Scipedia: Documents published in 2017

Multi-lane perception using feature fusion based on GraphSLAM

Scipedia content — Wed, 03 Feb 2021 16:47:09 +0100

n extensive, precise and robust recognition and modeling of the environment is a key factor for next generations of Advanced Driver Assistance Systems and development of autonomous vehicles. In this paper, a real-time approach for the perception of multiple lanes on highways is proposed. Lane markings detected by camera systems and observations of other traffic participants provide the input data for the algorithm. The information is accumulated and fused using GraphSLAM and the result constitutes the basis for a multi-lane clothoid model. To allow incorporation of additional information sources, input data is processed in a generic format. Evaluation of the method is performed by comparing real data, collected with an experimental vehicle on highways, to a ground truth map. The results show that ego and adjacent lanes are robustly detected with high quality up to a distance of 120 m. In comparison to serial lane detection, an increase in the detection range of the ego lane and a continuous perception of neighboring lanes is achieved. The method can potentially be utilized for the longitudinal and lateral control of self-driving vehicles.

Optimization Water Leakage Detection using Wireless Sensor Networks (OWLD)

Scipedia content — Wed, 03 Feb 2021 16:43:10 +0100

This paper presents a technical method to monitor the water distribution pipelines against leakage and to control the pump when the water level decreases in the tank. Water leakage is the most popular cause of water wasted in the domestic water distribution systems. Nowadays most people have their smartphone nearby them; therefore, adding an interface on the smartphone to control an automated system is a big plus. Energy saving is a benefit of the Optimization Water Leakage Detection (OWLD) system. It enables us to save energy, time and cost by having smart leakage detection in pipelines, measuring the water level in the tank and controlling the pump when the water level is low. This paper focuses mainly on two parts: The first part is an alarm based on Global System for Mobile technology (GSM) to send a Short Message Service (SMS) to the owner. This is made up of the following components: sensors, GSM Module, Arduino and relays to control the device. The second is the controlling part; it uses android application mobile to control the pump. The proposed system can effectively improve the efficiency of operation, reduce delay time and cost of maintenance pipelines after leakage detection.

Reconfiguring the Imaging Pipeline for Computer Vision

Scipedia content — Wed, 03 Feb 2021 16:38:27 +0100

dvancements in deep learning have ignited an explosion of research on efficient hardware for embedded computer vision. Hardware vision acceleration, however, does not address the cost of capturing and processing the image data that feeds these algorithms. We examine the role of the image signal processing (ISP) pipeline in computer vision to identify opportunities to reduce computation and save energy. The key insight is that imaging pipelines should be designed to be configurable: to switch between a traditional photography mode and a low-power vision mode that produces lower-quality image data suitable only for computer vision. We use eight computer vision algorithms and a reversible pipeline simulation tool to study the imaging system's impact on vision performance. For both CNN-based and classical vision algorithms, we observe that only two ISP stages, demosaicing and gamma compression, are critical for task performance. We propose a new image sensor design that can compensate for skipping these stages. The sensor design features an adjustable resolution and tunable analog-to-digital converters (ADCs). Our proposed imaging system's vision mode disables the ISP entirely and configures the sensor to produce subsampled, lower-precision image data. This vision mode can save ~75% of the average energy of a baseline photography mode while having only a small impact on vision task accuracy.

Two capacitive-pulling techniques to aid the settling of SC residue amplifier

Scipedia content — Wed, 03 Feb 2021 16:37:01 +0100

This paper presents two capacitive-pulling techniques to aid the settling of the switched-capacitor residue amplifier in a pipeline analog to digital converter. The main idea is to pre-charge the load capacitors to proper voltages, connect them to the output of the operational trans-conductance amplifiers (OTAs) during the evaluation phase, and hence pull the passive charge sharing so that the initial voltage step of the OTA input is instantly minimized. The OTA hence skips the slew region, and enters into the linear settling region, leaving just a minor charge to be moved by the OTA. This allows you to get the same settling precision with saving 30% power consumption of the OTA using minimal three-level pre-charged method. Alternatively, the conversion rate can be increased by over 30% using the continuously controlled pre-charged method.

Can Low Cost Road Engineering Measures Combat Driver Fatigue? A Driving Simulator Investigation

Scipedia content — Wed, 03 Feb 2021 16:33:42 +0100

Driver fatigue is a major cause of road accidents, accounting for over 20% of serious accidents on motorways and monotonous roads in the U.K. This study investigated the potential for low-cost, road-based, engineering measures to act as alerting features in an otherwise monotonous driving environment and hence combat fatigue. Thirty-three drivers took part in the driving simulator study. There was some evidence of an alerting effect provided to drivers by all three of the treatments tested: chevron road-surface markings, transverse- carriageway rumble strips and variable message signs. However, the alerting effect did appear to be relatively weak and potentially quite short-lived. Nevertheless, there may well be potential for any of the novel alerts to be deployed in the field in a known fatigue-related accident area.

Improving Continuous Integration with Similarity-based Test Case Selection

Scipedia content — Wed, 03 Feb 2021 16:30:10 +0100

utomated testing is an essential component of Continuous Integration (CI) and Delivery (CD), such as scheduling automated test sessions on overnight builds. That allows stakeholders to execute entire test suites and achieve exhaustive test coverage, since running all tests is often infeasible during work hours, i.e., in parallel to development activities. On the other hand, developers also need test feedback from CI servers when pushing changes, even if not all test cases are executed. In this paper we evaluate similarity-based test case selection (SBTCS) on integration-level tests executed on continuous integration pipelines of two companies. We select test cases that maximise diversity of test coverage and reduce feedback time to developers. Our results confirm existing evidence that SBTCS is a strong candidate for test optimisation, by reducing feedback time (up to 92% faster in our case studies) while achieving full test coverage using only information from test artefacts themselves. Software Center: Aspects of Automated Testing

Improving Small Object Proposals for Company Logo Detection

Scipedia content — Wed, 03 Feb 2021 16:27:10 +0100

Many modern approaches for object detection are two-staged pipelines. The first stage identifies regions of interest which are then classified in the second stage. Faster R-CNN is such an approach for object detection which combines both stages into a single pipeline. In this paper we apply Faster R-CNN to the task of company logo detection. Motivated by its weak performance on small object instances, we examine in detail both the proposal and the classification stage with respect to a wide range of object sizes. We investigate the influence of feature map resolution on the performance of those stages. Based on theoretical considerations, we introduce an improved scheme for generating anchor proposals and propose a modification to Faster R-CNN which leverages higher-resolution feature maps for small objects. We evaluate our approach on the FlickrLogos dataset improving the RPN performance from 0.52 to 0.71 (MABO) and the detection performance from 0.52 to 0.67 (mAP).

