Documents published in 2020 : Scipedia

General-purpose hierarchical optimisation of machine learning pipelines with grammatical evolution
A. Montoyo, Y. Almeida-Cruz, Y. Gutiérrez, S. Estevez-Velarde

Collection of closed articles in transport research (2020). Vol. 2020, 54

Abstract
This paper introduces Hierarchical Machine Learning Optimisation (HML-Opt), an AutoML framework that is based on probabilistic grammatical evolution. HML-Opt has been designed to provide a flexible framework where a researcher can define the space of possible pipelines to solve a specific machine learning problem, which can range from high-level decisions about representation and features to low-level hyper-parameter values. The evaluation of HML-Opt is presented via two different case studies, both of which demonstrate that it is competitive with existing AutoML tools on a variety of benchmarks. Furthermore, HML-Opt can be applied to novel problems, such as knowledge extraction from natural language text, whereas other techniques are insufficiently flexible to capture the complexity of these scenarios. The source code for HML-Opt is available online for the research community. This research has been supported by a Carolina Foundation grant in agreement with University of Alicante and University of Havana. Moreover, it has also been partially funded by both aforementioned universities, the Generalitat Valenciana (Conselleria d’Educació, Investigació, Cultura i Esport) and the Spanish Government through the projects LIVING-LANG (RTI2018-094653-B-C22) and SIIA (PROMETEO/2018/089, PROMETEU/2018/089).
Abstract
This paper introduces Hierarchical Machine Learning Optimisation (HML-Opt), an AutoML framework that is based on probabilistic grammatical evolution. HML-Opt has been designed [...]
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The most difficult at-fault fatal crashes to avoid with current active safety technology
R. Utriainen, T. Koisaari, T. Kari, T. Tervo

Collection of closed articles in transport research (2020). Vol. 2020, 53

Abstract
Objective: We studied which current fatal at-fault crashes would occur despite the most advanced current active safety devices (up to SAE level 2 of driving automation) and how frequent these crashes would be. Methods: We carried out a cross-sectional study of passenger cars that were first registered during the period 1st January 2010 to 31st December 2017 in Finland. To gain the true exposure for these cars, we accessed the national Vehicular and Driver Data Register to obtain the mileage information and the registration count for the study period of 2010-17. Similarly, we accessed the registry of Finnish road accident investigation teams and included all fatal at-fault crashes among the cars in our study for the same period. We used a real world reference technology for each active safety system in our analysis and chose one car brand as an example. This gave us exact system specifications and enabled testing the operation of the systems on the road. We performed field tests to gain further information on the precise operation of the safety systems in different operating conditions. Finally, we gathered all information on the studied active safety systems and analyzed the investigated at-fault fatal crashes case-by-case using our four level method. Results: Cars in our study were the primary party in 113 investigated fatal accidents during the years 2010-17. In 87 of the accidents, the leading cause of death was the injuries due to the crash, and these cases were classified as “unavoidable” (n = 58, 67 %), “avoidable” (n = 26, 30 %) or unsolved (n = 3, 3 %). Of the 58 “unavoidable” crashes 21 (36 %) were suicides, 21 (36%) involved active driver input which would have prevented the safety system operation, 15 (17 %) featured circumstances beyond the safety system performance and in one loss-of-control crash the driver had disabled the relevant safety system (electronic stability control). The registration years of the cars in our study (2010-17) totaled 3,772,864 and during this period, the cars travelled 75.9billion kilometers. The crash incidence of the “unavoidable” at-fault fatal crashes was 0.76-0.80 fatal crashes per billion kilometers and 15-16 fatal crashes per million registration years. Conclusions: We calculated a crash incidence for the “unavoidable” crashes which was 20–27% smaller than the observed crash rate of ESC-fitted passenger cars in our previous study. We concluded that suicides, active driver input until the crash, and challenging weather and road conditions are the most difficult factors for current active safety systems. Our analysis did not account for issues such as system usability or driver acceptance and therefore our results should be regarded as something that is currently theoretically achievable. However, the observed incidence is a good reference for automated driving development and the crash rate of automated cars. Peer reviewed
Abstract
Objective: We studied which current fatal at-fault crashes would occur despite the most advanced current active safety devices (up to SAE level 2 of driving automation) and [...]
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Is the H2 economy realizable in the foreseeable future? Part II: H2 storage, transportation, and distribution
C. Louis, N. Lymperopoulos, N. Muthuswamy, N. Muthuswamy, M. Buan, C. Flox, A. Iranzo, X. Shi, A. Kannan, K. Tammeveski, E. Veziroglu, S. Chavan, P. Kauranen, E. Carcadea, G. Maia, J. Prakash, H. Nazir, T. Kallio, S. Jose

Collection of closed articles in transport research (2020). Vol. 2020, 51

Abstract
The goal of the review series on the H2 economy is to highlight the current status, major issues, and opportunities associated with H2 production, storage, transportation, distribution and usage in various energy sectors. In particular, Part I discussed the various H2 (grey and green) production methods including the futuristic ones such as photoelectrochemical for small, medium, and large-scale applications. Part II of the H2 economy review identifies the developments and challenges in the areas of H2 storage, transportation and distribution with national and international initiatives in the field, all of which suggest a pathway for establishing greener H2 society in the near future. Currently, various methods, comprising physical and chemical routes are being explored with a focus on improving the H2 storage density, capacity, and reducing the cost. H2 transportation methods by road, through pipelines, and via ocean are pursued actively in expanding the market for large scale applications around the world. As of now, compressed H2 and its transportation by road is the most realistic option for the transportation sector. Peer reviewed
Abstract
The goal of the review series on the H2 economy is to highlight the current status, major issues, and opportunities associated with H2 production, storage, transportation, [...]
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A review of silhouette extraction algorithms for use within visual hull pipelines
G. Ascenso, T. Allen, C. Payton, M. Yap, S. Choppin

Collection of closed articles in transport research (2020). Vol. 2020, 50

Abstract
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Markerless motion capture would permit the study of human biomechanics in environments where marker-based systems are impractical, e.g. outdoors or underwater. The visual hull tool may enable such data to be recorded, but it requires the accurate detection of the silhouette of the object in multiple camera views. This paper reviews the top-performing algorithms available to date for silhouette extraction, with the visual hull in mind as the downstream application; the rationale is that higher-quality silhouettes would lead to higher-quality visual hulls, and consequently better measurement of movement. This paper is the first attempt in the literature to compare silhouette extraction algorithms that belong to different fields of Computer Vision, namely background subtraction, semantic segmentation, and multi-view segmentation. It was found that several algorithms exist that would be substantial improvements over the silhouette extraction algorithms traditionally used in visual hull pipelines. In particular, FgSegNet v2 (a background subtraction algorithm), DeepLabv3+ JFT (a semantic segmentation algorithm), and Djelouah 2013 (a multi-view segmentation algorithm) are the most accurate and promising methods for the extraction of silhouettes from 2D images to date, and could seamlessly be integrated within a visual hull pipeline for studies of human movement or biomechanics.
Abstract
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Markerless motion capture would permit the study of human biomechanics in environments where marker-based [...]
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A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management
A. Montlaur, Y. Xu, M. Melgosa, X. Prats, R. Dalmau

Collection of closed articles in transport research (2020). Vol. 2020, 49

Abstract
This paper proposes a collaborative air traffic flow management (ATFM) framework, in the scope of trajectory based operations, aiming to improve the cost-efficiency for airspace users (AUs) when facing ATFM regulations. The framework consists of four modules. The first one involves the AUs initially scheduling their preferred trajectories for all their flights. Based on this initial demand, the second module (assumed to be on the Network Manager -NM- side) detects time-varying hotspots (i.e. overloaded sectors along the day). In the third module, hotspot information is shared back to the AUs who plan alternative trajectory options to avoid crossing these congested airspace volumes (in the lateral and vertical domain); as well as providing to the NM different pre-tactical delay management preferences (including ground holding, linear holding, air holding and pre-tactical delay recovery); based on their internal cost breakdown structures. Incorporating all these potential combined options, the last module computes the best trajectory selections and the optimal distribution of delay assignments, such that the cost deviation from the initial status (all the user-preferred trajectories) is minimized. This model is formulated as mixed integer linear programming (MILP) and validated by a real-world case study focused on 24 h of traffic over the French airspace. Results using the proposed framework suggest a significant system delay reduction by nearly 97% over the existing method, whilst yielding an average of less than 100 kg extra fuel consumption and 50 Euro extra route charges for the 11% flights diverted to their alternative trajectories. Peer Reviewed
Abstract
This paper proposes a collaborative air traffic flow management (ATFM) framework, in the scope of trajectory based operations, aiming to improve the cost-efficiency for airspace [...]
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What drives decarbonization of new passenger cars?
T. Kuosmanen, X. Zhou

Collection of closed articles in transport research (2020). Vol. 2020, 47

Abstract
Transition towards a low-carbon transport sector fundamentally depends on decarbonization of the passenger car fleet. Therefore, it is critically important to understand the driving factors behind decreasing CO2 emissions of new passenger cars. This paper develops a new decomposition method to break down the change in the average CO2 emissions of new passenger cars into components representing changes in available technology, carbon efficiency of consumer choices, vehicle attributes, fuel mix, and the gap between type-approval and on-road CO2 emissions of passenger cars. Our decomposition draws insights from the traditional index decomposition analysis and frontier-based decomposition of productivity growth. It satisfies such desirable properties as factor reversal, time reversal, and zero-value robustness. An empirical application to a unique data set that covers all registered passenger cars in Finland sheds light on why and how the CO2 emissions of new cars decreased from year 2002 to year 2014. Peer reviewed
Abstract
Transition towards a low-carbon transport sector fundamentally depends on decarbonization of the passenger car fleet. Therefore, it is critically important to understand the [...]
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Balancing responsibilities: Effects of growth of variable renewable energy, storage, and undue grid interaction
R. Benders, H. Moll, G. Laugs

