were analyzed in each bicycle gathering area’s type. Second, five classification algorithms were compared in the accuracy of distinguishing the type of bicycle gathering areas using 25 impact factors. Finally, the application of the knowledge gained from the existing dockless bicycle operation data to guide the number planning and management of public bicycles was explored. We found the following. (1) There were 492 OFO bicycle gathering areas that can be divided into four types: high inefficient, normal inefficient, high efficient, and normal efficient. The high inefficient and normal inefficient areas gathered about 110,000 bicycles with low usage. (2) More types of bicycle gathering area will affect the accuracy of the classification algorithm. The random forest classification had the best performance in identifying bicycle gathering area types in five classification algorithms with an accuracy of more than 75%. (3) There were obvious differences in the characteristics of 25 impact factors in four types of bicycle gathering areas. It is feasible to use these factors to predict area type to optimize the number of available bicycles, reduce operating costs, and improve utilization efficiency. This work helps operators and government understand the characteristics of dockless PBS and contributes to promoting long-term sustainable development of the system through a machine learning approach.

Document type: Article

Exploring everyday mobility in a living lab based on economic interventions

Scipedia content — Mon, 22 Mar 2021 22:19:40 +0100

New mobility solutions, such as Mobility as a Service, have been suggested to have the potential to reduce car ownership and be part of a transition towards a more sustainable transportation system. However, research suggests that governance measures such as taxation and policies will be needed to ensure sustainability aspects. This paper explores everyday mobility by use of interventions in people’s everyday lives. The focus is on identifying underlying factors that may motivate or hinder changes that are positive from a sustainability perspective. This is then put in the perspective of new mobility services and policy making. Our findings support the view that privately owned cars are hard to replace with new mobility services that contribute to sustainability and are not based on individual cars. Economic interventions for increased sustainability will likely have limited effects, since the alternatives do not offer what car owners value most. Also, limited understanding of the car’s full costs may make the new services appear comparatively more expensive. Furthermore, urban planning to reduce the need for travel, and the capacity of the physical public transport infrastructure will continue to be important. Long vacation trips and “medium sized flows” are identified as opportunities for further research and for new solutions to support sustainable mobility transitions.

Document type: Article

Assessing the Impacts of Autonomous Bus-on-Demand Based on Agent-Based Simulation: A Case Study of Fuyang, Zhejiang, China

Scipedia content — Mon, 22 Mar 2021 22:29:50 +0100

This paper envisions and assesses the performance of an autonomous bus-on-demand (ABoD) system. We take Fuyang, Zhejiang, China, as the study area to investigate the spatiotemporal distribution of bus travel demand during workdays, and we propose replacing inefficient bus routes with the ABoD system. Agent-based models with various bus dispatching and operation control strategies are constructed to evaluate the performance of the ABoD system. The behaviors and interactions of the agents, passengers, autonomous buses, and a control center are designed. After the verification of the simulated bus travel demand with real-world demand, a series of scenarios with various ABoD operation strategies are simulated. The simulation results show that, in comparison with both current fixed-schedule bus services and the optimized bus dispatching strategies, the ABoD system occupies fewer road resources and utilizes bus vehicles more efficiently. Besides, the system is adaptive to the sudden surge in bus travel demand and is economically sustainable.

Document type: Article

Li-Ion Batteries: A Review of a Key Technology for Transport Decarbonization

Scipedia content — Mon, 22 Mar 2021 22:38:17 +0100

Lithium ion batteries are experiencing an increased success thanks to their interesting performances, in particular for electric vehicles applications. Their continuous technological improvements in the last years are providing higher energy density and lower manufacturing costs. However, the environmental performance of their supply chain is of paramount importance to guarantee a cleaner alternative to fossil-based solutions on the entire life cycle of the applications. This paper carries out a comprehensive review on the main aspects related to Li-ion batteries manufacturing, to support the readers in understanding the complexity of the subject and the main challenges and opportunities for the future developments of this technology. The paper discusses the expected future demand of batteries; the main aspects related to the supply chain, including existing assets, input materials and alternative technologies; the end-of-life of batteries; the environmental impacts; and the main geopolitical implications.

Document type: Article

Collaborative Multidepot Petrol Station Replenishment Problem with Multicompartments and Time Window Assignment

Scipedia content — Mon, 22 Mar 2021 22:42:12 +0100

Energy supply is an important system that affects the overall efficiency of urban transportation. To improve the system operational efficiency and reduce costs, we formulate and solve a collaborative multidepot petrol station replenishment problem with multicompartments and time window assignment by establishing a mixed-integer linear programming model. The hybrid heuristic algorithm composed of genetic algorithm and particle swarm optimization is used as a solution, and then the Shapley value method is applied to analyze the profit allocation of each petrol depot under different coalitions. The optimal membership sequence of the cooperation is determined according to the strict monotone path. To analyze and verify the effectiveness of the proposed method, a regional petrol supply network in Chongqing city in China is investigated. Through cooperation between petrol depots in the supply network, the utilization of customer clustering, time window coordination, and distribution truck sharing can significantly reduce the total operation costs and improve the efficiency of urban transportation energy supply. This approach can provide theoretical support for relevant government departments and enterprises to make optimal decisions. The implementation of the joint distribution of energy can promote the sustainable development of urban transportation.

Document type: Article

Are Existing Battery Electric Vehicles Adoption Studies Able to Inform Policy? A Review for Policymakers

Scipedia content — Mon, 22 Mar 2021 22:51:16 +0100

Accelerating the adoption of electric vehicles provides a rare historic opportunity for reducing the dependence on fossil fuel and decarbonising road networks in the field of transport. Many countries have introduced various policy packages on both national and local levels to encourage electric vehicle adoption, but their market shares remain low. For better understanding the reasons behind this evidence, exploring the determinants that influence consumers’ adoption intentions is significant. Previous literature reviews have made clear and elaborated syntheses of influential factors; however, a summary of how evidence can be translated into policy through these factors is lacking. In response, this paper synthesises the main policies of various countries, summarises the previous research results, and forms corresponding policy tools, which can provide a reference to policymakers and guide the policy-making process.

Document type: Article

Evidence from Nanjing, China

Scipedia content — Mon, 22 Mar 2021 22:55:36 +0100

Promoting a transition in individuals&rsquo

travel mode from car to an integrated metro and bikeshare systems is expected to effectively reduce the traffic congestion that results mainly from commute trips performed by individual automobiles. This paper focuses on the use frequency of an integrated metro&ndash

bikeshare by individuals, and presents empirical evidence from Nanjing, China. Using one-week GPS data collected from the Mobike company, the spatiotemporal characteristics of origin/destination for cyclists who would likely to use shared bike as a feeder mode to metro are examined. Three areas of travel-related spatiotemporal information were extracted including (1) the distribution of walking distances between metro stations and shared bike parking lots

(2) the distribution of cycling times between origins/destinations and metro stations

and (3) the times when metro&ndash

bikeshare users pick up/drop off shared bikes to transfer to/from a metro. Incorporating these three features into a questionnaire design, an intercept survey of possible factors on the use of the combined mode was conducted at seven functional metro stations. An ordered logistic regression model was used to examine the significant factors that influence groupings of metro passengers. Results showed that the high-, medium- and low-frequency groups of metro&ndash

bikeshare users accounted for 9.92%, 21.98% and 68.1%, respectively. Education, individual income, travel purpose, travel time on the metro, workplace location and bike lane infrastructure were found to have significant impacts on metro passengers&rsquo

use frequency of integrated metro&ndash

bikeshares. Relevant policies and interventions for metro passengers of Nanjing are proposed to encourage the integration of metro and bikeshare systems.

Document type: Article

Chats About Daily Traffic: Agentic Adaptability of Jabodetabek Commuters to Minimize Stress and Transcend Everyday Lives

Scipedia content — Mon, 22 Mar 2021 23:03:03 +0100

With the increasing number of people invading Greater Jakarta and the ongoing improvement of infrastructure in Greater Jakarta or Jabodetabek, one of the challenges faced by the community is traffic congestion. Previous studies revealed the negative impact of traffic congestion on community welfare and mental health. Thus, the present study aims to shed light on how Jabodetabek inhabitants and commuters experience, make sense, and adapt to daily traffic congestion. Data were obtained from discussions in six WhatsApp groups, which included a total of 160 respondents. The study supports the findings of previous studies, that is, traffic congestion leads to increased costs and losses and causes distress. However, the subjective perception of time management enables commuters to adapt to the situation. Nevertheless, the paper presents a novel finding: agentic adaptability of Jabodetabek commuters, which is evidenced by the ability to discover various means of adjusting to traffic congestion. Although effective policies are required to mitigate congestion, the good news is that many opportunities for adjustment await the community in terms of being stuck in traffic.