Comment: 8 Pages, ICMR 2017

Sustainability assessment of a transportation system under uncertainty: a multi-criteria analysis approach

Scipedia content — Wed, 03 Feb 2021 16:25:25 +0100

International audience; Urban development is a critical issue that many cities are facing, due to the demography growth which results from the economic attractiveness of the urban centers. Based on common standards such as the Urban Development Plans, some projects for transportation systems renewal are progressively launched. In order to allow social cohesion, especially by providing travelers with services which may allow to better organize the transport, it is necessary to structure the transportation system according to sustainability requirements. This paper examines an integrated approach for assessing the sustainability of the current transportation system design, based on a policy making problem, aiming at providing decision makers with a framework allowing them to choose the most eco-responsible policy amongst many alternatives. Since the sustainability indicators may conflict each other, in order to better take into account the requirements of the whole transportation system in its design phase, a system-based approach has been adopted to characterize the complex structure of these indicators. A general methodology for their elicitation is proposed, using a process-object methodology and based on surveys from recent research on sustainable transportation, along with eco-design principles, in order to take into account urban transport priorities, sustainability challenges and the analysis of the whole lifecycle of the transport infrastructure and equipment. To validate this proposal, a multi-criteria decision method, allowing subjectivity, uncertainty, incomplete judgments and group consensus is then performed, based on a case study which shows the flexibility of fuzzy analytical hierarchy process for such assessment.

National transport policy in Austria – from its beginning till today

Scipedia content — Wed, 03 Feb 2021 16:20:24 +0100

Introduction The objective of the paper is to research the historic development of the Austrian transport policy. It explores when a transport strategy was made for the first time, from whom, and which purpose was pursuit. It shows how the objectives of the transport strategy changed over time and when passenger and freight transport took over to become the main focus of the planning process. Furthermore it is researched when, and if, there was a change from a solely sectorial mono-modal transport strategy (road, rail separated) towards an integrated transport planning process and when, and if, there was a development away from a demand-fulfillment-driven transport planning paradigm towards a transport-demand-management driven transport planning strategy.

Document type: Article

A Decentralised Approach to Intersection Traffic Management

Scipedia content — Wed, 03 Feb 2021 16:19:30 +0100

Traffic congestion has a significant impact on quality of life and the economy. This paper presents a decentralised traffic management mechanism for intersections using a distributed constraint optimisation approach (DCOP). Our solution outperforms the state of the art solution both for stable traffic conditions (about 60% reduced waiting time) and robustness to unpredictable events.

Analysing The Congestion Impact Of Deliveries Schedule Observation In Urban Construction Sites

Scipedia content — Wed, 03 Feb 2021 16:19:05 +0100

In the context of urban construction logistics, this paper analyses the usage of delivery schedules, their observation and their impact on congestion. Logistics data were collected during 8 months on 4 construction sites in 4 European cities. Using qualitative and quantitative analyses, the authors expose the specificities of construction logistics and its impact in urban areas, in particular the impact of delivery time window scheduling on roads and site congestion. In conclusion, the authors propose solution leads that will be further explored in the framework of a European project, among others the use of Construction Consolidation Centres in urban areas.

Neighborhood-Based Recovery of Phase Unwrapping Faults

Scipedia content — Wed, 03 Feb 2021 16:18:50 +0100

mong several structured light approaches, phase shift is the most widely adopted in real-world 3D reconstruction devices. This is mainly due to its high accuracy, strong resilience to noise and straightforward implementation. However, Phase shift also exhibits an inherent weakness, that is the spatial ambiguity resulting from the periodicity of the sinusoidal wave adopted. Of course many phase unwrapping methods have been proposed to solve such ambiguity. One of the most promising methods exploits additional signals of mutually prime periods, in order to observe a distinct combination of phases for each spatial point. Unfortunately, for such combination to be properly recognized, a very high accuracy in phase recovery must be attained for each signal. In fact, even modest errors could lead to unwrapping faults, making the overall approach much less resilient to noise than plain phase shift. With this paper we introduce a feasible and effective fault recovery method that can be directly applied to multi-period phase shift. The combined pipeline offers an optimal accuracy and coverage even with high noise conditions, overcoming the setbacks of the original method. The performance of such pipeline is established by means of an in depth set of experimental evaluations and comparison, both with real and synthetically generated data.

Analysis of a Workload Model Learned from Past Sector Operations

Scipedia content — Wed, 03 Feb 2021 16:13:07 +0100

International audience; In this paper, we assess the performance of a workload model trained on a subset of sectors, focusing on how it generalizes on fresh sectors. The model of the air traffic controller workload is learned from historical data made of workload mesurements extracted from past sector operations and ATC complexity measurements computed from radar records and airspace data (sector geometry). The workload is assumed to be low when a given sector is collapsed with other sectors into a larger sector, normal when it is operated as is, and high when it is split into smaller sectors assigned to several working positions. This learning problem is modeled as a classification problem where the target variable is a workload category (low, normal, high) and the explanatory variables are the air traffic control (ATC) complexity metrics. In previous work, we compared several classifiers on this problem. The models were trained on one week of traffic, and their generalization performance was assessed on another week of traffic, using the same sectors in both the training and test sets. In the current work, we examine if models learned on a specific set of sectors can be performant on any other sector, or not. We also give a closer look at how the workload varies with the ATC complexity measures in our data, using bagplots of the data points for a few sector instances. The results allow us to better understand the strengths and limits of our data-driven model.