Collection of closed articles in transport research (2020). Vol. 2020, 46

Abstract
Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. However, effectiveness and usefulness of storage may vary under different circumstances. This study provides an abstract perspective on the merits of electrical energy storage integrated with decentralized supply systems consisting of solar PV and wind power in a mesolevel, residential sector context. We used a balancing model to couple demand and supply patterns based on Dutch weather data and assess the resultant loads given various scenarios. Our model results highlight differences in storage effectiveness for solar PV and wind power, and strong diminishing-returns effects. Small storage capacities can be functional in reducing surpluses in overdimensioned supply systems and shortages in under-dimensioned supply systems. However, full elimination of imbalance requires substantial storage capacities. The overall potential of storage to mitigate imbalance of variable renewable energy is limited. Integration of storage in local supply systems may have self-sufficiency and cost-effectiveness benefits for prosumers but may have additional peak load disadvantages for grid operators. Adequate policy measures beyond current curtailment strategies are required to ensure proper distribution of benefits and responsibilities associated with variable renewable energy and storage.
Abstract
Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. [...]
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Balancing responsibilities
G. Laugs, R. Benders, H. Moll

Collection of closed articles in transport research (2020). Vol. 2020, 45

Abstract
Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. However, effectiveness and usefulness of storage may vary under different circumstances. This study provides an abstract perspective on the merits of electrical energy storage integrated with decentralized supply systems consisting of solar PV and wind power in a mesolevel, residential sector context. We used a balancing model to couple demand and supply patterns based on Dutch weather data and assess the resultant loads given various scenarios. Our model results highlight differences in storage effectiveness for solar PV and wind power, and strong diminishing-returns effects. Small storage capacities can be functional in reducing surpluses in overdimensioned supply systems and shortages in under-dimensioned supply systems. However, full elimination of imbalance requires substantial storage capacities. The overall potential of storage to mitigate imbalance of variable renewable energy is limited. Integration of storage in local supply systems may have self-sufficiency and cost-effectiveness benefits for prosumers but may have additional peak load disadvantages for grid operators. Adequate policy measures beyond current curtailment strategies are required to ensure proper distribution of benefits and responsibilities associated with variable renewable energy and storage.
Abstract
Electrical energy storage is often proposed as a solution for the mismatch between supply patterns of variable renewable electricity sources and electricity demand patterns. [...]
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Liquid Organic Hydrogen Carriers and alternatives for international transport of renewable hydrogen
S. Drünert, M. Kaltschmitt, S. Timmerberg, M. Niermann

Collection of closed articles in transport research (2020). Vol. 2020, 44

Abstract
Hydrogen can be transported over long distances when stored in Liquid Organic Hydrogen Carriers (LOHC). This transport is possible under the following conversion steps: first, hydrogen is stored inside a LOHC molecule (exothermic hydrogenation) at the starting point of the provision chain. Then, the loaded LOHC can be stored and transported. At the point of consumption, hydrogen is released (endothermic de-hydrogenation) and the unloaded LOHC returns to the point of hydrogen production. The optimal LOHC for transport should be liquid at ambient conditions and show similar properties to crude oil-based liquids (e.g., diesel, gasoline). This allows for a stepwise implementation using the existing crude oil-based infrastructure. However, there is a large variety of different LOHCs and other competing transport options; e.g., the transport of compressed hydrogen gas in pipelines or the transport of liquefied hydrogen in tanker ships. Against this background, this paper investigates the energy consumption and costs of these different hydrogen transport options. Therefore, the production of hydrogen is considered in areas with favorable renewable energy sources, followed by international transport logistics, and a local distribution in Germany. The assessment shows that the distance and the way heat is supplied to de-hydrogenate the LOHCs - especially for methanol - define the cost performance compared to a transport of compressed or liquid hydrogen. If the heat needed for dehydrogenation is covered by waste heat, dibenzyltoluene (DBT) or toluene can show benefits in terms of efficiency and costs. Furthermore, the different transport systems have different specific niches in which they are competitive; i.e., no specific transportation chain is superior to all systems under all circumstances. Nevertheless, the assessment shows that long-distance transport favors LOHC, while short-distance transport via pipelines can be used for lower costs.
Abstract
Hydrogen can be transported over long distances when stored in Liquid Organic Hydrogen Carriers (LOHC). This transport is possible under the following conversion steps: first, [...]
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A data driven typology of electric vehicle user types and charging sessions
J. Helmus, M. Lees, R. van den Hoed

Collection of closed articles in transport research (2020). Vol. 2020, 42

Abstract
The understanding of charging behavior has been recognized as a crucial element in optimizing roll out of charging infrastructure. While current literature provides charging choices and categorizations of charging behavior, these seem oversimplified and limitedly based on charging data. In this research we provide a typology of charging behavior and electric vehicle user types based on 4.9 million charging transactions from January 2017 until March 2019 and 27,000 users on 7079 Charging Points the public level 2 charging infrastructure of 4 largest cities and metropolitan areas of the Netherlands. We overcome predefined stereotypical expectations of user behavior by using a bottom-up data driven two-step clustering approach that first clusters charging sessions and thereafter portfolios of charging sessions per user. From the first clustering (Gaussian Mixture) 13 distinct charging session types were found; 7 types of daytime charging sessions (4 short, 3 medium duration) and 6 types of overnight charging sessions. The second clustering (Partition Around Medoids) clustering result in 9 user types based on their distinct portfolio of charging session types. We found (i) 3 daytime office hours charging user types (ii) 3 overnight user types and (iii) 3 non-typical user types (mixed day and overnight chargers, visitors and car sharing). Three user types show significant peaks at larger battery sizes which affects the time between sessions. Results show that none of the user types display solely stereotypical behavior as the range of behaviors is more varied and more subtle. Analysis of population composition over time revealed that large battery users increase over time in the population. From this we expect that shifts charging portfolios will be observed in future, while the types of charging remain stable.
Abstract
The understanding of charging behavior has been recognized as a crucial element in optimizing roll out of charging infrastructure. While current literature provides charging [...]
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A Study on Cyclists behaviour and bicycles Kinematic
A. Micucci, M. Sangermano

Collection of closed articles in transport research (2020). Vol. 2020, 39

Abstract
study on cyclists’ behaviour and bicycle kinematic was conducted to determine the behavioural characteristics and kinetic representatives, as they are closely linked. The study focused on the behaviour of cyclists at road intersections and on cycle paths, including the crossing speeds, the accelerations, the time spent covering a fixed distance, as well as the most complex and dynamic part of the road transport system, the human factor. Whether the road users follow the laws of traffic and adopt a cautious and considerate driving attitude has a great impact on road safety. Video cameras placed at different locations were used to collect traffic data. A post processing phase to analyze the data followed. Interesting groups behaviour of cyclists were identified, as well as many characteristics curves related to the kinematic parameters. In general, a poor attitude towards compliance with behavioural rules has emerged in the medium-sized city of Bologna, Italy, especially for male cyclists. In addition, the average flow speed was observed under normal conditions, resulting in the order of 4 m/s. The results obtained are useful for understanding the performance of mixed traffic at intersection and on bicycle lanes, as well as building a basis for road accident reconstruction.
Abstract
study on cyclists’ behaviour and bicycle kinematic was conducted to determine the behavioural characteristics and kinetic representatives, as they are closely linked. The [...]
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Age effects on traffic sign comprehension
S. Bellgardt, M. Toepper, S. Boedeker, V. Bertke, P. Schulz, K. Labudda, S. Kreisel, M. Driessen, T. Beblo, S. Spannhorst

Collection of closed articles in transport research (2020). Vol. 2020, 37

Abstract
geing is associated with changes in cognitive functions that affect fitness to drive. However, little is known about age effects on traffic sign comprehension (TSC). In this study, we assessed 37 older and 29 younger healthy drivers with a standardised traffic sign test and a comprehensive neuropsychological test battery. Older drivers showed lower TSC speed and tended to interpret more recent traffic signs less accurately than younger drivers. Higher cognitive functioning was generally associated with better TSC performances in both groups. In older drivers, TSC speed was related to specific cognitive functions such as cognitive flexibility and inhibition. Our findings suggest that traffic signs should appear in time to meet age-related constraints in TSC processing speed and should put low demands on inhibitory skills and cognitive flexibility. However, our findings also suggest that cognitive abilities are important for TSC regardless of age. In addition, a periodic update of traffic sign knowledge appears to be necessary. (C) 2019 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd.
Abstract
geing is associated with changes in cognitive functions that affect fitness to drive. However, little is known about age effects on traffic sign comprehension (TSC). In this [...]
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Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows
L. Veelenturf, T. Woensel, P. Sun, M. Hewitt

Collection of closed articles in transport research (2020). Vol. 2020, 34

Abstract
The rise of e-commerce has increased the demands placed on pickup and delivery operations, as well as customer expectations regarding the quality of services provided by those operations. One strategy a logistics provider can employ for meeting these increases in demands and expectations is to complement and coordinate its fleet operations with those of for-hire, third-party logistics providers. Herein, we study an optimization problem for coordinating these operations: the time-dependent profitable pickup and delivery problem with time windows. In this problem, the logistics provider has the opportunity to use its fleet of capacitated vehicles to transport shipment requests, for a profit, from pickup to delivery locations. Owing to demographic and market trends, we focus on an urban setting, wherein road congestion is a factor. As a result, the problem explicitly recognizes that travel times may be time-dependent. The logistics provider seeks to maximize its profits from serving transportation requests, which we compute as the difference between the profits associated with transported requests and transportation costs. To solve this problem, we propose an adaptive large neighborhood search algorithm. The results of our extensive computational study show that the proposed algorithm can find high-quality solutions quickly on instances with up to 75 transportation requests. Furthermore, we study its impact on profits when explicitly recognizing traffic congestion during planning operations.
Abstract
The rise of e-commerce has increased the demands placed on pickup and delivery operations, as well as customer expectations regarding the quality of services provided by those [...]
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A framework for modelling and analysing coordination challenges in hinterland transport systems
W. Jaarsveld, R. Dijkman, A. Veenstra, P. Grefen, V. Gumuskaya