Document type: Article

Comparing Spatial Accessibility and Travel Time Prediction to Commercial Centres by Private and Public Transport: A Case Study of Oforikrom District

Scipedia content — Mon, 22 Mar 2021 23:07:31 +0100

The relevance of accessibility in shaping transport planning has often been neglected, hampering on decisions to improve transport efficiency. This is increasingly becoming problematic, as they often impede on economic and technological developments. Many studies on accessibility assert that it is easier for public transport to reach an activity centre than it is for private transport. For this reason, the research compares travel time forecast and accessibility levels with private and public transports en route to commercial centres. The research involves a 21-day transport survey for private cars and public shuttles in Oforikrom district using Global Positioning System (GPS) probe to record the traffic performance indicators to be analyzed in a GIS environment. The results of the study display on a map the level of accessibility via the modes, and a comparative line plot of travel time with private and public transport. The study reveals that private cars in the district generally perform better than public shuttles on the level of accessibility, and travel time. The execution of the research shows that the convergence of choice of transport mode and travel time dynamics is crucial for policymakers to implement diverse transport modes and commuters to choose a mode that has low accessibility cost.

Document type: Article

Battery Models for Battery Powered Applications: A Comparative Study

Scipedia content — Mon, 22 Mar 2021 23:09:06 +0100

Battery models have gained great importance in recent years, thanks to the increasingly massive penetration of electric vehicles in the transport market. Accurate battery models are needed to evaluate battery performances and design an efficient battery management system. Different modeling approaches are available in literature, each one with its own advantages and disadvantages. In general, more complex models give accurate results, at the cost of higher computational efforts and time-consuming and costly laboratory testing for parametrization. For these reasons, for early stage evaluation and design of battery management systems, models with simple parameter identification procedures are the most appropriate and feasible solutions. In this article, three different battery modeling approaches are considered, and their parameters’ identification are described. Two of the chosen models require no laboratory tests for parametrization, and most of the information are derived from the manufacturer’s datasheet, while the last battery model requires some laboratory assessments. The models are then validated at steady state, comparing the simulation results with the datasheet discharge curves, and in transient operation, comparing the simulation results with experimental results. The three modeling and parametrization approaches are systematically applied to the LG 18650HG2 lithium-ion cell, and results are presented, compared and discussed.

Document type: Article

Impact of Urban Undersea Tunnel Longitudinal Slope on the Visual Characteristics of Drivers

Scipedia content — Mon, 22 Mar 2021 23:10:30 +0100

This study aims to investigate the impact of the urban undersea tunnel longitudinal slope on the visual characteristics of drivers. 20 drivers were enrolled to conduct the real vehicle test of the urban undersea tunnel. First, the data of average fixation time and visual lobe were collected by an eye tracker. The differential significance was tested using the one-way repeated measures analysis of variance (ANOVA). Then, the difference between the up-and-down slope (direction) factor and the longitudinal slope (percent) factor on the two indexes were analyzed using the two-way repeated measures ANOVA. Second, by constructing a Lorentz model, the impact of the longitudinal slope on the average fixation time and the visual lobe were analyzed. Besides, a three-dimensional model of the longitudinal slope, average fixation time, and visual lobe was quantified. The results showed that the average fixation time and visual lobe under different longitudinal slopes markedly differed when driving on the uphill and downhill sections. The average fixation time and visual lobe under two factors were markedly different. Moreover, with an increase in the longitudinal slope, the average fixation time exhibited a trend of increasing first then decreasing; the visual lobe exhibited a trend of decreasing first and then increasing. The average fixation time reached the minimum and maximum value when the slope was 2.15% and 4.0%, whereas the visual lobe reached the maximum and minimum value when the slope was 2.88% and 4.0%. Overall, the longitudinal slope exerted a great impact on the visual load of the driver.

Document type: Article

Analyzing Household Vehicle Ownership in the Japanese Local City: Case Study in Toyota City

Scipedia content — Mon, 22 Mar 2021 23:15:03 +0100

This study aims to understand the crucial factors affecting vehicle ownership in the local city, Japan. 14,855 household sample data in Toyota City are used as the research sample. The sample data are extracted from the 5th Person Trip Survey data in the Chukyo region. First, the unknown annual income is complemented by using an ordered probit model. Then, a trivariate ordered probit model is utilized to analyze ownership of light motor vehicles, ordinary motor vehicles, and small trucks simultaneously. To estimate unknown parameters effectively and efficiently, one type of Markov Chain Monte Carlo methods called the Gibbs Sampler algorithm is applied in this study. The significant findings suggest the following: (1) the annual income only affects the ownership of ordinary motor vehicles; (2) a household with a 60-year-old or older householder is more likely to own small trucks, compared to that with a householder below the age of 60; (3) the population density negatively affects the number of light motor vehicles and that of small trucks; (4) there is a substitution effect of vehicle ownership between light motor vehicles and small trucks.

Document type: Article

Comparing of Data Collection for Network Level Pavement Management of Urban Roads and Highways

Scipedia content — Mon, 22 Mar 2021 23:19:50 +0100

Pavement condition data are collected by agencies to support pavement management system (PMS) for decision-making purpose as well as to construct performance model. The cost of pavement data collection increases with the increase of survey frequencies. However, a lower monitoring frequency could lead to unreliable maintenance decisions. It is necessary to understand the influence of monitoring frequencies on maintenance decision by considering the reliability of performance prediction models. Because of different maintenance conditions of urban roads and highways, their performance show different trends. In this paper, the influence of pavement monitoring frequency on the pavement performance models was investigated. The results indicate that low collection frequencies may result in delay in maintenance action by overestimating pavement performance. The collection frequency for Pavement Condition Index (PCI) can be reduced without compromising the accuracy of performance model, more work should be done to ensure the PCI data quality, thus to guarantee the rationality of maintenance decisions. Effect of frequency reduction on pavement performance (IRI) models of urban roads seems greater than on pavement performance (IRI) models of highways, which may lead to heavier monitoring work for urban roads management. This paper provided an example which demonstrated how a comparative analysis can be performed to determine whether the current data collection plan can provide sufficient data for time series analysis.

Document type: Article

Study of Pipeline Penetration Based on CEL in Clay

Scipedia content — Mon, 22 Mar 2021 23:25:41 +0100

In deep water, pipelines are usually laid directly on the seabed. During the laying process, the pipe typically penetrates into the seabed by a fraction of a diameter. The vertical embedment of pipeline and formation of berm during penetration have a significant effect on the pipeline stability. This study aims to investigate the vertical pipeline penetration at uniform and normal consolidated clay, by carrying out a series of numerical analyses, in which the coupled Eulerian-Lagrangian method (CEL) is incorporated to enable large deformation simulation. These analyses have been compared with collapse loads calculated using the theory solution. The results show that the CEL method is very suitable for simulating large-deformation pipesoil interaction.

Document type: Article

Vehicle Trajectory Prediction by Knowledge-Driven LSTM Network in Urban Environments

Scipedia content — Mon, 22 Mar 2021 23:35:43 +0100

An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types of vehicles. Vehicle trajectories are not only constrained by a priori knowledge about road structure, traffic signs, and traffic rules but also affected by posterior knowledge about different driving styles of drivers. The existing prediction models cannot fully combine the prior and posterior knowledge in the driving scene and perform well only in a specific traffic scenario. This paper presents a long short-term memory (LSTM) neural network driven by knowledge. First, a driving knowledge base is constructed to describe the prior knowledge about a driving scenario. Then, the prediction reference baseline (PRB) based on driving knowledge base is determined by using the rule-based online reasoning system. Finally, the future trajectory of the target vehicle is predicted by an LSTM neural network based on the prediction reference baseline, while the predicted trajectory considers both posterior and prior knowledge without increasing the computation complexity. The experimental results show that the proposed trajectory prediction model can adapt to different driving scenarios and predict trajectories with high accuracy due to the unique combination of the prior and posterior knowledge in the driving scene.

Document type: Article

Modeling the Charging Behaviors for Electric Vehicles Based on Ternary Symmetric Kernel Density Estimation

Scipedia content — Mon, 22 Mar 2021 23:38:37 +0100

The accurate modeling of the charging behaviors for electric vehicles (EVs) is the basis for the charging load modeling, the charging impact on the power grid, orderly charging strategy, and planning of charging facilities. Therefore, an accurate joint modeling approach of the arrival time, the staying time, and the charging capacity for the EVs charging behaviors in the work area based on ternary symmetric kernel density estimation (KDE) is proposed in accordance with the actual data. First and foremost, a data transformation model is established by considering the boundary bias of the symmetric KDE in order to carry out normal transformation on distribution to be estimated from all kinds of dimensions to the utmost extent. Then, a ternary symmetric KDE model and an optimum bandwidth model are established to estimate the transformed data. Moreover, an estimation evaluation model is also built to transform simulated data that are generated on a certain scale with the Monte Carlo method by means of inverse transformation, so that the fitting level of the ternary symmetric KDE model can be estimated. According to simulation results, a higher fitting level can be achieved by the ternary symmetric KDE method proposed in this paper, in comparison to the joint estimation method based on the edge KDE and the ternary t-Copula function. Moreover, data transformation can effectively eliminate the boundary effect of symmetric KDE.