Generation of variability in shape, aspect and time of 3D Fruits and Vegetables

Scipedia content — Wed, 03 Feb 2021 16:11:32 +0100

International audience; With the growth of organic Fruits and Vegetables (FaVs) markets, there is now a trend in marketing research toward studies of non-standardized fruits and vegetables in stores. Yet, because of the decaying nature of FaVs, it is difficult to conduct such studies. A solution is to conduct them within a Virtual Environment (VE) (with virtual FaVs). Therefore, it is of interest to develop an approach to generate a large variety and variability of FaVs, so one can later use them in a VE. In this paper we introduce a pipeline to generate a large variability of FaVs, focusing both on their shape and on their external appearance. Regarding the shape, we use a semi-automated approach. A parametric Skeletal Structure and Generalized Cylinders (GCs) generates their overall shape and metaball-based techniques give them an organic aspect. Regarding their external appearance, we use a particle system approach to simulate their modifications over time. This particle system-based approach decomposes FaVs appearance changes into distinct visual characteristics producing different texture maps that can be combined.

Optimization design of urban expressway ramp control

Scipedia content — Wed, 03 Feb 2021 16:06:14 +0100

In this paper, various types of expressway systems are analyzed, and a variety of signal combinations are proposed to mitigate traffic congestion. And various signal combinations are used to verify the effectiveness of the multi-signal combinatorial control strategy. The simulation software VISSIM was used to simulate the system. Based on the network model of 25 kinds of road length combinations and the simulation results, an optimization scheme suitable for the practical road model is summarized. The simulation results show that the controller can reduce the travel time by 25% under the large traffic flow and improve the road capacity by about 20%.

CAR-TO-CYCLIST CRASHES IN EUROPE AND DERIVATION OF USE CASES AS BASIS FOR TEST SCENARIOS OF NEXT GENERATION ADVANCED DRIVER ASSISTANCE SYSTEMS – RESULTS FROM PROSPECT

Scipedia content — Wed, 03 Feb 2021 16:03:51 +0100

Systems available on the market address also conflicts with vulnerable road users (VRUs) such as pedestrians"br" and cyclists. Within the European project PROSPECT (Horizon2020, funded by the EC) improved VRU ADAS"br" systems are developed and tested. However, before determining systems’ properties and starting testing, an"br" up-to-date analysis of VRU crashes was needed in order to derive the most important Use Cases (detailed"br" crash descriptions) the systems should address. Besides the identified Accident Scenarios (basic crash"br" descriptions), this paper describes in short the method of deriving the Use Cases for car-to-cyclist crashes."br" Method"br" Crashes involving one passenger car and one cyclist were investigated in several European crash databases"br" looking for all injury severity levels (slight, severe and fatal). These data sources included European statistics"br" from CARE, data on national level from Germany, Sweden and Hungary as well as detailed accident"br" information from these three countries using GIDAS, the Volvo Cars Cyclist Accident database and Hungarian"br" in-depth accident data, respectively. The most frequent accident scenarios were studied and Use Cases were"br" derived considering the key aspects of these crash situations (e.g., view orientation of the cyclist and the car"br" driver’s manoeuvre intention) and thus, form an appropriate basis for the development of Test Scenarios."br" Results"br" Latest information on car-to-cyclist crashes in Europe was compiled including details on the related crash"br" configurations, driving directions, outcome in terms of injury severity, accident location, other environmental"br" aspects and driver responsibilities. The majority of car-to-cyclist crashes occurred during daylight and in clear weather conditions. Car-to-cyclist crashes in which the vehicle was traveling straight and the cyclist is moving"br" in line with the traffic were found to result in the greatest number of fatalities. Considering also slightly and"br" seriously injured cyclists led to a different order of crash patterns according to the three considered"br" European countries. Finally the paper introduced the Use Cases derived from the crash data analysis. A total"br" of 29 Use Cases were derived considering the group of seriously or fatally injured cyclists and 35 Use Cases"br" were derived considering the group of slightly, seriously or fatally injured cyclists. The highest ranked Use"br" Case describes the collision between a car turning to the nearside and a cyclist riding on a bicycle lane"br" against the usual driving direction."br" Discussion"br" A unified European dataset on car-to-cyclist crash scenarios is not available as the data available in CARE is"br" limited, hence national datasets had to be used for the study and further work will be required to extrapolate"br" the results to a European level. Due to the large number of Use Cases, the paper shows only highest ranked"br" ones.

Message dissemination scheduling for multiple cooperative drivings

Scipedia content — Wed, 03 Feb 2021 16:02:53 +0100

With the advances of control and vehicular communication technologies, a group of connected and autonomous (CA) vehicles can drive cooperatively to form a so-called cooperative driving pattern, which has been verified to significantly improve road safety, traffic efficiency and the environmental sustainability. A more general scenario that various types of cooperative driving, such as vehicle platooning and traffic monitoring, coexist on roads will appear soon. To support such multiple cooperative drivings, it is critical to design an efficient scheduling algorithm for periodical message dissemination, i.e. beacon, in a shared communication channel, which has not been fully addressed before. In this paper, we consider multiple cooperative drivings in a bidirectional road, and propose both the decentralized and the RSU-assisted centralized beacon scheduling algorithms which aim at guaranteeing reliable delivery of beacon messages for cooperative drivings as well as maximizing the channel utilization. Numerical results confirm the effectiveness of the proposed algorithms.

Governing Urban Mobility. Strong Urban Governance for Liveable Cities:Lessons from the CREATE Project

Scipedia content — Wed, 03 Feb 2021 16:00:54 +0100

Why have some cities in Europe been able to achieve a shift from the car-oriented city towards more sustainable modes of transport? How can other parts of Europe and the EuroMed draw lessons from CREATE? In order to answer these fundamental questions, the CREATE (Congestion Reduction in Europe, Advancing Transport Efficiency) project’s main objective is to reduce road congestion in European cities by encouraging a switch from cars to more sustainable modes of transport. Among other valuable lessons, the CREATE project shows how strong urban governance contributes to the shift towards the liveable city.

Implementing an ISR defense on a MIPS architecture

Scipedia content — Wed, 03 Feb 2021 16:00:42 +0100

Code injection attacks are an undeniable threat in today's cyberworld. Instruction Set Randomization (ISR) was initially proposed in 2003. This technique was designed to protect systems against code injection attacks by creating an unique instruction set for each machine, thanks to randomization. It is a promising technique in the growing embedded system and Internet of Things (IoT) devices ecosystem, where the lack of complex memory management make these devices more vulnerable. However, most of ISR implementations up to day are entirely software based. In this work, we implement hardware support for an ISR defense on an 32 bits, 5 pipeline stages MIPS processor (which is an embedded system compatible architecture). Two obfuscation schemes were implemented, one based on XOR encryption and the other on transposition. The hardware implementation was tested under synthetic code injection attacks and results shows the effectiveness of the defense using both encryption circuits.