Collection of closed articles in transport research (2020). Vol. 2020, 33

Abstract
Multimodal transport systems connect seaports to their hinterland and have potential economic, social and environmental advantages over road transport. However, currently this potential is realised only to a limited extent, and road transport still dominates the market. We have conducted in-depth interviews with practitioners to explore possible reasons. We find that lack of coordination at the operational level between the parties involved in transport systems leads to inefficiencies in hinterland transport systems and compromises the advantages of multimodal transport. Although academic research recognises the significance of coordination, it generally employs an economic perspective at a strategic level, but does not say much about actual implementation at an operational level. To fill this gap, we develop a framework to model coordination challenges in hinterland transport, with an emphasis on the operational level. The framework is inspired by the modelling approaches in earlier literature, and tailored based on the common characteristics of coordination challenges observed during our interviews. Further, we propose a method to analyse such models in depth and reveal specific insights such as inadequacy of contracts to facilitate coordination, the dynamics of consequential planning decisions, and shortcomings in information exchange. To demonstrate the applicability of our framework, we use it to model and analyse the particularly tenacious coordination challenge of barge congestion in the Port of Rotterdam.
Abstract
Multimodal transport systems connect seaports to their hinterland and have potential economic, social and environmental advantages over road transport. However, currently [...]
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Liquefaction fragility of sewer pipes derived from the case study of Urayasu (Japan)
J. Koseki, G. Modoni, R. Spacagna, A. Baris, L. Paolella

Collection of closed articles in transport research (2020). Vol. 2020, 31

Abstract
The damage on supply and drainage water networks is a serious cause of economic disruption for urban systems affected by earthquakes. Among various concerns, the ruptures of sewer pipes and manholes generated by liquefaction determine a particularly severe sanitary hazard and require extensive, costly and time-consuming repairs. Quantitative risk assessment carried out with the characterisation and geographical mapping of seismic hazard, subsoil susceptibility, physical and functional vulnerability of the exposed elements, enables to estimate losses, identify weaknesses, inspire strategies to mitigate the impact of earthquakes and improve resilience. The present study deals with the physical vulnerability of sewer pipelines. Empirical fragility functions are derived from the evidences of liquefaction induced in Urayasu (Japan) by the 2011 Tohoku-Oki earthquake (Mw9.0). The spatial distribution of seismic signals, subsoil characteristics, pipes and surveyed damages are reconstructed in a GIS platform. An articulated methodology is developed to correlate variables and compensate their limited spatial correspondence, exploiting the complete coverage of the area with terrestrial settlements measured by LiDAR and their strong correlation with damage. Finally, ruptures of pipes are probabilistically quantified adopting a common liquefaction severity indicator as engineering demand parameter and measuring the efficiency of relations with statistical tests.
Abstract
The damage on supply and drainage water networks is a serious cause of economic disruption for urban systems affected by earthquakes. Among various concerns, the ruptures [...]
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Determining the Depth and Location of Buried Pipeline by Magnetometer Survey
S. Staples, S. Freear, D. Cowell, B. Varcoe, C. Vo

Collection of closed articles in transport research (2020). Vol. 2020, 30

Abstract
This paper proposes a new approach to determine the depth and location of buried pipelines using the remote magnetic field measured by aboveground magnetometer surveys. Calculation is presented and verified by the experimental results on 152-mm (6-in.). steel vessels. Performance of the technique is also evaluated through field trials against industrial pipe locators. The depth calculated from the measured magnetic field using this proposed technique agreed within the tolerance interval representing the confidence level of 99.7% of the depth determined by the industrial devices and was able to trend changes of the buried depth. In addition, it was possible to map the target pipeline using the survey route coordinates by calculating the lateral position of the survey route relative to the pipeline centerline from the measured magnetic field. So far, the depth measured by this proposed technique has shown a potential error of 8%. By producing a three-dimensional profile of buried pipelines through quick aboveground surveys, the proposed technique can be considered as a screening technique for asset and integrity management such as monitoring geohazard conditions.
Abstract
This paper proposes a new approach to determine the depth and location of buried pipelines using the remote magnetic field measured by aboveground magnetometer surveys. Calculation [...]
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A scoping indicator identifying potential impacts of all-inclusive MaaS taxis on other modes in Manchester
A. Walmsley, J. Anable, I. Philips

Collection of closed articles in transport research (2020). Vol. 2020, 27

Abstract
We present a spatial scoping indicator of the potential impacts of an all-inclusive taxi service as part of a plausible but hypothetical Mobility as a Service (MaaS) package in Manchester UK. Our indicator identifies the number of people in each area who have some potential for mode shift from walking, cycling, public transport or car commuting to an all-inclusive taxi service within a MaaS package. We find the method quick and straightforward. In our case study, potential to shift from walk to an all-inclusive taxi service within a MaaS package is almost double the potential shift away from car, which represents a risk of increased car use.
Abstract
We present a spatial scoping indicator of the potential impacts of an all-inclusive taxi service as part of a plausible but hypothetical Mobility as a Service (MaaS) package [...]
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Fleet modelling in strategic multi-criteria decision-making of approved training organization from capacity building and resource dependency theory perspective: risk taxonomy methodology
S. Başar, M. Karaca, H. Lapçın, S. Başar, A. Yilmaz

Collection of closed articles in transport research (2020). Vol. 2020, 26

Abstract
WOS: 000531158800001 Purpose in this study, research problem has been designed as a fleet-based optimization problem. This paper aims to present fleet modelling with risk taxonomy. Fleet modelling has been assumed as strategic multi-criteria decision-making problem to capacity building. Capacity building risk management is an essential element within the scope of its strategy to ensure sustainable corporate performance. Optimization is a fundamental target in aviation business' strategy and management since the manager make decisions in their multi-interrelated criteria environment. Also, aviation is a highly regulated sector, and its operational and business procedures have certain limits by both national and international authorities. For this reason, companies implement risk management for strategic optimization while performing operations in compliance with the legislation. Risk management with capacity building and resource dependency perspective applied for strategic optimization aims to capture opportunities and result in threats with minimum accidents and incidents. Design/methodology/approach the taxonomy and analytical hierarchy process (AHP) have been identified as methodologies in this research. the type of training in the high organizational performance of an approved training organization, strategy, resources and allocations with the corporate objectives, the amount and qualifications of the flight crew, their professionalism, maintenance team and licenses, hangar conditions and capacity, authority requirements and limits, region conditions, altitude and meteorology, student profile, together with a multi-criteria decision are to be considered. For each criterion, there are resources and thus resource dependence. in this study, the analytical network process method was used. in the construction of new taxonomy, specific criteria have been considered, and the analysis has been accomplished as multi-criteria decision-making problem because of the relationship and interaction between them. A number of professionals with high knowledge of the pilots and manager from Air Traffic Organization participated in the study. Findings the fleet modelling is both strategic and operational decision issue for training organizations. in this issue, there is a vital problem as which aircrafts should include fleet? Main criteria and sub-criteria are analyzed by AHP method supported by structured interview and sorted according to their priorities and the fleet qualifications consisting of the most suitable aircraft/aircraft are presented. the finding and suggestions will contribute to establish sustainable organization in based on capacity building and resource dependency for managers. While analyzing main criteria, the important criteria which were found were strategic and then operational. After ordering main criteria, sub-criteria were analyzed and were multiplicated with their items. According to study findings, aircraft suitability for training model is the most important item. It follows respectively aircraft maintenance sustainability, cost of aircraft supply and faculty budget adequacy. However, operation characteristics of the square that is less important item was found. It was seen that the strategies used to manage dependencies used the bridge strategy. the results we obtained with the interviews with pilot managers are very significant in terms of resource dependence on the subject of fleet optimization. While first criterion is operational, it continues with strategic and financial criteria. After interviews with pilot managers, it was figured out that maintenance is also very important criteria. For managing this dependency, university has acquisitions, which is one of the strategy to manage dependency, rather than outsourcing. For this reason, maintenance criterion has lower importance than others. When thinking of other criteria, strategic and financial criteria have played an important role. University has tried to decrease dependency and increase sustainability. Research limitations/implications Aircraft selection is a strategic decision of fleet modelling in both aviation business and also training organizations via influencing their corporate performance, operational performance, capacity building and their sustainability. There are some factors that limit the criteria, as research problem has been developed for approved training organizations not airlines. For this reason, our research is limited with fleet of training organizations. Our findings and suggestions may be useful for flight schools to managing their resource dependency and also to their capacity building. in this research, new taxonomy has been developed depending on training organizations' qualifications. Airlines may improve this taxonomy to use in their decision-making process. Practical implications the fleets, which were established considering the taxonomy in this study, will be able to manage the risk of resource dependency more successfully. Pilot candidates will be able to provide a more ergonomic and higher quality education. This research and its findings will contribute to the development of organizations' accurate and timely decision-making skills. Resource dependency may threat organizational sustainability in our research, New taxonomy and our holistic approach will support organizational efforts to achieve sustainable strategies. Social implications New taxonomy to modelling fleet that has been developed in this research may provide contribution to approved training organizations for both managing resource dependency-based risks and to capacity building-related decision-making process. This research may serve organizations as strategic decision-making tool. and also this kind of study may contribute to improve sustainability of organizations and serve more good fleet for their pilot candidates. For these reasons, this research may create social implications, as both resource using and capacity building will make contribution for society and add value. Originality/value This research presents new risk taxonomy and criteria. Also new taxonomy and its criteria are analysed with AHP. It is thought that this research shows risk management-based approach for fleet modelling creates benefits for approved training organizations to using their limited sources effectively and efficiently. the article includes risk management and capacity building-related approach to decision-making. also, this research presents modeling which will contribute to the management field besides literature. in developing taxonomy process, the analysis has been conducted, based on expert opinions and referred to for these pairwise comparisons. Airlines managers and risk managers may examine their fleet modelling according to our taxonomy which is based on risk management.
Abstract
WOS: 000531158800001 Purpose in this study, research problem has been designed as a fleet-based optimization problem. This paper aims to present fleet modelling with risk [...]
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Vision-Enhanced Low-Cost Localization In Crowdsourced Maps
G. Velez, A. Das, J. Eggert, O. Otaegui, G. Dubbelman, D. Betaille, B. Flade, A. Koppert