Document type: Article

Advancing Applied Research in High Volume Transport in Low-Income Countries in Africa and South Asia

Scipedia content — Mon, 22 Mar 2021 23:40:01 +0100

The Department for International Development (DFID) is funding the High Volume Transport (HVT) Applied Research Programme. This programme is an integral component of the UK response to delivering transport and mobility that is accessible, efficient, safe, and green in the low-income countries (LICs) in Africa and South Asia. The first part of the HVT programme produced an up-to-date and comprehensive state of knowledge on high volume transport in these countries. This Special Issue presents a selection of papers to cover key research priorities identified in road and rail transport, low carbon transport, and gender and inclusive transport. The state of knowledge has produced a sound basis for setting priorities for applied research in the second part of the programme. Applied research is directed to delivering high volume transport that contributes to economic growth and social development, and that is more resilient to the impact of climate change in LICs in Africa and South Asia.

Document type: Article

Simultaneous Incomplete Traffic Data Imputation and Similarity Pattern Discovery with Bayesian Nonparametric Tensor Decomposition

Scipedia content — Mon, 22 Mar 2021 23:54:22 +0100

A crucial task in traffic data analysis is similarity pattern discovery, which is of great importance to urban mobility understanding and traffic management. Recently, a wide range of methods for similarities discovery have been proposed and the basic assumption of them is that traffic data is complete. However, missing data problem is inevitable in traffic data collection process due to a variety of reasons. In this paper, we propose the Bayesian nonparametric tensor decomposition (BNPTD) to achieve incomplete traffic data imputation and similarity pattern discovery simultaneously. BNPTD is a hierarchical probabilistic model, which is comprised of Bayesian tensor decomposition and Dirichlet process mixture model. Furthermore, we develop an efficient variational inference algorithm to learn the model. Extensive experiments were conducted on a smart card dataset collected in Guangzhou, China, demonstrating the effectiveness of our methods. It should be noted that the proposed BNPTD is universal and can also be applied to other spatiotemporal traffic data.

Document type: Article

Intelligent Video Surveillance Technology in Intelligent Transportation

Scipedia content — Tue, 23 Mar 2021 00:07:51 +0100

Along with the strength of the country’s overall strength, the people’s pockets have become more and more popular, and there have been significant improvements in all aspects of life, especially in terms of travel methods. This reflects the increase in residents’ income, but it also brings huge traffic pressure. In the long run, traffic congestion is not only detrimental to urban development, but frequent traffic accidents threaten residents’ travel safety. Effective monitoring methods are essential to solving these problems, so it is necessary to carry out research on intelligent video monitoring technology in intelligent transportation. The purpose of this article is to solve the current situation of excessive traffic pressure in the city. Through the study of intelligent video surveillance technology in intelligent traffic, the use of constrained least squares algorithm to remove motion blur and apply Kalan filtering to the sharpening process is used to eliminate noise ambiguity and make a brief introduction to various classic moving target detection methods to realize real-time monitoring of intelligent traffic conditions and continuously adjust and verify the monitoring situation, and then establish intelligent video in intelligent traffic monitoring technology research system. The research results show that this kind of intelligent video surveillance technology research in intelligent transportation can effectively increase the awareness of intelligent video surveillance technology and improve the level of intelligent video surveillance technology. The data measurement time has been shortened by one hour, the aggregation time has been changed from three hours to two hours, and the analysis time has been shortened by half. Eased urban traffic road pressure and greatly reduced the incidence of traffic accidents, which is conducive to socialist harmony social construction.

Document type: Article

Problems of Sustainable Transport of Large-Sized Roundwood

Scipedia content — Tue, 23 Mar 2021 00:09:28 +0100

When considering the economic and environmental aspects of forestry, especially the issues related to timber harvesting, emphasis should be placed on the importance of the availability of raw material resources for the sustainable flow of goods. It would also be difficult to disregard certain issues related to transport, which play a key role in the efficient flow of wooden raw materials. It has to be noticed that timber transport options are limited by a number of factors, including the considerable fragmentation of wood resources and the lack of adequately developed railway transport facilities. This paper focuses on issues related to the road transport of timber carried out by transport companies. Observations to date of large-sized roundwood (thicker than 14 cm and longer than 3 m) transport in Poland indicate a relatively frequent occurrence of overloaded vehicles, exceeding the permissible total weight limit. Empirical evidence also suggests that in many cases, it is an effect of improperly endorsed standards with regard to the density of the transported material. Moreover, there is a clear correlation between the loading volume and economic as well as environmental factors. Therefore, the aim of this article was to show both the current situation in the transport of bulky timber and to present the possibilities for its optimization, from the point of view of locational, economic and environmental factors.

Document type: Article

Consequences of Transport Low-Carbon Transitions and the Carbon, Land and Water Footprints of Different Fuel Options in The Netherlands

Scipedia content — Tue, 23 Mar 2021 00:27:38 +0100

Transport greenhouse gas emissions are mainly caused by the use of fossil fuels, e.g., gasoline and diesel. This case study for The Netherlands calculates how alternative fuels, e.g., electricity, hydrogen or biofuels, contribute to policy aims to decarbonize transport. Alternative fuels, produced in various ways, have different carbon (CF), land (LFs) and water footprints (WFs). This study assesses CFs, LFs and WFs for fuels (kgCO"sub"2"/sub"e/m"sup"2"/sup"/m"sup"3"/sup" per GJ), showing differences among fuels dependent on primary energy sources. It calculates CFs, LFs and WFs for four scenarios with different fuels. The biofuel scenario is not attractive. CFs slightly decrease, while LFs and WFs increase enormously. The electricity scenario has small CFs and the smallest LFs and WFs, but this is only when using wind or solar energy. If storage is needed and hydrogen is produced using wind energy, CFs double from 3055 to 7074 kg CO"sub"2"/sub"e, LFs increase from 15 × 10"sup"6"/sup" to 43 × 10"sup"6"/sup" m"sup"2"/sup" and WFs from 3 × 10"sup"6"/sup" to 37 × 10"sup"6"/sup" m"sup"3"/sup" compared to the electricity scenario. The case study shows that wise fuel choices contribute to policy aims to decarbonize transport, although LFs and WFs are also important to consider. These case study results are relevant for sustainable transportation transitions worldwide.

Document type: Article

Improving Driver Assistance in Intelligent Transportation Systems: An Agent-Based Evidential Reasoning Approach

Scipedia content — Tue, 23 Mar 2021 00:30:52 +0100

Providing accurate real-time traffic information is an inherent problem for intelligent transportation systems (ITS). In order to improve the knowledge base of advanced driver assistance systems (ADAS), ITS are strongly concerned with data fusion techniques of all kinds of sensors deployed over the traffic network. Driver assistance is devoid of a comprehensive evidential reasoning system on contextual information, more specifically when a combination involves inside and outside sensory information of the driving environment. In this paper, we propose a novel agent-based evidential reasoning system using contextual information. Based on a series of information handling techniques, specifically, the belief functions theory and heuristic inference operations to achieve a consensus about daily driving activity in automatically inferring. That is quite different from other existing proposals, as it deals jointly with the driving behavior and the driving environment conditions. A case study including various scenarios of experiments is introduced to estimate behavioral information based on synthetic data for prediction, prescription, and policy analysis. Our experiments show promising, thought-provoking results encouraging further research.

Document type: Article

Coordinated Headway-Based Control Method to Improve Public Transit Reliability considering Control Points Layout

Scipedia content — Tue, 23 Mar 2021 00:32:28 +0100

The headway-based control method is usually used to regulate the bus headways and improve reliability of public transit. In general, the holding control strategy is applied at the control point, because enough space for dwell longer at the control point is required, while the stop-skipping control strategy can be used at any bus stop. However, in the headway-based control method, too much stop-skipping will bring longer waiting time and make the passengers impatient. The number and distribution of control points for stop-skipping are not considered in previous self-equalizing bus headway control works. Therefore, in this paper, the control points selection rules for stop-skipping involving their number and distribution on the bus route are discussed. A second by second discrete system is formulated to describe the bus operation. In the proposed control method, the threshold value for activating stop-skipping strategy is raised, avoiding provoking much additional waiting time because of boarding rejected. In the numerical analysis, a set of cases are conducted to evaluate the performance of control method under different number and distribution of control points for stop-skipping. The numerical results show that distribution of control points for stop-skipping has a greater influence on the public transit than the number.