Greybox Design Methodology

Scipedia content — Wed, 03 Feb 2021 15:58:56 +0100

In this paper, a novel Greybox design methodology is proposed to establish a design and co-optimization flow across the boundary of conventional software and hardware design. The dynamic timing of each software instruction is simulated and associated with processor hardware design, which provides the basis of ultra-dynamic clock management. The proposed scheme effectively implements the instruction-based clock management and achieves 21.71% frequency speedup. Besides, a novel program-driven hardware optimization flow is proposed, in which software operations are mapped with hardware gate netlist and sorted by the usage frequency. The experiments on an ARM based pipeline design in commercial 65nm CMOS process show an extra 10% frequency speedup is obtained with high optimization efficiency. Overall, the proposed Greybox design method achieves frequency speedup by 31.56%, comparing with conventional design method.

Market integration VS temporal granularity: How to provide needed flexibility resources?

Scipedia content — Wed, 03 Feb 2021 15:58:10 +0100

International audience; The aim of this paper is to study the implications of the decision of the French regulator to join the FCR Cooperation, a common platform for cross-border procurement of primary reserve. Two aspects will be analyzed: 1) cost of procurement and increase of social welfare by cross-border procurement and 2) implications for entry of new entrants like aggregators of Electric Vehicles. Our results are that joining the FCR Cooperation will impact negatively participation of aggregators and might not result to lower costs for procurement of reserve.

On the value of device flexibility in smart grid applications

Scipedia content — Wed, 03 Feb 2021 15:57:18 +0100

Demand-side management and demand response are proposed as a means to solve different objectives in smart grids, such as, e.g., maximizing self-consumption of a house or peak shaving. Crucial components in these approaches are load shiftable/steerable devices, so-called smart appliances. Although several studies already use these devices and determine how to use their flexibility, their impact on — or value for — the overall system is not studied. This paper provides a methodology to calculate the value of flexibility of smart devices. The methodology makes it possible to quantitatively compare the impact of these devices for different kinds of objectives. The developed methodology is applied in a case study to compare the flexibility of white goods, home batteries and electric vehicles. The results indicate among others that smart white goods may not always be that important for smart grids.

A Simulation Tool to Assess the Integration of Cargo Bikes into an Urban Distribution System

Scipedia content — Wed, 03 Feb 2021 15:56:53 +0100

International audience; The use of cargo bikes for goods deliveries represents a promising concept of urban logistics. In this contribution, a new simulation-based assessment tool integrating this emission free vehicles in urban distribution systems is presented. First, typical schemes are identified and an analysis of the underlying planning problems is conducted. Second, the developed GIS-based discrete-event simulation model and the coupled tour-planning algorithm are described, implementing the pattern of control optimization. To the best of our knowledge, such a tool is not yet existing. Finally, the tool is applied, evaluating the potential use of cargo bikes for B2B-deliveries in the medium size city of Grenoble in France.

BiAgent-Based Model for IoT Applications

Scipedia content — Wed, 03 Feb 2021 15:56:11 +0100

International audience; The Internet of Things (IoT) consists in connecting every aspect of daily and professional life to a common infrastructure, in order to improve considerably the efficiency of otherwise unthinking objects. The huge scale on which they operate, as well as the lack of adequate standards and infrastructures makes the development of IoT applications a task of gradually growing complexity. The objective of this work is to define a formal model with BiAgents (Bigraphical Agents) for IoT applications, based on a suggested generic multi-layered architecture. We show how bigraphs support the structural aspects modelisation of these applications while the agents specify their analytical and decisional aspects. We proceed then to the edition and execution of our model using the bigraph implementation tool (RCTool4 Bigraphs), and through the exploitation of its model-checker, we formally verify its most critical property. As a practical example, we study the case of a Collision Avoidance System.

Adaptive control design for nonlinear systems via successive approximations

Scipedia content — Wed, 03 Feb 2021 15:55:56 +0100

Date of Conference: 11–13 October 2017 Conference Name: ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 The paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies.

Privacy-Preserving Detection of Inter-Domain SDN Rules Overlaps

Scipedia content — Wed, 03 Feb 2021 15:51:18 +0100

SDN approaches to inter-domain routing promise better traffic engineering, enhanced security, and higher automation. Yet, naive deployment of SDN on the Internet is dangerous as the control-plane expressiveness of BGP is significantly more limited than the data-plane expressiveness of SDN, which allows fine-grained rules to deflect traffic from BGP's default routes. This mismatch may lead to incorrect forwarding behaviors such as forwarding loops and blackholes, ultimately hindering SDN deployment at the inter-domain level. In this work, we make a first step towards verifying the correctness of inter-domain forwarding state with a focus on loop freedom while keeping private the SDN rules, as they comprise confidential routing information. To this end, we design a simple yet powerful primitive that allows two networks to verify whether their SDN rules overlap, i.e., the set of packets matched by these rules is non-empty, without leaking any information about the SDN rules. We propose an efficient implementation of this primitive by using recent advancements in Secure Multi-Party Computation and we then leverage it as the main building block for designing a system that detects Internet-wide forwarding loops among any set of SDN-enabled Internet eXchange Points.

Mechanism for Investment in the Transport Infrastructure Development in Latvia

Scipedia content — Wed, 03 Feb 2021 15:46:04 +0100

Well-developed and efficient infrastructure is crucial for ensuring the effective functioning of the economy. A considerable lack of industry financing certainly affects the assessment of the quality of the overall infrastructure in a global context; according to the report by the World Economic Forum, Latvia languished in 51st position in its global league table for overall quality of the transport infrastructure provision [1]. In countries that have a high rating on the quality of the overall infrastructure, for example, Germany and Great Britain, appropriate investment mechanisms have been developed. They set benchmarks for decision-making and evaluation of investment efficiency. The goal of this study is to develop a conceptual approach to the creation of an investment mechanism for Latvia, based on the experience of Germany and other countries having a high rating of the quality of the overall infrastructure. In general, the results of the study can be useful in developing financial mechanism for investing in the development of transport infrastructure in Latvia as an integral part of the investment policy for the industry development.