Collection of closed articles in transport research (2020). Vol. 2020, 25

Abstract
The lane-level localization of vehicles with low-cost sensors is a challenging task. In situations in which Global Navigation Satellite Systems (GNSSs) suffer from weak observation geometry or from the influence of reflected signals, the fusion of heterogeneous information presents a suitable approach for improving the localization accuracy. We propose a solution based on a monocular front-facing camera, a low-cost inertial measurement unit (IMU), and a single-frequency GNSS receiver. The sensor data fusion is implemented as a tightly coupled Kalman filter that corrects the IMU-based trajectory with GNSS observations while employing European Geostationary Overlay Service correction data. Further, we consider vision-based complementary data that serve as an additional source of information. In contrast to other approaches, the camera is not used to infer the motion of the vehicle, but rather for directly correcting the localization results under the usage of map information. More specifically, the so-called camera-to-map alignment is done by comparing virtual 3D views (candidates) created from projected map data with lane geometry features that are extracted from the camera image. One strength of the proposed solution is its compatibility with state-of-the-art map data, which are publicly available from different sources. We validate the approach on real-world data recorded in The Netherlands and show that it presents a promising and cost-efficient means to support future advanced driver assistance systems.
Abstract
The lane-level localization of vehicles with low-cost sensors is a challenging task. In situations in which Global Navigation Satellite Systems (GNSSs) suffer from weak observation [...]
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On the sustainable perishable food supply chain network design:A dairy products case to achieve sustainable development goals
J. Jouzdani, K. Govindan, K. Govindan

Collection of closed articles in transport research (2021). Vol. 2021, 2

Abstract
Perishable products require special handling measures that may have social and environmental impacts along with their well-known economic aspects. Therefore, the sustainability of food supply chains has gained ground; however, the sustainability of perishable food supply chains, is still not a fully explored field of study. Therefore, in this research, a multi-objective mathematical programming model is developed to optimize the cost, energy consumption, and the traffic congestion associated with such supply chain operations. In this study, product lifetime uncertainty is explicitly modeled as a Weibull random variable, and food perishability is assumed to be affected by vehicle refrigerator utilization, which is considered as a decision variable. In addition, multiple vehicle types and multiple product types are considered. A dairy supply chain case is investigated, and the interrelations and interactions of all three aspects of sustainability, also known as the three triple bottom lines (TBL) of sustainability, are studied. The results indicate that emphasizing the economic aspect, for highly perishable products, the environmental impact of the chain may increase by 120%, and for the highly congested road networks, the social impact may rise by 51%. However, a 15% economic compromise can improve the sustainability of the supply chain network design by 150%. It is also shown that road congestion and the uncertain perishability of the products are critical factors that can, although differently, affect the operation and the design of the supply chain. This study contributes to the sustainable development goals (SDG’s) such as Zero Hunger (SDG 2); Affordable and Clean Energy (SDG 7); Decent Work and Economic Growth (SDG 8); Industry, Innovation, and Infrastructure (SDG 9); Responsible Consumption and Production (SDG 12); Climate Action (SDG 13) and Peace, Justice, and Strong Institutions (SDG 16). The results suggest that decision-makers can significantly reduce the environmental and social influences of the supply chain even without drastically compromising the economic aspect.
Abstract
Perishable products require special handling measures that may have social and environmental impacts along with their well-known economic aspects. Therefore, the sustainability [...]
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Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model
M. Farrokhifar, F. Aghdam, A. Alahyari, A. Monavari, A. Safari

Collection of closed articles in transport research (2020). Vol. 2020, 23

Abstract
Energy supply through integrated renewable energy sources (RESs) and battery systems will be of higher importance for future residential sectors. Optimal energy management and sizing for the components of residential systems can enhance efficiency, self-suffiency, and meanwhile can be cost-effective by reducing investment as well as operating costs. Accordingly, this paper proposes an exhaustive optimization model for determining the capacity of RESs, namely: wind turbines and photovoltaic (PV) systems. In this study, batteries and electric vehicles (EVs) are utilized in line with other sources to capture fluctuations of RESs. To model the uncertainties of RESs, energy prices, and load demands a linearized stochastic programming framework is applied. The proposed framework involves long-term and efficient resource development alongside with short-term management and utilization of these resources for supplying the demand load. In our study, we utilize the roulette wheel mechanism (RWM) method as well as proper probability distribution functions (PDFs) to generate scenarios for all sources of uncertainties, including wind turbines, PV systems, demand, and electricity market price. The approach is verified in two different cases, including an individual home and a larger micro-grid (MG). The results of multiple numerical simulations demonstrate the effectiveness of the proposed stochastic model.
Abstract
Energy supply through integrated renewable energy sources (RESs) and battery systems will be of higher importance for future residential sectors. Optimal energy management [...]
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Net emission reductions from electric cars and heat pumps in 59 world regions over time
A. Lam, A. Lam, U. Chewpreecha, H. Pollitt, J. Mercure, M. Huijbregts, F. Knobloch, F. Knobloch, P. Salas, S. Hanssen

Collection of closed articles in transport research (2020). Vol. 2020, 22

Abstract
The electrification of passenger road transport and household heating features prominently in current and planned policy frameworks to achieve greenhouse gas emissions reduction targets. However, since electricity generation involves using fossil fuels, it is not established where and when the replacement of fossil-fuel-based technologies by electric cars and heat pumps can effectively reduce overall emissions. Could electrification policies backfire by promoting their diffusion before electricity is decarbonized? Here we analyse current and future emissions trade-offs in 59 world regions with heterogeneous households, by combining forward-looking integrated assessment model simulations with bottom-up life-cycle assessments. We show that already under current carbon intensities of electricity generation, electric cars and heat pumps are less emission intensive than fossil-fuel-based alternatives in 53 world regions, representing 95% of the global transport and heating demand. Even if future end-use electrification is not matched by rapid power-sector decarbonization, it will probably reduce emissions in almost all world regions. Little is known about the actual effects of electrification policies on carbon emissions. This study shows that, under current carbon intensities of electricity generation, electric cars and heat pumps are less emission intensive than fossil-fuel-based alternatives in 53 of 59 world regions.
Abstract
The electrification of passenger road transport and household heating features prominently in current and planned policy frameworks to achieve greenhouse gas emissions reduction [...]
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Online Driver Distraction Detection Using Long Short-Term Memory
B. Schuller, C. Blaschke, M. Wöllmer, B. Färber, B. Trefflich, S. Mayer, T. Schindl

Collection of closed articles in transport research (2020). Vol. 2020, 19

Abstract
Lane-keeping assistance systems for vehicles may be more acceptable to users if the assistance was adaptive to the driver's state. To adapt systems in this way, a method for detection of driver distraction is needed. Thus, we propose a novel technique for online detection of driver's distraction, modeling the long-range temporal context of driving and head tracking data. We show that long short-term memory (LSTM) recurrent neural networks enable a reliable subject-independent detection of inattention with an accuracy of up to 96.6%. Thereby, our LSTM framework significantly outperforms conventional approaches such as support vector machines (SVMs).
Abstract
Lane-keeping assistance systems for vehicles may be more acceptable to users if the assistance was adaptive to the driver's state. To adapt systems in this way, a method for [...]
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User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions
A. Traverso, A. Traverso, A. Dekker, B. Zhang, B. Zhang, S. Huang, S. Huang, M. Welch, A. McNiven, A. McNiven, L. Wee, C. McIntosh, D. Jaffray, B. O'Sullivan, B. O'Sullivan, F. Hoebers

Collection of closed articles in transport research (2020). Vol. 2020, 18

Abstract
Purpose Precision cancer medicine is dependent on accurate prediction of disease and treatment outcome, requiring integration of clinical, imaging and interventional knowledge. User controlled pipelines are capable of feature integration with varied levels of human interaction. In this work we present two pipelines designed to combine clinical, radiomic (quantified imaging), and RTx-omic (quantified radiation therapy (RT) plan) information for prediction of locoregional failure (LRF) in head and neck cancer (HN and 2) a pipeline with minimal user input that utilizes deep learning convolutional neural networks to extract and combine CT imaging, RT dose and clinical features for model development. Results Clinical features with logistic regression in our highly user-driven pipeline had the highest precision recall area under the curve (PR-AUC) of 0.66 (0.33–0.93), where a PR-AUC = 0.11 is considered random. CONCLUSIONS: Our work demonstrates the potential to aggregate features from multiple specialties for conditional-outcome predictions using pipelines with varied levels of human interaction. Most importantly, our results provide insights into the importance of data curation and quality, as well as user, data and methodology bias awareness as it pertains to result interpretation in user controlled pipelines.
Abstract
Purpose Precision cancer medicine is dependent on accurate prediction of disease and treatment outcome, requiring integration of clinical, imaging and interventional knowledge. [...]
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Influence of values attitudes towards transport modes and companions on travel behavior
H. Timmermans, T. Ruiz, S. Rasouli, R. Arroyo, L. Mars