Document type: Article

Application of Least Squares with Conditional Equations Method for Railway Track Inventory Using GNSS Observations

Scipedia content — Tue, 23 Mar 2021 00:34:12 +0100

Satellite geodetic networks are commonly used in surveying tasks, but they can also be used in mobile surveys. Mobile satellite surveys can be used for trackage inventory, diagnostics and design. The combination of modern technological solutions with the adaptation of research methods known in other fields of science offers an opportunity to acquire highly accurate solutions for railway track inventory. This article presents the effects of work carried out using a mobile surveying platform on which Global Navigation Satellite System (GNSS) receivers were mounted. The satellite observations (surveys) obtained were aligned using one of the methods known from classical land surveying. The records obtained during the surveying campaign on a 246th km railway track section were subjected to alignment. This article provides a description of the surveying campaign necessary to obtain measurement data and a theoretical description of the method employed to align observation results as well as their visualisation.

Document type: Article

Dynamic Origin-Destination Matrix Estimation Based on Urban Rail Transit AFC Data: Deep Optimization Framework with Forward Passing and Backpropagation Techniques

Scipedia content — Tue, 23 Mar 2021 00:39:03 +0100

At present, the existing dynamic OD estimation methods in an urban rail transit network still need to be improved in the factors of the time-dependent characteristics of the system and the estimation accuracy of the results. This study focuses on predicting the dynamic OD demand for a time of period in the future for an urban rail transit system. We propose a nonlinear programming model to predict the dynamic OD matrix based on historic automatic fare collection (AFC) data. This model assigns the passenger flow to the hierarchical flow network, which can be calibrated by backpropagation of the first-order gradients and reassignment of the passenger flow with the updated weights between different layers. The proposed model can predict the time-varying OD matrix, the number of passengers departing at each time, and the travel time spent by passengers, of which the results are shown in the case study. Finally, the results indicate that the proposed model can effectively obtain a relatively accurate estimation result. The proposed model can integrate more traffic characteristics than traditional methods and provides an effective and hierarchical passenger flow estimation framework. This study can provide a rich set of passenger demand for advanced transit planning and management applications, for instance, passenger flow control, adaptive travel demand management, and real-time train scheduling.

Document type: Article

An Automatic Emergency Braking Model considering Driver’s Intention Recognition of the Front Vehicle

Scipedia content — Tue, 23 Mar 2021 00:45:55 +0100

Driver’s intention of the front vehicle plays an important role in the automatic emergency braking (AEB) system. If the front vehicle brakes suddenly, there is potential collision risk for following vehicle. Therefore, we propose a driver’s intention recognition model for the front vehicle, which is based on the backpropagation (BP) neural network and hidden Markov model (HMM). The brake pedal, accelerator pedal, and vehicle speed data are used as the input of the proposed BP-HMM model to recognize the driver’s intention, which includes uniform driving, normal braking, and emergency braking. According to the recognized driver’s intention transmitted by Internet of vehicles, an AEB model for the following vehicle is proposed, which can dynamically change the critical braking distance under different driving conditions to avoid rear-end collision. In order to verify the performance of the proposed models, we conducted driver’s intention recognition and AEB simulation tests in the cosimulation environment of Simulink and PreScan. The simulation test results show that the average recognition accuracy of the proposed BP-HMM model was 98%, which was better than that of the BP and HMM models. In the Car to Car Rear moving (CCRm) and Car to Car Rear braking (CCRb) tests, the minimum relative distance between the following vehicle and the front vehicle was within the range of 1.5 m–2.7 m and 2.63 m–5.28 m, respectively. The proposed AEB model has better collision avoidance performance than the traditional AEB model and can adapt to individual drivers.

Document type: Article

Depicting corrosion-born defects in pipelines with combined neutron/γ ray backscatter: a biomimetic approach

Scipedia content — Tue, 23 Mar 2021 00:49:12 +0100

The identification of corrosion, cracks and defects in pipelines used for transporting oil and gas can reduce the possibility of leaks, and consequently, it can limit the extent of an environmental disaster, public hazard and the associated financial impact of such events. Typically, corrosion in oil pipelines is measured with non-destructive ultrasonic or electromagnetic techniques, on the basis that corrosion and defects are often manifest as a change of thickness in the steel from which pipelines are made. However, such approaches are not practical for underground pipelines and their deployment can be complicated for the case of pipelines covered by insulation. In this paper, we present an innovative, non-destructive testing technique, which exploits the backscatter of a combination of fast-neutron and γ radiation from steel samples of a variety of thicknesses consistent with changes that might arise due to corrosion of a pipe wall. Our research demonstrates the potential to measure and characterise different steel thicknesses by detecting both the elastic, fast-neutron backscatter and the Compton-scattered γ radiations, simultaneously. Further, we demonstrate that the presence of insulation yields a consistent and separable influence on the experimental, wall-thickness measurements. The data from experimental measurements are supported by a comprehensive Monte Carlo computer simulation study.

Document type: Article

Computationally Efficient Energy Management in Hybrid Electric Vehicles Based on Approximate Pontryagin’s Minimum Principle

Scipedia content — Tue, 23 Mar 2021 00:50:56 +0100

This article presents an energy management method for a parallel hybrid electric vehicle (HEV) based on approximate Pontryagin’s Minimum Principle (A-PMP). The A-PMP optimizes gearshift commands and torque distribution for overall energy efficiency. As a practical numerical solution in PMP, the proposed methodology utilizes a piecewise linear approximation of the engine fuel rate and state of charge (SOC) derivative by considering drivability and fuel economy simultaneously. Moreover, battery aging is explicitly studied by introducing a control-oriented model, which aims to investigate the effect of battery aging on the optimization performance in the development of the HEVs. An approximate energy management strategy with piecewise linear models is then formulated by the A-PMP, which targets a better performance for the Hamiltonian optimization. The gearshift map is extracted from the optimal results in the standard PMP to hinder frequent gearshift by considering both drivability and fuel economy. Utilizing an approximated Hamilton function, the torque distribution, gearshift command, and the battery aging degradation are jointly optimized under a unified framework. Simulations are performed for dynamic programming (DP), PMP, and A-PMP to validate the effectiveness of the proposed approach. The results indicate that the proposed methodology achieves a close fuel economy compared with the DP-based optimal solution. Moreover, it improves the computation efficiency by 50% and energy saving by 3.5%, compared with the PMP, while ensuring good drivability and fuel efficiency.

Document type: Article

Assessing the Potential of Short Sea Shipping and the Benefits in Terms of External Costs: Application to the Mediterranean Basin

Scipedia content — Tue, 23 Mar 2021 01:07:08 +0100

The paper aims to investigate short sea shipping services as a competitive, sustainable freight transport system which is able to respond to economic, social and environmental needs. An assessment methodology is proposed which considers an aggregate discrete choice model, simulating the split between the competitive transport alternatives in the Mediterranean basin. The proposed methodology was used to assess the potential of short sea shipping (SSS) and the net benefits deriving from lower external costs in the north-western Mediterranean basin. Two future scenarios are considered: introduction of new SSS services as envisaged by current EU projects and plans, and the introduction of new SSS routes and an increase in frequencies of existing services. Significant results were obtained in terms of shifting freight traffic from the road network as well as external benefits.

Document type: Article

How Much Space Is Required? Effect of Distance, Content, and Color on External Human–Machine Interface Size

Scipedia content — Tue, 23 Mar 2021 01:08:49 +0100

The communication of an automated vehicle (AV) with human road users can be realized by means of an external human–machine interface (eHMI), such as displays mounted on the AV’s surface. For this purpose, the amount of time needed for a human interaction partner to perceive the AV’s message and to act accordingly has to be taken into account. Any message displayed by an AV must satisfy minimum size requirements based on the dynamics of the road traffic and the time required by the human. This paper examines the size requirements of displayed text or symbols for ensuring the legibility of a message. Based on the limitations of available package space in current vehicle models and the ergonomic requirements of the interface design, an eHMI prototype was developed. A study involving 30 participants varied the content type (text and symbols) and content color (white, red, green) in a repeated measures design. We investigated the influence of content type on content size to ensure legibility from a constant distance. We also analyzed the influence of content type and content color on the human detection range. The results show that, at a fixed distance, text has to be larger than symbols in order to maintain legibility. Moreover, symbols can be discerned from a greater distance than text. Color had no content overlapping effect on the human detection range. In order to ensure the maximum possible detection range among human road users, an AV should display symbols rather than text. Additionally, the symbols could be color-coded for better message comprehension without affecting the human detection range.