Mass flow measurement of gas-liquid two-phase CO 2 in CCS transportation pipelines using Coriolis flowmeters

Scipedia content — Wed, 03 Feb 2021 15:45:12 +0100

Carbon Capture and Storage (CCS) is a promising technology that stops the release of CO\$_2\$ from industrial processes such as electrical power generation. Accurate measurement of CO\$_2\$ flows in a CCS system where CO\$_2\$ flow is a gas, liquid, or gas-liquid two-phase mixture is essential for the fiscal purpose and potential leakage detection. This paper presents a novel method based on Coriolis mass flowmeters in conjunction with least squares support vector machine (LSSVM) models to measure gas-liquid two-phase CO\$_2\$ flow under CCS conditions. The method uses a classifier to identify the flow pattern and individual LSSVM models for the metering of CO2 mass flowrate and prediction of gas volume fraction of CO\$_2\$, respectively. Experimental work was undertaken on a multiphase CO\$_2\$ flow test facility. Performance comparisons between the general LSSVM and flow pattern based LSSVM models are conducted. Results demonstrate that Coriolis mass flowmeters with the LSSVM model incorporating flow pattern identification algorithms perform significantly better than those using the general LSSVM model. The mass flowrate measurement of gas-liquid CO\$_2\$ is found to yield errors less than ±2% on the horizontal pipeline and ±1.5% on the vertical pipeline, respectively, over flowrates from 250 kg/h to 3200 kg/h. The error in the estimation of CO\$_2\$ gas volume fraction is within ±10% over the same range of flow rates.

Document type: Article

Vehicle rebalancing for Mobility-on-Demand systems with ride-sharing

Scipedia content — Wed, 03 Feb 2021 15:43:43 +0100

Recent developments in Mobility-on-Demand (MoD) systems have demonstrated the potential of road vehicles as an efficient mode of urban transportation Newly developed algorithms can compute vehicle routes in real-time for batches of requests and allow for multiple requests to share vehicles. These algorithms have primarily focused on optimally producing vehicle schedules to pick up and drop off requests. The redistribution of idle vehicles to areas of high demand, known as rebalancing, on the contrary has received little attention in the context of ride-sharing. In this paper, we present a method to rebalance idle vehicles in a ride-sharing enabled MoD fleet. This method consists of an algorithm to optimally partition the fleet operating area into rebalancing regions, an algorithm to determine a real-time demand estimate for every region using incoming requests, and an algorithm to optimize the assignment of idle vehicles to these rebalancing regions using an integer linear program. Evaluation with historical taxi data from Manhattan shows that we can service 99.8% of taxi requests in Manhattan using 3000 vehicles with an average waiting time of 57.4 seconds and an average in-car delay of 13.7 seconds. Moreover, we can achieve a higher service rate using 2000 vehicles than prior work achieved with 3000. Furthermore, with a fleet of 3000 vehicles, we reduce the average travel delay by 86%, the average waiting time by 37%, and the amount of ignored requests by 95% compared to earlier work at the expense of an increased distance travelled by the fleet.

Short-term 4D Trajectory Prediction Using Machine Learning Methods

Scipedia content — Wed, 03 Feb 2021 15:38:04 +0100

International audience; 4D trajectory prediction is the core element of future air transportation system, which is intended to improve the operational ability and the predictability of air traffic. In this paper, we introduce a novel model to address the short-term trajectory prediction problem in Terminal Manoeuvring Area (TMA) by application of machine learning methods. It consists of two parts: clustering-based preprocessing part and Multi-cells Neural Network (MCNN)-based machine learning part. First, in the preprocessing part, Principle Component Analysis (PCA) is applied to the real 4D trajectory dataset for reducing the vector variable dimensions. Then, the trajectories are clustered into partitions and noises by Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method. After that, the Neural Network (NN) model is chosen as machine learning method to find out the good predicting model for each individual cluster cell. Finally, with the real traffic data in Beijing TMA, the predicted Estimated Time of Arrival (ETA) for each flight is generated. Experiment results demonstrate that our proposed method is effective and robust in the short-term 4D trajectory prediction. In addition, it can make an accurate trajectory prediction in terms of MAE and RMSE with regards to comparative models.

The Application Research of Oil Pipeline Patrol by UAV in PCOC

Scipedia content — Wed, 03 Feb 2021 15:32:43 +0100

Accent Adaptation for the Air Traffic Control Domain

Scipedia content — Wed, 03 Feb 2021 15:31:09 +0100

Road fuel taxes in Europe: Do they internalize road transport externalities?

Scipedia content — Wed, 03 Feb 2021 15:29:22 +0100

Countries in Europe have road fuel taxes and these account for roughly half of the net fuel price. We compare current road fuel taxes and corrective taxes, estimated on the basis of negative externalities from road transport for 22 European countries, taking into account the effect of fuel taxation on fuel efficiency. We focus on cars running on diesel or petrol and commercial vehicles running on diesel. If fuel taxes were intended to internalize all road transport externalities, then a number of countries could be considered to be on the right path already in what respects petrol taxation. Diesel, on the other hand, seems to be under-taxed in all 22 countries. Petrol tax increases would be in order in some countries and diesel tax increases would be in order in all 22 countries, at least as a bridge until fine-tuned policies, such as widespread peak congestion pricing or pay-as-you-drive insurance can be put in place.