Collection of closed articles in transport research (2020). Vol. 2020, 17

Abstract
The design and implementation of transport policies to promote active transport requires a deep comprehension of the factors that influence travel behavior. In this context, psychological factors and social interactions play an important role in explaining travel-related decisions. Even though, the importance of psychosocial variables in travel behavior research has been widely recognized during recent years, there is a lack of understanding of how these factors interact. This paper aims to better understand the interrelationships between values, attitudes towards transport modes and a subset of the social network composed by habitual trips and activities companions. For this purpose, a theoretical framework is proposed which posits all the possible relationships among these factors. In order to test this conceptual framework, two Structural Equation Models are estimated considering attitudes towards active transport (bike and walking), using a dataset from a web-based survey developed for the MINERVA project in Valencia (Spain). The data is composed by 404 respondents who provided valid information regarding all the variables of the study. Results confirm the hierarchical value-attitude-behavior structure while several effects are also found directly between values and attitudes. For instance, individuals who attach more importance to Stimulation and Achievement values are higher active transport user, while values traditionally associated with car use are no longer maintaining this relation. Besides that, positive attitudes towards walking and cycling are strongly associated with a higher use of active transport, and also seem to discourage the use of motorized modes. Several characteristics of companions affects personal values and active travel and less influence is found on attitudes. These findings are useful to develop transport policies and campaigns to promote sustainable transport, such as the design of strategies in the context of Travel Behavior Change Programs. Limitations of this research include several aspects related to online surveys, for instance, sample size and underrepresentation of individuals over 55 years.
Abstract
The design and implementation of transport policies to promote active transport requires a deep comprehension of the factors that influence travel behavior. In this context, [...]
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Potential advantages in heat and power production when biogas is collected from several digesters using dedicated pipelines - A case study in the "Province of West-Flanders" (Belgium)
A. Broekhuis, J. Bekkering, E. Hengeveld, M. Dael, W. Gemert

Collection of closed articles in transport research (2020). Vol. 2020, 16

Abstract
In the case study "West-Flanders" costs of electricity and heat production are estimated if a dedicated biogas grid using pipelines would be implemented to centralize energy production in a region. Heat may not be used effectively at digester sites, e.g. because of a change in treatment of digestate. A large scale centralized combined heat and power (CHP) engine can produce additional electrical power at a hub, i.e. central collection point, and has lower specific costs compared to decentralized CHPs at digester sites. A biogas transport model is used to calculate transport costs in a grid. These costs, partly balanced by a scale advantage in CHP costs, are attributed to the additional electrical energy (80%) and heat (20%) produced. If the hub is at a digester site, costs of additional electricity can be as low as 4.0 (sic)ct kWh(e)(-1) and are in many cases below 12 (sic)ct kWh(e)(-1), i.e. in the same order of magnitude or lower than costs of electricity from biogas produced using separate CHPs at the different digester sites; costs of heat at the hub show to be lower than 1 (sic)ct kWh(th)(-1) assuming an effective heat use of 50%. In case a hub is situated at a location with high potential heat demand, i.e. a heat sink, transport of biogas from one digester only to a central located hub can provide 3.4 MWth of heat at 1.95 (sic)ct kWh(th)(-1). For such a centrally located hub additional electrical energy costs show to be slightly higher, but with three or more digesters these costs are lower than 20 (sic)ct kWh(e)(-1) and heat costs are around 0.5 (sic)ct kWh(th)(-1). With a centralized hub more renewable energy is produced, i.e. a more efficient use of biomass feedstock. It is concluded that costs for additional electricity and heat can be at a competing level and scale advantages in a CHP can be a driver to collect biogas at a hub using a biogas grid. (C) 2019 Elsevier Ltd. All rights reserved.
Abstract
In the case study "West-Flanders" costs of electricity and heat production are estimated if a dedicated biogas grid using pipelines would be implemented to centralize energy [...]
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A variant of the split vehicle routing problem with simultaneous deliveries and pickups for inland container shipping in dry-port based systems
T. Woensel, S. Fazi, S. Fazi, J. Dong, J. Fransoo

Collection of closed articles in transport research (2020). Vol. 2020, 15

Abstract
In this paper, we will study a typical problem in inland container shipping, concerning the barge transportation of maritime containers between a dry port and a set of seaport terminals. The barges depart from the dry port and visit a set of sea terminals, where containers need either to be dropped off or picked up. The goal is to achieve economies of scale with barges and avoid trucking as much as possible. The decision thus involves finding the best allocation of containers to barges in order to guarantee on-time delivery and meet capacity restrictions. The problem will be modeled as a variant of the split vehicle routing problem with simultaneous pickups and deliveries coupled with time features. The model includes parameters that can be tuned to improve barge utilization and travelling distance. A hybrid local search meta-heuristic algorithm, combined with a branch-and-cut solver, will be developed to solve the model. Numerical experiments have been conducted to test the performance of the algorithm and provide solution analysis for practical insights. Real-world data has been collected from a local barge operator based in the Port of Rotterdam region and will be used as input for the experiments. This will result in an in-depth analysis into current planning practices. The proposed framework complements existing models in the literature and contributes to the development of a comprehensive set of decision support tools, which help in the decision-making process for inland terminals.
Abstract
In this paper, we will study a typical problem in inland container shipping, concerning the barge transportation of maritime containers between a dry port and a set of seaport [...]
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Route and stopping intent prediction at intersections from car fleet data
B. Schuller, F. Klanner, J. Jordan, F. Gross, F. Weninger

Collection of closed articles in transport research (2020). Vol. 2020, 14

Abstract
In this paper, an approach is presented to predict the route and stopping intent of human-driven vehicles at urban intersections using a selection of distinctive features observed on the vehicle state (position, heading, acceleration, velocity). For potential future advanced driver assistance systems, this can facilitate the situation analysis and risk assessment at road intersections, helping to improve the protection of vulnerable road users. After extracting recorded driving data for nine intersections (featuring over 50 000 crossings) from a database, they are assigned to possible routes and transformed from a time-based representation to a distance-based one. Using random decision forests, the route intent can be predicted with a mean unweighted average recall (UAR) of 0.76 at 30 m before the relevant intersection center, the stopping intent prediction scores a mean UAR of 0.78.
Abstract
In this paper, an approach is presented to predict the route and stopping intent of human-driven vehicles at urban intersections using a selection of distinctive features [...]
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Operational flexibility of electrified transport and thermal units in distribution grid
B. Bak-Jensen, J. Pillai, R. Sinha

Collection of closed articles in transport research (2020). Vol. 2020, 13

Abstract
The decentralised infrastructure of the Danish thermal and electricity infrastructure has improved security, efficiency and reliability in energy transmission and consumption in each of the systems. To further improve this trend, this paper investigates the concept of decentralised coupling of electrified thermal and transportation system in low voltage residential network to identify their operational flexibility. In this paper, diagnosis based on actual data from the energy distributors and surveys is used to understand and improve the flexibility of an integrated energy system. The main contribution is a set up model with an autonomous control system that can assess the potential flexibility from thermal units (eg heat pumps and storages) and electric vehicles (EV) charging systems, in the low voltage distribution network as a multi-energy system. Each thermal system and EV charging has its respective individual controller. The proposed control technique manages to successfully operate and control the thermal units and EVs charging system within the recommended operating limits of grid voltage, and by sharing flexibility within the specific network integrated with multi-carrier energy systems. It has the capability of sensing local key control parameters like node voltage, state of charge of EV, temperature and level of hot water in the storage tank. These control parameters allow scheduling, re-scheduling, and decision making on the operation of individual thermal and EV charging-unit with operational priorities. This enhances the sharing of flexibility for proper coordination, control, and management of thermal and EV charging systems in low voltage (LV) distribution networks with mutual technical benefits. From the results of the steady-state analysis of power system, the application of the proposed control architecture is found to be effective to manage grid congestions and local voltage control, satisfying the thermal energy requirements of the customer as well as charging needs of EV.
Abstract
The decentralised infrastructure of the Danish thermal and electricity infrastructure has improved security, efficiency and reliability in energy transmission and consumption [...]
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Cycling as a service assessed from a combined business-model and transitions perspective
B. Petzer, A. Wieczorek, G. Verbong

Collection of closed articles in transport research (2020). Vol. 2020, 12

Abstract
Cycling-based mobility services or 'Cycling as a Service' (CaaS) have recently expanded in number and scale in the Netherlands. In contrast to the contexts of most other CaaS studies to date, cycling has a high modal share and strong institutions in the Dutch context. However, these supportive features have not translated into straightforward success for CaaS providers. Instead, responses to CaaS providers have varied widely, from tolerance to opposition. In this study we employ a combined business model and transition perspective to investigate this variation and its implications for CaaS in Dutch urban mobility systems. We present value propositions derived from business models, and integrate these into Hoogma's fit-and-stretch strategy framework for emerging niches. This enables a comparison between technology design and value propositions, and an analysis of the CaaS niche's transitions potential. Our findings clarify the strategies used by niche actors to enter and operate within established cycling regimes.
Abstract
Cycling-based mobility services or 'Cycling as a Service' (CaaS) have recently expanded in number and scale in the Netherlands. In contrast to the contexts of most other CaaS [...]
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Polynomial Augmented Extended Kalman Filter to Estimate the State of Charge of Lithium-Ion Batteries
B. Haus, P. Mercorelli

Collection of closed articles in transport research (2020). Vol. 2020, 11

Abstract
In battery-electric vehicles, an accurate knowledge of the current state of charge (SOC) of the battery is crucial for safe and efficient operation. Offset-free SOC estimation for Lithium-ion batteries (LIB) during operation still is a challenging problem, due to the uncertain output nonlinearity present in battery models. In battery management systems employed in such vehicles, the age- and cycle-dependent relationship between the open circuit voltage (OCV) and the state of charge of each cell (SOC) can be kept track of using lookup tables. Between the scattered data points, linear interpolation is often used. Another common approach is to switch between models, each with a different piecewise polynomial fit of low order. In this contribution, a single polynomial fit of a higher order with state-dependent coefficients for the whole SOC-OCV range is proposed, so as to avoid switching and facilitate usage of Taylor-based linearization algorithms like in the extended Kalman filter. While the polynomial order is high, the number of parameters is only three; the parameters are estimated and updated by the Kalman filter itself. This augmentation of the observer's state vector with said polynomial parameters is inspired by the idea of an increased “stochastization,” introducing redundancy that aids to achieve a more accurate SOC estimation. In this sense, the algorithm can be described as a model-adaptive extended Kalman estimator. Two variants of a polynomial EKF are investigated: polynomial EKF with output and with state nonlinearity models. Their performances are compared in real experiments using a dedicated test bench based on a Samsung ICR18650-26F cell, demonstrating the effectiveness of the algorithms. The variant that includes the terminal voltage in the state vector, i.e. the state nonlinearity variant of the EKF, shows better result, also compared to the existing literature.
Abstract
In battery-electric vehicles, an accurate knowledge of the current state of charge (SOC) of the battery is crucial for safe and efficient operation. Offset-free SOC estimation [...]
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Dataset for calculating the currents and voltages induced on underground pipelines by nonparallel overhead power lines
A. Popoli, L. Sandrolini, A. Cristofolini