Document type: Article

The Shape of a Vehicle Windshield Affects Reaction Time and Brain Activity During a Target Detection Task

Scipedia content — Tue, 23 Mar 2021 01:26:26 +0100

Background: Achieving clear visibility through a windshield is one of the crucial factors in manufacturing a safe and comfortable vehicle. The optic flow (OF) through the windshield has been reported to divert attention and could impair visibility. Although a growing number of behavioral and neuroimaging studies have assessed drivers' attention in various driving scenarios, there is still little evidence of a relationship between OF, windshield shape, and driver's attentional efficacy. The purpose of this research was to examine this relationship. Methods: First, we quantified the OF across the windshield in a simulated driving scenario with either of two types of the windshield (a tilted or vertical pillar) at different speeds (60 km/h or 160 km/h) and found more upward OF along the tilted pillar than along the vertical pillar. Therefore, we hypothesized that the predominance of upward OF around the windshield along a tilted pillar could distract a driver and that we could observe the corresponding neural activity. Magnetic resonance scans were then obtained while the subjects performed a visual detection task while watching the driving scene used in the OF analysis. The subjects were required to press a button as rapidly as possible when a target appeared at one of five positions (leftmost, left, center, right, and rightmost). Results: We found that the reaction time (RT) on exposure to a tilted pillar was longer than that on exposure to a vertical pillar in the leftmost and rightmost conditions. Furthermore, there was more brain activity in the precuneus when the pillar was tilted than when it was vertical in the rightmost condition near the pillar. In a separate analysis, activation in the precuneus was found to reflect relative changes in the amount of upward OF when the target was at the rightmost position. Conclusions: Overall, these observations suggest that activation in the precuneus may reflect extraneous cognitive load driven by upward OF along the pillar and could distract visual attention. The findings of this study highlight the value of a cognitive neuroscientific approach to research and development in the motor vehicle manufacturing industry.

Document type: Article

Design of Real-Time Dynamic Reversible Lane in Intelligent Cooperative Vehicle Infrastructure System

Scipedia content — Tue, 23 Mar 2021 01:33:25 +0100

The rapidly growing traffic demand and the slowly increasing traffic supply have produced an mounting contradiction, which is mainly manifested in cities as road congestion and unbalanced bidirectional traffic flow. Most of the reversible lanes are implemented on fixed sections and fixed times and are mainly guided by ground markings, road signs, railings, and traffic police officer. It requires a lot of human and material costs. And, the control effect is lagging and inaccurate. Aiming at these problems, a real-time dynamic reversible lane scheme in the Intelligent Cooperative Vehicle Infrastructure System (CVIS) was proposed. Traffic information was collected in real time through the CVIS, and a reversible lane scheme was established based on the real-time service level "mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"""mml:mi"V"/mml:mi""mml:mo"/"/mml:mo""mml:mi"C"/mml:mi""/mml:math" and BRP functions. A lane change control model was applied to determine the number of lanes and the timing of lane changes. Then, the reversible lanes were managed in real time through intelligent road stud lights and light curtain walls. Buffer sections and no-entry sections were set to ensure reversible lanes operating safely and efficiently. VISSIM simulation was used for case analysis, and the results showed that compared with the traditional time-controlled reversible lane scheme, the real-time dynamic reversible lane scheme could reduce the average vehicle delay by 27.4% and decrease the vehicle VOC, CO and NO"jats:sub"X"/jats:sub" emissions by 13.5%.

Document type: Article

A Novel Algorithm for Controlling Active and Reactive Power Flows of Electric Vehicles in Buildings and Its Impact on the Distribution Network

Scipedia content — Tue, 23 Mar 2021 02:11:29 +0100

In the literature, many optimization algorithms were developed to control electrical loads, especially Electric Vehicles (EVs) in buildings. Despite the success of the existing algorithms in improving the power profile of charging EVs and reducing the total electricity bill of the end-users, these algorithms didn&rsquo

t show significant contribution in improving the voltage profile on the network, especially with the existence of highly inductive loads. The control of the active power may not be sufficient to regulate the voltage, even if sophisticated optimization algorithms and control strategies are used. To fill the gap in the literature, we propose a new algorithm that is able to control both the active and reactive power flows using electric vehicles in buildings and homes. The algorithm is composed of two parts

the first part uses optimization to control the active power and minimize the electricity bill, while the second part controls the reactive power using the bidirectional converter in the EV in a way that the voltage profile on the distribution transformer respects its limits. The new approach is validated through a comparative study of four different scenarios, (i) without EV, (ii) with EV using uncoordinated charging, (iii) with EV using coordinated charging, (iv) with EV using our proposed algorithm. Results show that our algorithm has maintained the voltage within the recommended limits, and it has minimized the peak load, the electricity cost, and the techno-economic losses on the network.

Document type: Article

A Comparative Study on Drivers’ Stop/Go Behavior at Signalized Intersections Based on Decision Tree Classification Model

Scipedia content — Tue, 23 Mar 2021 02:15:14 +0100

The stop/go decisions at signalized intersections are closely related to driving speed during signal change intervals. The speed during stop/go decision-making has a significant influence on the dilemma area, resulting in changes of stop/go decisions and high complexity of the decision-making process. Considering that traffic delays and vehicle exhaust pollution are mainly caused by queuing at intersections, the stop-line passing speed during the signal change interval will affect both vehicle operation safety and the atmospheric environment. This paper presents a comparative study on drivers’ stop/go behaviors when facing a transition signal period consisting of 3 s green flashing light (FG) and 3 s yellow light (Y) at rural high-speed intersections and urban intersections. For this study, 1,459 high-quality vehicle trajectories of five intersections in Shanghai during the transition signal period were collected. Of these five intersections, three are high-speed intersections with a speed limit of 80 km/h, and the other two are urban intersections with a speed limit of 50 km/h. Trajectory data of these vehicle samples were statistically analyzed to investigate the general characteristics of potential influencing factors, including the instantaneous speed and the distance to the intersection at the start of FG, the vehicle type, and so on. Decision Tree Classification (DTC) models are developed to reveal the relationship between the drivers’ stop/go decisions and these possible influencing factors. The results indicate that the instantaneous speed of FG onset, the distance to the intersection at the start of FG, and the vehicle type are the most important predictors for both types of intersections. Besides, a DTC model can offer a simple way of modeling drivers’ stopping decision behavior and produce good results for urban intersections.

Document type: Article

Assessing Gender Gaps in Educational Provision, Research and Employment Opportunities in the Transport Sector at the European Level

Scipedia content — Tue, 23 Mar 2021 02:20:51 +0100

Serious gaps are found when evaluating the recognition and inclusion of gender aspects in transport strategies, research and innovation. Similar issues can be spotted in the transport labor market, where only 22% of workers are women at the European level. The roots of these limitations are in the low participation of women in Science, Technology, Engineering and Maths (STEM) studies and, therefore, in the traditionally male-dominated transport field occupations. Stemming from the European project TInnGO, the current paper proposes a descriptive analysis to evaluate the gender gaps in educational provision and research in ten European countries. Specific indicators, such as percentages in the gender composition or the presence of university courses dealing with mobility and transport, have been defined and their availability in different countries is verified. In addition, a desktop review of practices for encouraging and supporting women in STEM studies is operated, underling characteristics such as the kind of initiative, the methods and tools used, the target group or the type of promoter. The results of this activity show that a wide network of associations and mentoring operates in various European nations, mostly targeting secondary school students, trying to make females aware of their potentialities in a deeply gender-biased field like the STEM one.

Document type: Article

Evaluating pedestrian and cyclist behaviour at a level crossing

Scipedia content — Tue, 23 Mar 2021 02:30:18 +0100

The article gives an overview about the results of the use of a newly developed measurement technique in order to analyse the behaviour of road users at level crossings. For the test of the measurement technique a before/after design was chosen in order to evaluate the effects of a speed bump on the behaviour of road users and on safety at level crossings. The measurement technique combines the use of (1) an infrared camera and (2) conventional video recording. The use of an infrared camera allows the registration of variables such as speed, position, distance and acceleration independent of lighting conditions. A conventional camera includes recording of road users' head movements on the basis of which one can conclude where their attention is directed. Besides the analysis of changes in motorists’ behaviour due to installation of a speed bump, data on the behaviour of vulnerable road users was also collected. The article concentrates especially on these results. It shows different forms of misconduct amongst the vulnerable road users that stems from different sources of error and could potentially lead to accidents. Crossings against red were observed as well as a negative effect of group size on the frequency of looking to the left and/or right. Generally vulnerable road users were crossing the railway mostly alone followed by crossing in pairs. Bigger groups were also observed but were more an exception like school classes or groups of recreational cyclists. The gaze behaviour of the vulnerable road users to the left and right hardly changed over the time and about two thirds of the pedestrians and cyclists were looking in at least one direction before crossing the railway. During the period without the speed bump eleven pedestrians and five cyclists were crossing the rail road while the red light was activated (none within the period where the speed bump was implemented – which might be due to the speed bump itself but cannot be ascribe to it with certainty). It can be concluded that the presented measurement technique could be suitable to be included in evaluations of the behaviour of vulnerable road users to achieve a more comprehensive format, which includes night time observations, observation of vulnerable road user behaviour and estimation of the effect of a safety measure.