A Rational Agent Controlling an Autonomous Vehicle: Implementation and Formal Verification

Scipedia content — Tue, 02 Feb 2021 08:47:35 +0100

The development and deployment of Autonomous Vehicles (AVs) on our roads is not only realistic in the near future but can also bring significant benefits. In particular, it can potentially solve several problems relating to vehicles and traffic, for instance: (i) possible reduction of traffic congestion, with the consequence of improved fuel economy and reduced driver inactivity; (ii) possible reduction in the number of accidents, assuming that an AV can minimise the human errors that often cause traffic accidents; and (iii) increased ease of parking, especially when one considers the potential for shared AVs. In order to deploy an AV there are significant steps that must be completed in terms of hardware and software. As expected, software components play a key role in the complex AV system and so, at least for safety, we should assess the correctness of these components. In this paper, we are concerned with the high-level software component(s) responsible for the decisions in an AV. We intend to model an AV capable of navigation; obstacle avoidance; obstacle selection (when a crash is unavoidable) and vehicle recovery, etc, using a rational agent. To achieve this, we have established the following stages. First, the agent plans and actions have been implemented within the Gwendolen agent programming language. Second, we have built a simulated automotive environment in the Java language. Third, we have formally specified some of the required agent properties through LTL formulae, which are then formally verified with the AJPF verification tool. Finally, within the MCAPL framework (which comprises all the tools used in previous stages) we have obtained formal verification of our AV agent in terms of its specific behaviours. For example, the agent plans responsible for selecting an obstacle with low potential damage, instead of a higher damage obstacle (when possible) can be formally verified within MCAPL. We must emphasise that the major goal (of our present approach) lies in the formal verification of agent plans, rather than evaluating real-world applications. For this reason we utilised a simple matrix representation concerning the environment used by our agent.

Comment: In Proceedings FVAV 2017, arXiv:1709.02126

Managing Safety Data: the TOKAI Experience for the Air Navigation Service Providers

Scipedia content — Tue, 02 Feb 2021 08:47:23 +0100

Socio-technical systems such as the Air Traffic Management (ATM) system have become increasingly complex in the last decades and a call for systematic data analyses is necessary to manage operations and related criticalities. In the context of risk and safety management, it thus become central to allow structured and complete in-depth understanding of safety performance, especially in relation to safety events (accidents, incidents, near-misses). Following relevant international and EU regulations (ICAO Annex 13, EC Directive 2003/42/EC, EU 376/2014, etc.), EUROCONTROL developed the TOKAI (Toolkit for ATM Occurrence Investigation) as a tool to support occurrence investigation and generate a structured repository for safety data management. This paper aims to present the general features of TOKAI, also in line with the legislative context. The paper provides an overview on how incident data from TOKAI may contribute to support an effective data management in aviation, by means of exemplar statistical analysis to support the decision-making at different organizational levels.

Combined Driver Distraction and Intention Algorithm for Maneuver Prediction and Collision Avoidance

Scipedia content — Tue, 02 Feb 2021 08:47:08 +0100

Driver intention detection holds high potential for adaptive driver assistance systems and automated driving functions. To develop a combined driver distraction and intention model as well as an intention detection algorithm a real driving study with 45 subjects performing 1260 braking and 1890 evasion maneuvers was conducted and analyzed. The driver`s distraction level and hand position are varied to analyze their influence on driver intention. With a probabilistic approach, a sensitivity analysis of indicators for detecting driver intention was developed. The accelerator pedal and the longitudinal and lateral accelerations reveal to be most sensitive for evasion, while the longitudinal acceleration, the brake pressure and the accelerator pedal are most sensitive for braking. By using this sensitivities for algorithm design and combining them with information about whether drivers have recognized the object and their distraction level, evasion maneuvers can be detected correctly at least three seconds prior to passing the object in 91 % of all cases, braking maneuvers in 87 % of all cases. The driver`s distraction level turned out to be relevant for intention recognition, as 87 % of drivers reduce their distraction at least three seconds prior to passing the object. We conclude that drivers cannot have a relevant intention and be highly distracted at the same time. Driver distraction detection hence contributes to the driver intention recognition. A three seconds prediction frame allow effective risk mitigation by warning and automated interventions.

How Education and Training May be Used to Increase Eco-friendly Transports

Scipedia content — Tue, 02 Feb 2021 08:45:33 +0100

The aim of this paper is to demonstrate how education and training may be used to increase the use of eco-friendly transport modes for freight transport. Due to an increase in education and training people’s awareness for the eco-friendly transport mode inland navigation should be enhanced. The results of this paper are part of the education cooperation “REWWay”. Qualitative empiric research in form of expert interviews and focus groups is used to identify stakeholders’ needs for education and training for eco-friendly freight transport. The research sample consists of secondary, vocational and tertiary education and the industry. Results demonstrate a lack of transport education for eco-friendly transport. Teachers, lecturers and the industry are highly interested in appropriate and high-quality offers in education and training. Moreover, results suggest that appropriate education concerning eco-friendly transport opportunities is able to support a shift towards eco-friendly logistics.

Joint flow control and link scheduling in hybrid terrestrial-satellite wireless backhauling network

Scipedia content — Tue, 02 Feb 2021 08:42:46 +0100

In this paper, the problem of cross-layer design of the link scheduling and flow control is studied in hybrid terrestrial-satellite wireless backhauling network. Considering network limitations and requirements, the target is to minimize the traffic delivery time by deciding the active backhauling links that can transmit simultaneously. Additionally, the proposed scheme provides a way to utilize the satellite links efficiently in order to provide the required link failure resiliency and traffic off-loading capability. Simulation results quantify the benefits of using the satellite links in cases of link failure and traffic congestion.

Peer Reviewed

Document type: Conference object

Evaluation of Transit Signal Priority Implementation for Bus Transit along a Major Arterial Using Microsimulation

Scipedia content — Tue, 02 Feb 2021 08:40:16 +0100

Transit Signal Priority (TSP) provides preferential treatment for public transit vehicles at signalized intersections when implemented. TSP is usually provided by interrupting the typical signal timings and extending the green or truncating the red for the signal phases that serve transits. This study investigates the impact of implementing a TSP treatment along a major arterial. A microsimulation approach was used to model, assess, and evaluate the potential benefits of implementing this treatment to bus transit vehicles. The network was built in a VISSIM multimodal microsimulation environment to test the traffic network performance with and without priority treatments. The study considered different peak hours for performance assessment. Three transit routes were considered in the microscopic modeling. The results showed a significant benefit of implementing TSP for the transit vehicles. The travel time was reduced by more than 40% in some cases, which can be translated into lower transit delay and more reliable transit service. The results also showed that TSP has a minimal negative effect on the general traffic. In fact, the general traffic along the studied transit routes benefited from the TSP implementation because of the better traffic progression and additional green times. 2018 The Authors. Published by Elsevier B.V. This report was made possible by UREP award (UREP18-054-2-020) from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopu

Air Traffic Flow Forecast in the Period of Major Events Based on Cost-Effectiveness Optimization

Scipedia content — Tue, 02 Feb 2021 08:38:28 +0100

Reliability of computing systems: From flip flops to variables

Scipedia content — Tue, 02 Feb 2021 08:37:57 +0100

International audience; Reliability evaluation is a critical task in computing systems. From one side, the results must be accurate enough not to under-or over-estimate the overall system reliability (thus either resulting in a non-reliable system, or a system for which too expensive solutions have been adopted). On the other side, the time required for the analysis should be kept at the minimum. This paper presents some new advances in the reliability assessment of computing systems, by showing techniques targeting both hardware and software levels, and the combination of both.