Collection of closed articles in transport research (2020). Vol. 2020, 9

Abstract
The electromagnetic interference caused by overhead power lines on nonparallel underground pipelines is assessed in “A numerical model for the calculation of electromagnetic interference from power lines on nonparallel underground pipelines” (Popoli et al., 2020 [1]) by segmenting the pipeline path in a number of traits parallel to the power line. The analysis requires a multi-port electrical component to be extracted for each pipeline segment by means of finite element 2D analysis; circuit analysis can then be applied to the network composed of the cascade of the multi-port electrical components in order to calculate the induced voltages and currents on the pipeline. The data in this paper consist of matrices which represent the multi-port electrical components corresponding to the segments in which the pipeline has been subdivided. These matrices can then be used as constitutive relations in network analysis, as detailed in (Popoli et al., 2019 [2]), in order to find the induced pipeline voltages and currents for different intersection angles between the pipeline and overhead power line routings.
Abstract
The electromagnetic interference caused by overhead power lines on nonparallel underground pipelines is assessed in “A numerical model for the calculation of electromagnetic [...]
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The Covid-19 pandemic effects in rural areas
C. De Luca, S. Tondelli, H. Åberg

Collection of closed articles in transport research (2020). Vol. 2020, 8

Abstract
Rural communities tell us the story of a thousand of years of collaboration between nature, culture and humans. The current Covid-19 pandemic is considerably threating rural areas, posing challenges exacerbated by low available financial resources, not easily accessible health services and greater isolation. Rural areas are also considered safe shelters characterized by better daily living conditions thanks to easy to maintain social distancing and access to nature, to cultural and nature-based recreation activities. The Covid-19 crisis is revealing the crucial role of natural and cultural heritage for social cohesion, local development and mental wellbeing. The paper presents some responses to the Covid-19 crisis collected through an open call for action within the RURITAGE project. It aims at show how rural areas can cope with emergencies and it builds the basis to rethink the current crisis as a crucial tipping point for a resilient development of rural territories. It is key to overcome the idea of rural areas as mere food production system, calling for a broader vision of rural communities as poles of development based on local heritage, natural resources, creativity and social inclusion as essential elements to regenerate rural areas and to rapidly support their transition towards sustainable future.
Abstract
Rural communities tell us the story of a thousand of years of collaboration between nature, culture and humans. The current Covid-19 pandemic is considerably threating rural [...]
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Performance comparison of population-based optimization algorithms for air traffic control
N. Basturk, A. Sahinkaya

Collection of closed articles in transport research (2020). Vol. 2020, 6

Abstract
"jats:title content-type="abstract-subheading""Purpose"/jats:title" "jats:p"The purpose of this paper is to present a detailed performance comparison of recent and state-of-the-art population-based optimization algorithms for the air traffic control problem."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Design/methodology/approach"/jats:title" "jats:p"Landing sequence and corresponding landing times for the aircrafts were determined by using population-based optimization algorithms such as artificial bee colony, particle swarm, differential evolution, biogeography-based optimization, simulated annealing, firefly and teaching–learning-based optimization. To obtain a fair comparison, all simulations were repeated 30 times for each of the seven algorithms, two different problems and two different population sizes, and many different criteria were used."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Findings"/jats:title" "jats:p"Compared to conventional methods that depend on a single solution at the same time, population-based algorithms have simultaneously produced many alternate possible solutions that can be used recursively to achieve better results."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Research limitations/implications"/jats:title" "jats:p"In some cases, it may take slightly longer to obtain the optimum landing sequence and times compared to the methods that give a direct result; however, the processing times can be reduced using powerful computers or GPU computations."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Practical implications"/jats:title" "jats:p"The simulation results showed that using population-based optimization algorithms were useful to obtain optimal landing sequence and corresponding landing times. Thus, the proposed air traffic control method can also be used effectively in real airport applications."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Social implications"/jats:title" "jats:p"By using population-based algorithms, air traffic control can be performed more effectively. In this way, there will be more efficient planning of passengers’ travel schedules and efficient airport operations."/jats:p" "/jats:sec" "jats:sec" "jats:title content-type="abstract-subheading""Originality/value"/jats:title" "jats:p"The study compares the performances of recent and state-of-the-art optimization algorithms in terms of effective air traffic control and provides a useful approach."/jats:p" "/jats:sec
Abstract
"jats:title content-type="abstract-subheading""Purpose"/jats:title" "jats:p"The purpose of this paper is to present a detailed performance comparison of recent and state-of-the-art [...]
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Distributed control of active cell balancing and low-voltage bus regulation in electric vehicles using hierarchical model-predictive control
C. Amon, K. Gupta, Z. Gong, M. Donkers, C. Silva, B. Ven, H. Bergveld, O. Trescases

Collection of closed articles in transport research (2020). Vol. 2020, 5

Abstract
Electric vehicle battery performance near end-of-life is limited by mismatched cell degradation, leading to an estimated 5-10% cell capacity variation across the pack. Active cell balancing hardware architectures incorporating a Low-Voltage (LV) bus supply have been introduced to unlock lost capacity due to cell imbalance at reduced cost, through elimination of the vehicle's 400-to-12V dc-dc converter. In this work, a hierarchical model-predictive control scheme is applied to a time-shared isolated converter active balancing architecture that incorporates LV bus supply. The proposed controller efficiently divides computation among the battery management system hardware components. The energy-buffering capability of the lead-acid battery, which is connected to the LV bus, is used to trade-off balancing and bus regulation objectives, reducing peak power and improving the system cost-effectiveness. Simultaneous state-of-charge balancing and LV bus regulation is verified in simulation and experiment using real-world drive and LV load data collected from a GM Bolt electric vehicle. Similar controller performance compared to a central scheme is achieved in simulation. The experimental setup includes a custom 12S2P, 3.9kWh, liquid-cooled Lithium Nickel Manganese Cobalt battery module with embedded battery management system. The controller performance is evaluated with an initial maximum state-of-charge imbalance of 6.8%.
Abstract
Electric vehicle battery performance near end-of-life is limited by mismatched cell degradation, leading to an estimated 5-10% cell capacity variation across the pack. Active [...]
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Evaluating urban logistics schemes using agent-based simulation
M. Mes, W. Zijm, W. Heeswijk, W. van Heeswijk, J. Schutten

Collection of closed articles in transport research (2020). Vol. 2020, 4

Abstract
The domain of urban freight transport is becoming increasingly complex. Many urban supply chains are composed of small and independent actors that cannot efficiently organize their highly fragmented supply chains, thereby negatively affecting the quality of life in urban areas. Both companies and local administrators try to improve transport efficiency and reduce external costs, but the effects of such interventions are difficult to predict, especially when applied in combination with each other (an urban logistics scheme). This paper presents an agent-based simulation model to quantify the effects of urban logistics schemes on multiple actors. We provide a detailed mathematical representation in the form of a Markov decision process. Based on an extensive literature study, we aggregate data to represent various actors in typical Western European cities. We perform numerical experiments to obtain insights into urban logistics schemes. The results show that most schemes yield significant environmental improvements but that achieving long-term financial viability is challenging for urban consolidation centers in particular. We also demonstrate that interventions, such as subsidies and access restrictions, do not always yield the intended effect. In a backcasting experiment, we identify conditions and schemes to achieve a financially viable urban consolidation center.
Abstract
The domain of urban freight transport is becoming increasingly complex. Many urban supply chains are composed of small and independent actors that cannot efficiently organize [...]
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Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives
I. Henke, A. Cartenì, E. Cascetta, F. Pagliara

Collection of closed articles in transport research (2020). Vol. 2020, 3

Abstract
Highlights • HSR had impacts on socio-economic, territorial and transport systems in several countries. • The paper analyses the impacts induced by HSR services in Italy after ten years of operation. • Italy represents the first case of competitive HSR market without public subsidies. • Competition between HSR operators brought a significant decrease in ticket prices (-40%) • HSR passengers/year passed from 15 to 45 millions (+200%) in 10 years. • HSR contributed, in 10 years, to an increase of the rail-based transport accessibility up to + 30% • HSR contributed to an extra growth of per capita GDP of + 2.6–5.6% in 10 years. • Regional equity in terms of travel time accessibility decreased by 11% in 10 years. • Extension of the HSR network would increase accessibility (+18%), economic growth (+3.6%) and equity (+49%) The deployment of HSR services in the recent decades has been, arguably, the most significant innovation for intercity travel around the globe. HSR has brought impacts which have been widely studied in different countries in relation to the different socioeconomic, territorial and transport characteristics. This paper analyses the economic growth, the transport accessibility and the social impacts observed in Italy after ten years of HSR operation, as well as the estimated impacts of the system completion. The Italian case study is of particular interest since along the 1,467 km of new high speed line (300 km/h), a combination of major cities distances and a unique HSR competitive market, producing prices reductions and more daily trains, brought a 200% increase of HSR demand (from 15 to 45 millions of passengers/year). Estimations results show that, on average, HSR in Italy contributed to a significant increase in transport accessibility (+32%) for the zones along the HSR network, while only marginal for the others (+6%). Impacts on the economic growth show that HSR has contributed to an extra growth of per capita GDP of + 2.6% in 10 years and would have contributed to a further increase of 3.6% if the final project scenario (HSR_N) would had been completed by 2018. Regional (horizontal) equity impacts were evaluated in terms of the Gini indexes variations with respect to the distribution of the transport accessibility. It results that HSR in Italy has decreased equity in terms of users’ travel time accessibility of 11%, increasing the differences between the zones served by HSR and those not. If the HSR_N scenario would have been completed equity indices would have increased of 29% with respect to the pre-HSR 2008 scenario, thus reducing regional inequalities in the country. Results show that the HSR project was a country-level “game changer” in Italy, suggesting that the wider economic benefits, the assumptions on market regulation, the effects on regional disparities and the compensatory measures should be included in the ex ante and ex post evaluation of similar projects.
Abstract
Highlights • HSR had impacts on socio-economic, territorial and transport systems in several countries. • The paper analyses the impacts induced by HSR services in Italy [...]
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Air Traffic Control Capacity Planning Under Demand and Capacity Provision Uncertainty
G. Pavlovic, N. Ivanov, R. Jovanović, F. Fichert, X. Fei, A. Strauss, S. Starita