Document type: Article

Modified Maintenance Network Model for Urban Rail Transit Systems Based on the Variable Coverage Radius: Evidence from Changchun City in China

Scipedia content — Tue, 23 Mar 2021 02:32:11 +0100

Network-wide maintenance lacks strong theoretical support and practical cases. However, research on this topic has entered an extensive exploratory stage; for example, new network design methods are being sought, and successful practices from traditional maintenance by line and by profession are being incorporated. This paper proposes a novel set-covering model with the variable coverage radius for the maintenance network of urban rail transit systems in the context of network-wide maintenance. The concepts of network-wide maintenance follow principles that are similar to those of bio-geography-based optimization (BBO), i.e., patterns of migration, variation, and extinction of different populations in different habitats. Therefore, a BBO algorithm is implemented with combinatorial optimization programming. Experiments from Changchun city in China show that the proposed model and algorithm are effective in fulfilling network-wide requirements through a direct tradeoff between the coverage radius and maintenance response time. In addition, the maintenance capacity and variable coverage radius of each maintenance point influence both the maintenance timeliness and resource utilization of maintenance units.

Document type: Article

Smart Edge Broker for Location-Based Transfer between Services and Distributed Data in IoT Smart Services

Scipedia content — Tue, 23 Mar 2021 02:47:29 +0100

Various kinds of smart sensors are being developed and released with the growth of sensor technology and Internet of Things (IoT) technology. IoT smart service can provide convenience in our daily lives with these smart sensors. However, the increasing number of mobile sensors and amount of data may increase latency. It may cause network congestion on a particular network. Therefore, we propose a Smart Edge Broker (SEB) to intelligently transmit data traffic generated by a smart city in this paper. SEB can prevent the traffic congestion from being transmitted or bypassed to a location where traffic is not necessary. In addition, SEB can prevent overload in a specific area between services through a location-based transfer. Plus, SEB is suitable to operate it as a fog computing model by placing it at the edge of a smart city network. We conducted a latency measurement experiment and load measurement experiment to evaluate the effectiveness of the proposed Smart Edge Broker. As a result, we found that the latency was reduced by 72%, and the CPU usage was reduced by 63% compared to when the Smart Edge Broker was not used.

Document type: Article

Maritime Transport in a Life Cycle Perspective: How Fuels, Vessel Types, and Operational Profiles Influence Energy Demand and Greenhouse Gas Emissions

Scipedia content — Tue, 23 Mar 2021 03:06:18 +0100

&ldquo

Well-to-Propeller&rdquo

Life Cycle Assessment of maritime transport was performed with a European geographical focus. Four typical types of vessels with specific operational profiles were assessed: a container vessel and a tanker (both with 2-stroke engines), a passenger roll-on/roll-off (Ro-Pax) and a cruise vessel (both with 4-stroke engines). All main engines were dual fuel operated with Heavy Fuel Oil (HFO) or Liquefied Natural Gas (LNG). Alternative onshore and offshore fuel supply chains were considered. Primary energy use and greenhouse gas emissions were assessed. Raw material extraction was found to be the most impactful life cycle stage (~90% of total energy use). Regarding greenhouse gases, liquefaction was the key issue. When transitioning from HFO to LNG, the systems were mainly influenced by a reduction in cargo capacity due to bunkering requirements and methane slip, which depends on the fuel supply chain (onshore has 64% more slip than offshore) and the engine type (4-stroke engines have 20% more slip than 2-stroke engines). The combination of alternative fuel supply chains and specific operational profiles allowed for a complete system assessment. The results demonstrated that multiple opposing drivers affect the environmental performance of maritime transport, a useful insight towards establishing emission abatement strategies.

Document type: Article

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data

Scipedia content — Tue, 23 Mar 2021 03:19:04 +0100

Current studies on traffic crash prediction mainly focus on the crash frequency and crash severity of freeways or arterials. However, collision type for urban expressway crash is rarely considered. Meanwhile, with the rapid development of urban expressway systems in China in recent years, traffic safety problems have attracted more attention. In addition, the traffic characteristics are considered to be a potentially important predictor of traffic accidents; however, their impact on crashes has been controversial. Therefore, a crash frequency predicting model for urban expressway considering collision types is proposed in this study. The loop detector traffic data and historical crash data were aggregated based on the similarities of the traffic conditions 5 minutes before crash occurrence, among which crashes were divided by collision type (rear-end collision and side-impact collision). The impact of traffic characteristics along with weather variables as well as their interactions on crash frequency was modelled by using negative binomial regression model. The results indicated that the influence of traffic and weather factors on two collision types shared similar trend, but different level. For rear-end collisions, crash frequency increased with lower average speed and high traffic volume under low speed limit. And when the speed limit is high, higher average speed coupled with larger volume increases the probability of crash. Higher average speed and traffic volume increase the probability of side-impact collisions, without being affected by the speed limit. The findings of the present study could help to determine efficient safety countermeasures aimed at improving the safety performance of urban expressway.

Document type: Article

A framework for describing interaction between human operators and autonomous, automated, and manual control systems

Scipedia content — Tue, 23 Mar 2021 03:31:36 +0100

This paper addresses how to describe critical episodes of interaction between human operators and autonomous, automated, and manual control systems. The first part of the paper poses three questions: (1) what levels of cognitive control are important to include in a descriptive framework for joint human-autonomy in process control; (2) how should one describe temporal developments in joint socio-technical systems; and (3) how does one analyse communication and control at the system joints. The paper proceeds by proposing a new framework for description and analysis, the Joint Control Framework (JCF), with a simple notation, the Score (JCF-S). It allows descriptions of the three previously mentioned aspects through three analytical activities: process mapping (PM), analysis of Levels of Autonomy in Cognitive Control (LACC), and temporal descriptions of human-machine interaction (T-HMI) through the Score notation. This facilitates analyses across cases and domains. The framework is discussed based on an analysis of two episodes; one work episode (from an air traffic control tower simulator); and one work procedure (from an unmanned traffic management system design concept). "p"Funding Agencies|Linkoping University - Swedish Transport Administration; Air Navigation Services of Sweden

Document type: Article

Does a Confidence Level for Automated Driving Time Estimations Improve the Subjective Evaluation of an Automation HMI?

Scipedia content — Tue, 23 Mar 2021 03:43:38 +0100

Current research in human factors and automated driving is increasingly focusing on predictable transitions instead of urgent and critical take-overs. Predictive human–machine interface (HMI) elements displaying the remaining time until the next request to intervene were identified as a user need, especially when the user is engaging in non-driving related activities (NDRA). However, these estimations are prone to errors due to changing traffic conditions and updated map-based information. Thus, we investigated a confidence display for Level 3 automated driving time estimations. Based on a preliminary study, a confidence display resembling a mobile phone connectivity symbol was developed. In a mixed-design driving simulator study with 32 participants, we assessed the impact of the confidence display concept (within factor) on usability, frustration, trust and acceptance during city and highway automated driving (between factor). During automated driving sections, participants engaged in a naturalistic visual NDRA to create a realistic scenario. Significant effects were found for the scenario: participants in the city experienced higher levels of frustration. However, the confidence display has no significant impact on the subjective evaluation and most participants preferred the baseline HMI without a confidence symbol.

Document type: Article

CoDR: Correlation-based Data Reduction Scheme for Efficient Gathering of Heterogeneous Driving Data

Scipedia content — Tue, 23 Mar 2021 03:45:56 +0100

A variety of deep learning techniques are actively employed for advanced driver assistance systems, which in turn require gathering lots of heterogeneous driving data, such as traffic conditions, driver behavior, vehicle status and location information. However, these different types of driving data easily become more than tens of GB per day, forming a significant hurdle due to the storage and network cost. To address this problem, this paper proposes a novel scheme, called CoDR, which can reduce data volume by considering the correlations among heterogeneous driving data. Among heterogeneous datasets, CoDR first chooses one set as a pivot data. Then, according to the objective of data collection, it identifies data ranges relevant to the objective from the pivot dataset. Finally, it investigates correlations among sets, and reduces data volume by eliminating irrelevant data from not only the pivot set but also other remaining datasets. CoDR gathers four heterogeneous driving datasets: two videos for front view and driver behavior, OBD-II and GPS data. We show that CoDR decreases data volume by up to 91%. We also present diverse analytical results that reveal the correlations among the four datasets, which can be exploited usefully for edge computing to reduce data volume on the spot.