Socio-technical factors influencing current trends in material throughput in the UK automotive industry

Scipedia content — Tue, 02 Feb 2021 08:37:07 +0100

This paper investigates why material throughput remains high in the UK automotive industry when there are opportunities for material efficiency improvements. Informed by socio-technical studies of automobility, the paper emphasises the importance of recognising how decisions regarding material use are always shaped by more than simply cost considerations. Drawing on industry interviews, six interconnected socio-technical factors are identified that guide the vehicle design and manufacturing process. These are: (1) customer preferences; (2) market positioning; (3) techno-economic feasibility; (4) supply chain feasibility; (5) regulation and (6) organisational attributes. These factors can provide insights into the current operating context of the UK automotive industry and help explain why the average material intensity of vehicles and vehicle throughput are increasing. Overall, the paper shows that the efficiency of material use in the UK automotive industry is the outcome of complex and advanced design and manufacturing processes. Understanding these processes and the factors that guide them can potentially increase the likelihood of the automotive industry adopting material efficiency initiatives. S. Cooper is supported by a UK Engineering and Physical Sciences Research Council (EPSRC) PhD studentship (reference EP/L504920/1). Professor J.M. Allwood and Dr B.J. Doody by grant number EP/N02351X/1. None of the funding sources were involved with conducting the research.

Live Blackboxes: Requirements for Tracking and Verifying Aircraft in Motion

Scipedia content — Tue, 02 Feb 2021 08:36:27 +0100

The Malaysian Airlines (MH370) aircraft went missing somewhere over the Indian Ocean two years ago. After intensive search since then, international team still has not been able to locate any first-hand evidence from the missing plane's flight data recorders (also known as 'blackboxes'). To mitigate similar problems, a proposal has been made to analyse live streamed flight data using cloud computing; however, satellite communication is constrained by bandwidth and scalability challenges. In this paper, we propose five requirements for addressing these challenges. These requirements frame a class of monitoring problems that share some similar accuracy concerns around safety and security. We evaluate these requirements to assess the readiness of the proposed technology - which we call "live blackboxes'' -- by using actual global scale data and performing an analysis of different live streaming intervals. Preprocessing with a locality-sensitive hashing function, it results in reduction of the required bandwidth by 4.75 times. Therefore, to track and verify all civilian aircraft in motion, the scalability requirement could be satisfied by satellite communications. While the paper focuses on a particular problem in air traffic management, we speculate similar requirements for the continuous monitoring of critical systems.

Optimization of Airport Surface Traffic: A Case-study of Incheon International Airport

Scipedia content — Tue, 02 Feb 2021 08:32:42 +0100

V2G enabled EVs providing frequency containment reserves: field results

Scipedia content — Tue, 02 Feb 2021 08:30:54 +0100

Frequency regulation is procured by transmission system operators (TSOs) to ensure stable and reliable operation of power systems. In the Nordic energy region, frequency-controlled normal operation reserve (FNR) is one of the services that require fast-response. Electric vehicles (EVs) with vehicle to grid (V2G) capability may be considered an FNR provider in a future renewable-based power system. This paper presents results from the first commercial V2G hub in the Nordic area using the EV fleet of Frederiksberg Forsyning. The results are achieved by participating in the Danish frequency regulation market, and provide an analysis of the EV fleet operational data. Additionally, an analysis on practical issues that may result from realistic implementation of frequency regulation, such as delays, measurement errors and physical equipment constraints is given. These issues must be taken into account when developing new strategies for providing frequency services with EVs in a future scenario. Results show that a set of EVs operating in aggregated mode is able to support the grid while satisfying the primary goal of the EV fleet, i.e. transportation of fleet customers.

PROBABILISTIC ASSESSMENT OF PIPELINE - FAULT CROSSING

Scipedia content — Tue, 02 Feb 2021 08:26:54 +0100

Buried steel pipelines transporting oil and oil products play a vital role in the en- ergy supply chain. Pipelines extend to long distances and thus intercepting tectonic faults, when a seismic area is crossed, is often inevitable and may heavily threat the pipeline integri- ty. Earthquakes and the associated fault displacements are naturally random events and therefore the imposed large ground displacements on the pipeline have to be considered through a probabilistic perspective. In the present study, a comprehensive seismic risk analy- sis of buried pipeline - fault crossing is presented, consisting of two steps. The first step is the probabilistic assessment of the fault displacement accounting also for the pertinent uncertain- ties. The second step is the pipeline structural analysis. The transition from the seismological data to the structural analysis is realized through the fault displacement components as the selected vector intensity measure. The outcome of the proposed methodology is the strain hazard curves for both tensile and compressive longitudinal strains. The resulting strain ca- pacities are compared to strain demands from structural codes in order to assess the potential of pipeline failure due to local buckling or tensile fracture. Furthermore, uncertainty and dis- aggregation results from the fault displacement hazard analysis are presented for the selec- tion of the appropriate deterministic design scenario and the evaluation of the fault displacement hazard parameters. Lastly, the proposed process is a reliable estimation tool for seismic risk assessment of pipeline - fault crossing and a decision making tool for route se- lection and application of preventive measures against the consequences of faulting on pipe- lines.