Collection of closed articles in transport research (2020). Vol. 2020, 2

Abstract
In air traffic management, a fundamental decision with large cost implications is the planning of future capacity provision. Here, capacity refers to the available man-hours of air traffic controllers to monitor traffic. Airspace can be partitioned in various ways into a collection of sectors, and each sector has a fixed maximum number of flights that may enter within a given time period. Each sector also requires a fixed number of man-hours to be operated; we refer to them as sector-hours. Capacity planning usually takes place a long time ahead of the day of operation to ensure that sufficiently many air traffic controllers are available to manage the flow of aircrafts. However, at the time of planning, there is considerable uncertainty regarding the number and spatiotemporal distribution of nonscheduled flights and capacity provision, the former mainly due to business aviation, and the latter usually stemming from the impact of weather, military use of airspaces, etc. Once the capacity decision has been made (in terms of committing to a budget of sector-hours per airspace to represent long-term staff scheduling), on the day of operation, we can influence traffic by enforcing rerouting and tactical delays. Furthermore, we can modify which sectors to open at a given time (the so-called sector-opening scheme) subject to the fixed capacity budgets in each airspace. The fundamental trade-off is between reducing the capacity provision cost at the expense of potentially increasing displacement cost arising from rerouting or delays. To tackle this, we propose a scalable decomposition approach that exploits the structure of the problem and can take traffic and capacity provision uncertainty into account by working with a large number of traffic scenarios. We propose several decision policies based on the resulting pool of solutions and test them numerically using real-world data.
Abstract
In air traffic management, a fundamental decision with large cost implications is the planning of future capacity provision. Here, capacity refers to the available man-hours [...]
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The Challenge of Transdisciplinary Research: A Case Study of Learning by Evaluation for Sustainable Transport Infrastructures
G. Mikusiński, M. Frisk, A. Sjölund, M. Ljung, G. Göransson, P. Angelstam, L. Folkeson, M. Blicharska, S. Jönsson-Ekström, J. Skoog, R. Axelsson, M. Henningsson, J. Törnblom

Collection of open articles in transport research (2020). Vol. 2020, 233

Abstract
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. Document type: Article
Abstract
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. [...]
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Development of Micro-Mobility Based on Piezoelectric Energy Harvesting for Smart City Applications
P. Songsukthawan, A. Ngaopitakkul, C. Jettanasen

Collection of open articles in transport research (2020). Vol. 2020, 232

Abstract
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. Document type: Article
Abstract
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 [...]
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Train Type Identification at S&C
M. Kratochvílová, J. Podroužek, J. Apeltauer, I. Vukušič, O. Plášek

Collection of open articles in transport research (2020). Vol. 2020, 231

Abstract
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. Document type: Article
Abstract
The presented paper concerns the development of condition monitoring system for railroad switches and crossings that utilizes vibration data. Successful utilization of such [...]
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Structural Behavior of Pipelines Buried in Expansive Soils under Rainfall Infiltration (Part I: Transverse Behavior)
R. Demagh, M. Bouatia, Z. Derriche

Collection of open articles in transport research (2020). Vol. 2020, 230

Abstract
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. Document type: Article
Abstract
Landslides, fault movements as well as shrink/swell soil displacements can exert important additional loadings on soil buried structures such as pipelines. These loadings [...]
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Multiclock Constraint System Modelling and Verification for Ensuring Cooperative Autonomous Driving Safety
J. Wang, Z. Huang, X. Huang, Y. Zhu, F. Wang

Collection of open articles in transport research (2020). Vol. 2020, 229

Abstract
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. Document type: Article
Abstract
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 [...]
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Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles
Y. Wang, J. Yu, T. Chen, W. Hao, Z. Wang

Collection of open articles in transport research (2020). Vol. 2020, 228

Abstract
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. Document type: Article
Abstract
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 [...]
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Taxi Demand Prediction Based on a Combination Forecasting Model in Hotspots
H. Chen, Z. Liu, Q. Zhang, Y. Li

Collection of open articles in transport research (2020). Vol. 2020, 227

Abstract
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. Document type: Article
Abstract
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 [...]
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A Regression Tree Approach for Investigating the Impact of High Speed Rail on Tourists’ Choices
F. Pagliara, F. Mauriello, L. Russo

Collection of open articles in transport research (2020). Vol. 2020, 226

Abstract
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. Document type: Article
Abstract
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 [...]
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Prospects of Electric Vehicles in the Developing Countries: A Literature Review
J. Albrecht, S. Rajper

Collection of open articles in transport research (2020). Vol. 2020, 225

Abstract
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. Document type: Article
Abstract
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 [...]
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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
D. Wang, P. Rasmussen, J. Dubus, A. Gonzalez

Collection of open articles in transport research (2020). Vol. 2020, 224

Abstract
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. Document type: Article
Abstract
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 [...]
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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
S. Esmene, T. Taylor, M. Leyshon

Collection of open articles in transport research (2020). Vol. 2020, 223

Abstract
Document type: Article
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Transferring Urban Mobility Studies in Tehran, Istanbul, and Cairo to Other Large MENA Cities: Steps toward Sustainable Transport
H. Masoumi, E. Fruth

Collection of open articles in transport research (2020). Vol. 2020, 222

Abstract
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. Document type: Article
Abstract
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 [...]
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A Hybrid Approach for Turning Intention Prediction Based on Time Series Forecasting and Deep Learning
H. Zhang, R. Fu

Collection of open articles in transport research (2020). Vol. 2020, 221

Abstract
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. Document type: Article
Abstract
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) [...]
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Railway Polygonized Wheel Detection Based on Numerical Time-Frequency Analysis of Axle-Box Acceleration
D. Yanliang, L. Liang, S. Ying, S. Baochen

Collection of open articles in transport research (2020). Vol. 2020, 220

Abstract
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. Document type: Article
Abstract
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 [...]
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Intelligent Driving Assistant Based on Road Accident Risk Map Analysis and Vehicle Telemetry
L. Navarro, J. Terán, C. M., M. Pardo

Collection of open articles in transport research (2020). Vol. 2020, 219

Abstract
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. Document type: Article
Abstract
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, [...]
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Gender-Responsive Public Transportation in the Dammam Metropolitan Region, Saudi Arabia
M. Al-Rashid, T. Campisi, N. Akgün, S. Ahmed, K. Nahiduzzaman

Collection of open articles in transport research (2020). Vol. 2020, 218

Abstract
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. Document type: Article
Abstract
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 [...]
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Causes and Treatment Measures of Submarine Pipeline Free-Spanning
B. Zhang, T. Wang, G. Rui, Z. Wang

Collection of open articles in transport research (2020). Vol. 2020, 217

Abstract
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. Document type: Article
Abstract
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 [...]
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A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems
J. Berling, A. Lau, M. Swaid, B. Lührs, N. Dzikus, M. Niklaß, I. Terekhov, V. Gollnick

Collection of open articles in transport research (2020). Vol. 2020, 216

Abstract
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
Abstract
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 [...]
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Investigation of the frequency of free vibrations for pipelines with different physical and mechanical properties of the material
A. Dmitriev

Collection of open articles in transport research (2020). Vol. 2020, 215

Abstract
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. Document type: Article
Abstract
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 [...]
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An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections
Y. Wang, C. Zhou, S. Liu, X. Chang, J. Rong

Collection of open articles in transport research (2020). Vol. 2020, 214

Abstract
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. Document type: Article
Abstract
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 [...]
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Sustainability of the Air Cargo Handling Process in the Context of Safety and Environmental Aspects
I. Štimac, M. Drljača, A. Vidović, S. Petar

Collection of open articles in transport research (2020). Vol. 2020, 213

Abstract
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. Document type: Article
Abstract
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 [...]
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The Impact of E-Commerce-Related Last-Mile Logistics on Cities: A Systematic Literature Review
E. Alvarez-Palau, M. Viu-Roig

Collection of open articles in transport research (2020). Vol. 2020, 212

Abstract
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
Abstract
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 [...]
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Assessment of Priorities of Construction of High-Speed Rail in the Czech Republic in Terms of Impacts on Internal and External Integration
M. Viturka, V. Pařil

Collection of open articles in transport research (2020). Vol. 2020, 211

Abstract
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
Abstract
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 [...]
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Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model
A. Kumar, Y. Nahleh, R. Alhindawi, N. Shiwakoti

Collection of open articles in transport research (2020). Vol. 2020, 210

Abstract
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
Abstract
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 [...]
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Sociodemography, Geography, and Personality as Determinants of Car Driving and Use of Public Transportation
U. Holmberg, F. Sprei, J. Roos

Collection of open articles in transport research (2020). Vol. 2020, 209

Abstract
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
Abstract
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 [...]
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Dynamic Model for Scheduling Crew Shifts
D. Teichmann, J. Horinka, M. Dorda, V. Graf

Collection of open articles in transport research (2020). Vol. 2020, 208

Abstract
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
Abstract
In regular as well as nonscheduled air transport, extraordinary situations occasionally occur, which may fundamentally disrupt the flight schedule. Fundamental disruptions [...]
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Effect of Concentric Annular Gap Flow on Wall Shear Stress of Stationary Cylinder Pipe Vehicle under Different Reynolds Numbers
J. Song, X. Jia, X. Sun

Collection of open articles in transport research (2020). Vol. 2020, 207

Abstract
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
Abstract
The tube-contained raw material pipeline hydraulic transportation technology is an optimization and improvement of traditional hydraulic capsule pipeline (HCP) transport. [...]
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Macroscopic Traffic Flow Characterization at Bottlenecks
M. Khan, Z. Khan, N. Minallahe, T. Gulliver, K. Khattak, M. Ali, A. Iftikhar