Document type: Article

Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection

Scipedia content — Tue, 23 Mar 2021 04:07:09 +0100

Drowsy driving imposes a high safety risk. Current systems often use driving behavior parameters for driver drowsiness detection. The continuous driving automation reduces the availability of these parameters, therefore reducing the scope of such methods. Especially, techniques that include physiological measurements seem to be a promising alternative. However, in a dynamic environment such as driving, only non- or minimal intrusive methods are accepted, and vibrations from the roadbed could lead to degraded sensor technology. This work contributes to driver drowsiness detection with a machine learning approach applied solely to physiological data collected from a non-intrusive retrofittable system in the form of a wrist-worn wearable sensor. To check accuracy and feasibility, results are compared with reference data from a medical-grade ECG device. A user study with 30 participants in a high-fidelity driving simulator was conducted. Several machine learning algorithms for binary classification were applied in user-dependent and independent tests. Results provide evidence that the non-intrusive setting achieves a similar accuracy as compared to the medical-grade device, and high accuracies (>

92%) could be achieved, especially in a user-dependent scenario. The proposed approach offers new possibilities for human&ndash

machine interaction in a car and especially for driver state monitoring in the field of automated driving.

Document type: Article

Multiagent Reinforcement Learning-Based Taxi Predispatching Model to Balance Taxi Supply and Demand

Scipedia content — Tue, 23 Mar 2021 04:14:05 +0100

With the improvement of people’s living standards, people’s demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; taxi drivers usually rely on their operational experience or cruise randomly to find passengers. Without macroguidance, the role of the taxi system cannot be fully utilized. Many scholars have studied taxi behaviors to find better operational strategies for drivers, but their researches rely on local optimization methods to improve the profit of drivers, which will lead to imbalance between supply and demand in the city. To solve this problem, we propose a Multiagent Reinforcement Learning- (MARL-) based taxi predispatching model through analyzing the running data of 13,000 taxis. Different from other methods of scheduling taxis based on the real-time location of orders, our model first predicts the demand for taxis in different regions in the next period and then dispatches taxis in advance to meet the future requirement; thus, the number of taxis needed and available in different regions can be balanced. Besides, in order to reduce computational complexity, we propose several methods to reduce the state space and action space of reinforcement learning. Finally, we compare our method with another taxi dispatching method, and the results show that the proposed method has a significant improvement in vehicle utilization rate and passenger demand satisfaction rate.

Document type: Article

Evaluating the impact of new aircraft separation minima on available airspace capacity and arrival time delay

Scipedia content — Tue, 23 Mar 2021 04:25:08 +0100

Although the application of new, reduced aircraft separation minima can directly increase runway throughput, the impact thereof on the traffic flow of aircraft arriving at the destination airport has not been discussed yet. This paper proposes a data-driven and queue-based modeling approach and presents an analysis of the impact on the delay time of arriving aircraft in the airspace within a radius of 100 nautical miles around an airport. The parameters of our queuing model were estimated by analysing the data contained in the radar tracks and flight plans for flights that arrived at Tokyo International Airport during the 2 years of 2016 and 2017. The results clarified the best arrival strategy according to the distance from the arrival airport: The combination of airspace capacity control and reduction of the flight time and separation variance is the most powerful solution to mitigate delays experienced by arriving traffic while also allowing an increase in the amount of arrival traffic. The application of new wake vortex categories would enable us to increase the arrival traffic to 120%. In addition, the arrival delay time could be minimised by implementing the proposed arrival traffic strategies together with automation support for air traffic controllers.

Document type: Article

Coatings & linings for oil & gas pipelines – the most effective method of corrosion protection for aged pipelines

Scipedia content — Tue, 23 Mar 2021 04:35:01 +0100

Pipelines around the world are in danger due to ageing, deposits and corrosion. Leaky fittings and cracks are an environmental hazard and cause the loss of valuable resources such as drinking water, gas, or oil. The pipelines may get corroded internally due to the nature of the fluid flowing inside and due to various other factors. The environmental and societal impact of infrastructure failure is a primary consideration for today’s pipeline operators. Without implementing safety measures and having a corrosion control program, corrosion makes transporting hazardous material unsafe. There are many methods NACE (National Association of Corrosion Engineers) recommends as part of a successful corrosion control program to protect oil and gas pipelines. Coatings and linings applied to pipelines whether above or below ground and often used in combination with cathodic protection. Different linings may be used for internal corrosion protection, provided the lining material does not degrade following long-term exposure to the transported fluid, at the pipeline pressure and temperature conditions.

Document type: Article

Evaluating Cyclists’ Route Preferences with Respect to Infrastructure

Scipedia content — Tue, 23 Mar 2021 04:39:34 +0100

Providing a sufficiently appropriate route environment is crucial to ensuring fair and safe biking, thus encouraging cycling as a sustainable mode of transport. At the same time, better understanding of cyclists&rsquo

preferences regarding the features of their routes and their infrastructure requirements is fundamental to evaluating improvement of the current infrastructure or the development of new infrastructure. The present study has two objectives. The first is to investigate cyclists&rsquo

route preferences by means of a choice experiment based on a stated preference survey. Subsequently, the second objective is to compare cyclist preferences in two countries with different cycling characteristics (both in infrastructure as well as cyclists&rsquo

behavior). For this purpose, a graphical online stated preferences survey was conducted in Greece and Germany. Within the framework of statistical analyses, multinomial mixed logit discrete choice models were developed that allow us to quantify the trade-offs of interest, while distinguishing between the preferences of different user groups. In addition, user requirements in Greece, as a country with a low cycling share and very little dedicated bike infrastructure, were compared to the requirements in Germany, where cycling is popular and the infrastructure is well developed. The results over the whole sample indicate that subgroups value infrastructure differently according to their specific needs. When looking at country specifics, users from Greece are significantly more willing to accept longer travel times in return for higher-quality facilities. The utility of low speed limits in mixed traffic is also different. In Germany, low speed limits offset the disturbance caused by motorized traffic, but in Greece they do not. Consequently, the results help to asses which types of infrastructure are most sustainable from a user perspective and help to set priorities when the aim is to adapt the road infrastructure efficiently in a stable strategy.

Document type: Article

Efficient Paradigm to Measure Street-Crossing Onset Time of Pedestrians in Video-Based Interactions with Vehicles

Scipedia content — Tue, 23 Mar 2021 04:44:33 +0100

With self-driving vehicles (SDVs), pedestrians can no longer rely on a human driver. Previous research suggests that pedestrians may benefit from an external Human–Machine Interface (eHMI) displaying information to surrounding traffic participants. This paper introduces a natural methodology to compare eHMI concepts from a pedestrian’s viewpoint. To measure eHMI effects on traffic flow, previous video-based studies instructed participants to indicate their crossing decision with interfering data collection devices, such as pressing a button or slider. We developed a quantifiable concept that allows participants to naturally step off a sidewalk to cross the street. Hidden force-sensitive resistor sensors recorded their crossing onset time (COT) in response to real-life videos of approaching vehicles in an immersive crosswalk simulation environment. We validated our method with an initial study of N = 34 pedestrians by showing (1) that it is able to detect significant eHMI effects on COT as well as subjective measures of perceived safety and user experience. The approach is further validated by (2) replicating the findings of a test track study and (3) participants’ reports that it felt natural to take a step forward to indicate their street crossing decision. We discuss the benefits and limitations of our method with regard to related approaches.

Document type: Article

What are the factors and needs promoting mobility-as-a-service? Findings from the Swiss Household Energy Demand Survey (SHEDS)

Scipedia content — Tue, 23 Mar 2021 04:49:04 +0100

Mobility-as-a-Service (MaaS) is a service that supports customers’ transportation needs by providing information and ticketing for a multitude of transport modes in one interface; thus, buy potentially fostering multimodality and public transport, it represents an important lever to reduce negative transportation impacts such as emissions and congestion. By means of an online survey conducted in Switzerland, we try to understand potential user needs as well as factors that would motivate the use of MaaS. Comparing the openness to use MaaS for specific trip purposes like commuting and leisure activities, we find the lowest level of openness for commuting and the highest for weekend leisure trips. Intention to reduce car usage was positively related to openness to MaaS in commuting. On the other hand, factors that positively influence openness to using MaaS for leisure activities include a higher education degree, experience with carsharing and the use of transport-related climate policy announcements directly affecting consumers. These findings suggest focusing specifically on either commuting or leisure activities when designing policy measures. ISSN:1867-0717 ISSN:1866-8887

Document type: Article

Profitability of Frequency Regulation by Electric Vehicles in Denmark and Japan Considering Battery Degradation Costs

Scipedia content — Tue, 23 Mar 2021 04:54:24 +0100

This paper determines the profitability of the primary frequency regulation (FR) service considering the wear of the electric vehicle (EV) battery as a cost. To evaluate the profitability of the FR service, the cost of degradation from FR provision is separated from the degradation caused by driving usage. During FR, the power response is proportional to the frequency deviation with full activation power of 9.2 kW, when deviations are larger than 100 mHz. The degradation due to FR is found to be an additional 1–2% to the 7–12% capacity reduction of a 40 kWh Lithium-ion NMC battery pack over 5 years. The overall economic framework is applied in Denmark, both DK1 and DK2, and Japan, by considering historical frequencies. The DK2 FR market framework is taken as reference also for the Japanese and the DK1 cases. Electricity prices and charger efficiency are the two main parameters that affect the profitability of the service. Indeed, with domestic prices there is no profitability, whereas with industrial prices, despite differences between the frequencies, the service is similarly profitable with approx. 3500€ for a five-year period.

Document type: Article

A systematic review of indicators to assess the sustainability of road infrastructure projects

Scipedia content — Tue, 23 Mar 2021 04:56:32 +0100

Background: This study aims to examine to what extent sustainability has been incorporated into assessments of road infrastructure projects. It identifies promising approaches that include indicators reflecting core sustainability criteria, determines criteria that were insufficiently covered as indicators, and develops an integrated indicator set covering all criteria. Methods: A systematic review was performed to obtain all related papers/reports in two academic databases: Scopus and Web of Sciences. The indicators extracted from papers/reports were first coded, then evaluated by using quantitative and qualitative content analysis. Results: The project appraisal methods for decision-making is found to be a promising approach, covering more extensive criteria than others. Two criteria – namely adaptation and precaution and intergenerational equity – were hardly ever adopted as indicators. Ten main groups of indicators were extracted to construct an integrated set incorporating all core criteria. Conclusions: Some criteria appear to have become mainstream, while others deserve attention. The safest choice is to combine methods/tools or to adopt the integrated set developed for exhaustive criteria inclusion.

Document type: Article

Fuel Economy in Truck Platooning: A Literature Overview and Directions for Future Research

Scipedia content — Tue, 23 Mar 2021 05:03:21 +0100

A truck platoon is a set of virtually linked trucks that travel in tandem with small intervehicle distances. Several studies have proved that traveling in platoons can significantly improve fuel economy due to the reduced aerodynamic drag. However, most literature only provides scattered pieces of information regarding fuel economy in truck platoons. Therefore, a literature survey is needed to understand what has been studied and what problems remain to be further addressed. This paper presents an overview of existing studies to illustrate the state of the art about fuel savings for truck platooning. Specifically, it summarized the methodologies, the contributing factors of fuel consumption, the coordination methods to improve the platooning rate, and the look-ahead control strategies to generate fuel-efficient speed profiles for each vehicle driving in a platoon over different road grades. After that, the autonomous truck platooning was introduced, and we raised and discussed a couple of outstanding questions to be addressed in future work.

Document type: Article

Features of Earthquake-Induced Seabed Liquefaction and Mitigation Strategies of Novel Marine Structures

Scipedia content — Tue, 23 Mar 2021 05:28:41 +0100

With the accelerated development of marine engineering, a growing number of marine structures are being constructed (e.g., seabed pipelines, drilling platforms, oil platforms, wind turbines). However, seismic field investigations over recent decades have shown that many marine structures were damaged or destroyed due to liquefaction. Seismic liquefaction in marine engineering can have huge financial repercussions as well as a devastating effect on the marine environment, which merits our great attention. As the effects of seawater and the gas component in the seabed layers are not negligible, the seabed soil layers are more prone to liquefaction than onshore soil layers, and the liquefied area may be larger than when liquefaction occurs on land. To mitigate the impact of liquefaction events on marine engineering structures, some novel liquefaction-resistant marine structures have been proposed in recent years. This paper reviews the features of earthquake-induced liquefaction and the mitigation strategies for marine structures to meet the future requirements of marine engineering.

Document type: Article

Heterogenous Trip Distance-Based Route Choice Behavior Analysis Using Real-World Large-Scale Taxi Trajectory Data

Scipedia content — Tue, 23 Mar 2021 05:33:26 +0100

Most early research on route choice behavior analysis relied on the data collected from the stated preference survey or through small-scale experiments. This manuscript focused on the understanding of commuters’ route choice behavior based on the massive amount of trajectory data collected from occupied taxicabs. The underlying assumption was that travel behavior of occupied taxi drivers can be considered as no different than the well-experienced commuters. To this end, the DBSCAN algorithm and Akaike information criterion (AIC) were first used to classify trips into different categories based on the trip length. Next, a total of 9 explanatory variables were defined to describe the route choice behavior, and and the path size (PS) logit model was then built, which avoided the invalid assumption of independence of irrelevant alternatives (IIA) in the commonly seen multinomial logit (MNL) model. The taxi trajectory data from over 11,000 taxicabs in Xi’an, China, with 40 million trajectory records each day were used in the case study. The results confirmed that commuters’ route choice behavior are heterogenous for trips with varying distances and that considering such heterogeneity in the modeling process would better explain commuters’ route choice behaviors, when compared with the traditional MNL model.

Document type: Article

“Gas pipeline wars” in the post-Soviet space: geographical aspect

Scipedia content — Tue, 23 Mar 2021 06:24:13 +0100

The article discusses the transformation of the territorial organization of gas pipeline transport in the post-Soviet period under the influence of the system of international relations that developed between the countries of the post-Soviet space. Notably, the author establishes the following major geographical factors affecting this process: the level of provision with natural gas and the peculiarities of the transport and geographical position of the countries. The author specifically emphasizes an active, consistent and purposeful policy on this issue in Russia, Azerbaijan, Kazakhstan, and Turkmenistan, which reinforces and strengthens the geopolitical interests of these states in the examined region. Their competitive advantages are clearly indicated. Particular attention is focused on the possibility of multipurpose use of gas pipelines thanks to the connecting pipes created between them. The interest intersection of three categories of states was revealed: those of the countries in the post-Soviet space (Russia, Ukraine, Azerbaijan, Turkmenistan, Kazakhstan, Uzbekistan); those of Russia and countries located in the neighboring regions (EU, China, Turkey, Iran); those of the states actively involved in investing in geological exploration, creation of mining enterprises, gas storages, construction of compressor stations on them (USA, Great Britain, Saudi Arabia, Japan, etc.).

Document type: Article

DroneBased Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

Scipedia content — Tue, 23 Mar 2021 06:33:55 +0100

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

Document type: Article

A Model for Sustainable Courier Services: Vehicle Routing with Exclusive Lanes

Scipedia content — Tue, 23 Mar 2021 06:36:32 +0100

In Southeast Asian cities, it is common for logistic companies to operate a heterogeneous fleet of delivery vehicles with motorcycles being the preferred vehicle to handle the final phase of delivery. In such scenarios, heterogeneous fleet vehicle routing problem (HFVRP) is generally applied to plan an optimal delivery. However, in many downtown cores of large and rapidly developing Southeast Asian cities, HFVRP is neither viable nor reliable because of road usage restrictions. The purpose of this article is to develop and test a different approach that accurately takes these restrictions into account and provides viable and more sustainable results. Restrictions in this paper refer to situations of urban areas in Vietnam where (i) certain vehicle types are prohibited in specified areas or where narrow alleyways limit the utilization of vehicles that exceed the road capacity and (ii) certain roads are exclusive to certain vehicle types. In networks, limited access and exclusive lanes are represented as links, or arcs, exclusive to one or another. Taking these limitations into consideration, we have developed a unique model, which we have termed Vehicle Routing Problem with Exclusive Links (VRP-EL). The model was validated and tested for its performance on scenarios with varying ratios of exclusive links. Scenarios up to 500 customers were tested on a meta-heuristic algorithm, simulated annealing. VRP-EL produces realistic outcomes. Limiting certain links to be selected according to vehicle types increases overall travel distance. However, this increase outweighs the cost of re-planning and rerouting had they not been constrained initially. The reduction in traveling distance leads to fossil fuel reduction for the overall system. The estimation of reduced carbon emissions through applying the proposed model is presented. Considering the severe traffic congestion and carbon emissions caused by motorcycles in Vietnam, the proposed model leads to a sustainable road environment.

Document type: Article

Research on Joint Control of On-Ramp Metering and Mainline Speed Guidance in the Urban Expressway Based on MPC and Connected Vehicles

Scipedia content — Tue, 23 Mar 2021 06:55:34 +0100

The traffic operational efficiency of the urban expressway system will affect one of the entire cities. Moreover, the idea that traffic control can improve the traffic operational efficiency of the urban expressway system has been fully confirmed. At present, the main control methods include on-ramp metering and speed guidance control. However, there is a gap in using these two control methods together, such as unclear application conditions and unsystematic methods. In this paper, on-ramp metering and speed guidance control are combined effectively. Based on the research of METANET macroscopic traffic flow model and model predictive control (MPC), a novel joint control method based on MPC and connected vehicles (CVs) for on-ramp metering and speed guidance control of the urban expressway is proposed. Finally, the simulation results show that the proposed control method can effectively improve the traffic efficiency and traffic safety.

Document type: Article