Collection of open articles in transport research (2020). Vol. 2020, 205

Abstract
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
Abstract
Traffic congestion is a significant issue in urban areas. Realistic traffic flow models are crucial for understanding and mitigating congestion. Congestion occurs at bottlenecks [...]
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Effects of Vehicle Restriction Policies on Urban Travel Demand Change from a Built Environment Perspective
X. Cheng, L. Li, T. Zhang, K. Huang, L. Qu

Collection of open articles in transport research (2020). Vol. 2020, 204

Abstract
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
Abstract
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. [...]
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MPP: A Novel Algorithm for Estimating Vehicle Space Headways from a Single Image
X. Li, X. Li, Z. Yu, Z. Yu, Q. Jiang, Q. Jiang

Collection of open articles in transport research (2020). Vol. 2020, 203

Abstract
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
Abstract
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 [...]
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A New Production-Splitting Method for the Multi-Well-Monitor System
W. Luo, C. He, J. Yu, B. Teng, J. Zhang, X. Liu

Collection of open articles in transport research (2020). Vol. 2020, 202

Abstract
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
Abstract
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 [...]
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Performance evaluation of lossy quality compression algorithms for RNA-seq data
S. Wang, R. Yu, W. Yang

Collection of open articles in transport research (2020). Vol. 2020, 201

Abstract
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
Abstract
Background Recent advancements in high-throughput sequencing technologies have generated an unprecedented amount of genomic data that must be stored, processed, and transmitted [...]
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Effect of High-Altitude Environment on Driving Safety: A Study on Drivers’ Mental Workload, Situation Awareness, and Driving Behaviour
P. Chu, W. Xinyan, B. Wu, B. Wu, Y. Weihua, C. Suping

Collection of open articles in transport research (2020). Vol. 2020, 200

Abstract
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
Abstract
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 [...]
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The Dynamical Decision Model of Intersection Congestion Based on Risk Identification
K. Lin, X. Sun, P. Jiao, H. Lu

Collection of open articles in transport research (2020). Vol. 2020, 199

Abstract
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
Abstract
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 [...]
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A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems
M. Mauro, G. Pani, M. Tizzoni, M. Carminati, J. Foschi, L. Mezzera, F. Zanetto, M. Antonelli, A. Turolla

Collection of open articles in transport research (2020). Vol. 2020, 198

Abstract
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
Abstract
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 [...]
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Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation
H. Ahn, H. Lee, B. Lee

Collection of open articles in transport research (2020). Vol. 2020, 197

Abstract
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
Abstract
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 [...]
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Assessing Sustainable Mobility Measures Applying Multicriteria Decision Making Methods
J. Damidavičius, J. Antuchevičienė, M. Burinskienė

Collection of open articles in transport research (2020). Vol. 2020, 196

Abstract
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
Abstract
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 [...]
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Nowcast models for train delays based on the railway network status
A. Thaduri

Collection of open articles in transport research (2020). Vol. 2020, 195

Abstract
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
Abstract
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 [...]
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Recognition of Functional Areas Based on Call Detail Records and Point of Interest Data
Y. Chen, L. Sun, G. Yuan, Z. Liu, T. Li, J. Lai

Collection of open articles in transport research (2020). Vol. 2020, 194

Abstract
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
Abstract
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 [...]
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Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data
L. Wang, W. Qi, B. Shen

Collection of open articles in transport research (2020). Vol. 2020, 193

Abstract
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
Abstract
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 [...]
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Efficiency Evaluation of Bus Transport Operations Given Exogenous Environmental Factors
Y. Chen, P. Bai, J. Tang, X. Wei, Q. Li

Collection of open articles in transport research (2020). Vol. 2020, 192

Abstract
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
Abstract
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 [...]
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An Application of Cluster Analysis Method to Determine Vietnam Airlines’ Ground Handling Service Quality Benchmarks
T. Wang, Y. Pham

Collection of open articles in transport research (2020). Vol. 2020, 191

Abstract
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
Abstract
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 [...]
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Seasonality Effect Analysis and Recognition of Charging Behaviors of Electric Vehicles: A Data Science Approach
O. Montoya, J. Dominguez-Jimenez, J. Campillo, E. Delahoz, J. Hernández

Collection of open articles in transport research (2020). Vol. 2020, 190

Abstract
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
Abstract
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 [...]
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A Correlative Analysis of Modern Logistics Industry to Developing Economy Using the VAR Model: A Case of Pakistan
S. Hanif, D. Mu, S. Baig, K. Alam

Collection of open articles in transport research (2020). Vol. 2020, 189

Abstract
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
Abstract
The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap [...]
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Research on the Electromagnetic-Heat-Flow Coupled Modeling and Analysis for In-Wheel Motor
M. Yuan, C. Zhao, S. Liu, H. Xue, D. Tan

Collection of open articles in transport research (2020). Vol. 2020, 188

Abstract
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
Abstract
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 [...]
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Understanding how city networks are leveraging climate action: experimentation through C40
T. Nguyen, L. Coenen, K. Davidson

Collection of open articles in transport research (2020). Vol. 2020, 187

Abstract
"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
Abstract
"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 [...]
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Defining Highway Node Acceptance Capacity (HNAC): Theoretical Analysis and Data Simulation
Y. Dong, J. Xu, X. Liu, H. Ru, Z. Duan

Collection of open articles in transport research (2020). Vol. 2020, 186

Abstract
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
Abstract
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 [...]
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Modeling Drivers’ Stopping Behaviors during Yellow Intervals at Intersections considering Group Heterogeneity
J. Li, H. Zhang, Y. Zhang, X. Zhang

Collection of open articles in transport research (2020). Vol. 2020, 185

Abstract
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
Abstract
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 [...]
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Research on Consumers’ Preferences for the Self-Service Mode of Express Cabinets in Stations Based on the Subway Distribution to Promote Sustainability
L. Sun, T. Ting, D. Xuan, X. Guo, J. Xiaohong, L. Tengfei

Collection of open articles in transport research (2020). Vol. 2020, 184

Abstract
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
Abstract
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 [...]
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The influence of economic barriers and drivers on energy efficiency investments in maritime shipping, from the perspective of the principal-agent problem
J. Pérez-López, A. Calvo-Silvosa, Á. Longarela-Ares

Collection of open articles in transport research (2020). Vol. 2020, 183

Abstract
[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
Abstract
[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 [...]
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Quantifying the Impact of Rainfall on Taxi Hailing and Operation
Y. Tian, J. Sun, H. Dong, G. Qin

Collection of open articles in transport research (2020). Vol. 2020, 182

Abstract
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
Abstract
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 [...]
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Energy-Efficient Direct Yaw Moment Control for In-Wheel Motor Electric Vehicles Utilising Motor Efficiency Maps
P. Sun, A. Stensson Trigell, L. Drugge, J. Jerrelind

Collection of open articles in transport research (2020). Vol. 2020, 181

Abstract
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
Abstract
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. [...]
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Passenger Volume Prediction by a Combined Input-Output and Distributed Lag Model and Data Analytics of Industrial Investment
F. Yang, Z. Huang, H. Yuan, J. Wang, W. Li, S. Wang

Collection of open articles in transport research (2020). Vol. 2020, 180

Abstract
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
Abstract
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 [...]
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Real-Time Incident Detection and Capacity Estimation Using Loop Detector Data
S. Rizvi, Y. Shen, A. Ahmed

Collection of open articles in transport research (2020). Vol. 2020, 179

Abstract
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
Abstract
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 [...]
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A Deep Cycle Limit Learning Machine Method for Urban Expressway Traffic Incident Detection
Y. Fang, B. Peng, L. Zheng, X. Zhou, Q. Yang

Collection of open articles in transport research (2020). Vol. 2020, 178

Abstract
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
Abstract
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. [...]
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A computational framework for revealing competitive travel times with low carbon modes based on smartphone data collection
J. Nurminen, J. Nurminen, M. Mladenovic, I. Kosonen, M. Bagheri, A. Ylä-Jääski, C. Roncoli

Collection of open articles in transport research (2020). Vol. 2020, 177

Abstract
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
Abstract
Evaluating potential of shifting to low-carbon transport modes requires considering limited travel-time budget of travelers. Despite previous studies focusing on time-relevant [...]
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The Relationship between Bus Drivers’ Improper Driving Behaviors and Abnormal Vehicle States Based on Advanced Driver Assistance Systems in Naturalistic Driving
W. Li, T. Wang, X. Yan, J. Chen, Y. Chen

Collection of open articles in transport research (2020). Vol. 2020, 176

Abstract
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
Abstract
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 [...]
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A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting
P. Wu, Z. Huang, Y. Pian, L. Xu, J. Li, K. Chen

Collection of open articles in transport research (2020). Vol. 2020, 175

Abstract
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
Abstract
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 [...]
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Internal versus external European air market realities: the competitive divide
D. Ellis

Collection of open articles in transport research (2020). Vol. 2020, 174

Abstract
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
Abstract
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. [...]
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Fatigue Driving Prediction on Commercial Dangerous Goods Truck Using Location Data: The Relationship between Fatigue Driving and Driving Environment
S. Niu, G. Li

Collection of open articles in transport research (2020). Vol. 2020, 173

Abstract
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
Abstract
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 [...]
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Driving Simulator Validity of Driving Behavior in Work Zones
Z. Yanning, Z. Sun, G. Zhongyin

Collection of open articles in transport research (2020). Vol. 2020, 172

Abstract
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
Abstract
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 [...]
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Moving a Taxi Sector to Become Electric: Characterizing Taxi Drivers Interested in Purchasing a Full Electric Vehicle
M. Tamis, R. Hoed

Collection of open articles in transport research (2020). Vol. 2020, 170

Abstract
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
Abstract
Electrification of mobility exceeds personal transport to increasingly focus on particular segments such as city logistics and taxis. These commercial mobility segments have [...]
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