On the Support of Air Traffic Control in Anti - terrorism Operation in the Northwest

Scipedia content — Tue, 02 Feb 2021 08:07:21 +0100

Adaptive Robust Traffic Engineering in Software Defined Networks

Scipedia content — Tue, 02 Feb 2021 08:00:42 +0100

One of the key advantages of Software-Defined Networks (SDN) is the opportunity to integrate traffic engineering modules able to optimize network configuration according to traffic. Ideally, network should be dynamically reconfigured as traffic evolves, so as to achieve remarkable gains in the efficient use of resources with respect to traditional static approaches. Unfortunately, reconfigurations cannot be too frequent due to a number of reasons related to route stability, forwarding rules instantiation, individual flows dynamics, traffic monitoring overhead, etc. In this paper, we focus on the fundamental problem of deciding whether, when and how to reconfigure the network during traffic evolution. We propose a new approach to cluster relevant points in the multi-dimensional traffic space taking into account similarities in optimal routing and not only in traffic values. Moreover, to provide more flexibility to the online decisions on when applying a reconfiguration, we allow some overlap between clusters that can guarantee a good-quality routing regardless of the transition instant. We compare our algorithm with state-of-the-art approaches in realistic network scenarios. Results show that our method significantly reduces the number of reconfigurations with a negligible deviation of the network performance with respect to the continuous update of the network configuration.

Comment: 10 pages, 8 figures, submitted to IFIP Networking 2018

Influence of Classroom Learning Modus, Locus of Control Type, Learning Ethos, Characteristic of Profession Practice Place, Capability And Mindset Entrepreneurship Graduate of Polytechnic of Road Transport Safety

Scipedia content — Tue, 02 Feb 2021 07:59:09 +0100

Are People the Key to Enabling Collaborative Smart Logistics?

Scipedia content — Tue, 02 Feb 2021 07:49:44 +0100

The number of parcels delivered is growing annually, with a 15.7% increase to 1 billion parcel deliveries in the UK in 2015. We introduce Freight Traffic Control 2050 which is exploring how to transform last-mile urban freight through ``collaborative logistics'. Based on our ethnographic fieldwork, we introduce the context and challenges in this domain. We highlight the value of experience and tacit knowledge, and the importance of approaching this domain from a socio-technical perspective. We offer a selection of early challenges identified as a starting point for discussion within the HCI community.

Effect of high pressure water jet cleaning device on the motion stability of an in-pipe cleaning robot

Scipedia content — Tue, 02 Feb 2021 07:49:17 +0100

The in-pipe cleaning robot (IPCR) is a new equipment for pipelines cleaning. However, most existing in-pipe robots are used to inspection and simple maintenance, etc. They cannot effectively complete the pipelines cleaning works, especially large diameter pipelines. This paper proposes a novel wheeled and wall-pressing type IPCR equipped with new high pressure water jet cleaning device. The whole mechanisms of the proposed IPCR are designed and a novel preload mechanism is applied to guarantee the IPCR reach to the target operation distance. Based on the multi-body theory, the contact mechanisms model is built. The motion equation and differential-algebraic equations of the IPCR system are obtained respectively. To verify the effect of the high pressure water jet cleaning jet on the motion stability of the IPCR, the virtual simulation platform is established in software RecurDyn and some simulation experiments are carried out. The results show that under the condition of sufficient preload force, the high pressure water jet cleaning device starts after the main body runs stable, which can guarantee the global motion stability.

Exploring the Business Case of a Risk-Averse Electric Vehicle Aggregator in the Nordic Market

Scipedia content — Tue, 02 Feb 2021 07:41:45 +0100

The Nordic power system is facing the challenge of the ongoing decrease of synchronous generation along with increased penetration of inverter based renewable generation leading to reduced system inertia. Meanwhile, the electrification of the transport sector will result in a significant amount of additional electrical loads. However, the electrification of private transport is a technology of growing interest that can provide flexibility to the power system if adequately utilized. Electric vehicles (EV) can be considered as temporary energy storage with availability, energy and capacity constraints. In this paper, we use first hand data of a real EV fleet of Tesla vehicles and their historical driving patterns to develop a two-stage stochastic optimization problem. This model maximizes the profit of a risk-averse EV aggregator that aims to place optimal bids on the day ahead in both energy and Frequency Containment Reserve (FCR) markets. Only uni-directional charging is examined, while we take into account uncertainty from prices and vehicle utilization. Case studies are carried out modelling individual vehicle driving behavior in different Nordic price areas in both winter and summer. We identify a strong alignment of EV availability and periods of high FCR prices. Results show that consumption is shifted largely towards early hours of the morning. When compared to a reference ”cost of charging case”, up to 50% of the cost of charging can be covered in Norway, while the entire cost is met in Sweden. "p"QC 20181017

Dynamic management of a partial reconfigurable hardware architecture for pedestrian detection in regions of interest

Scipedia content — Tue, 02 Feb 2021 07:35:09 +0100

International audience; In this paper, we propose a video streaming architecture implementing an IP core design based on Histograms of Oriented Gradients (HOG) algorithm, by using a high-level synthesis workflow. Also, we present a decision algorithm for a dynamically reconfigurable architecture, applied to people detection in video over a Region Of Interest (ROI). Our method dynamically manages the resource consumption in our hardware accelerator. In the test performed with only one reconfigurable module, our method achieves a power reduction up to 7% and a speed of 51 fps, but these results could be improved according to the number of reconfigurable modules. For implementation, we used a Xilinx Zynq 7000 series platform and our experimental results are compared with other software and hardware implementations. Our hardware architecture can be used in a vast number of vision systems, including advanced driver assistance systems (ADAS).

Classification non supervisée de courbes basée sur l'information au second ordre : détection de la dégradation de l'état de pistes d'atterrissage

Scipedia content — Tue, 02 Feb 2021 07:33:41 +0100

International audience; In air transportation, especially in airport safety, radar tracks are continuously recorded and may be used for detecting incidents on airport surface. However, all known statistical algorithms, even those based on functional data, are unable to distinguish between a safety critical flight and another one departing from standard behavior, but otherwise safe. In this work, we propose a change of paradigm by representing curves as points in a shape manifold. In this framework, it is possible to use Finsler distances between shapes that explicitly take into account the second derivative and can be able to 1 correctly detect skid situations from deviant trajectories that cannot be considered as a slipped trajectory. This metric is next used in curve clustering for detecting bad runway conditions. Some results on datasets of synthetic and real trajectories are presented, as well as a comparison of existing metrics.; Sur la plupart des plateformes aéroportuaires, les déplacements des aéronefs sont enregistrés en continu par des radars de surveillance et les trajectoires ainsi obtenues peuvent être utilisées pour détecter ou prévenir des incidents lors du roulage, en particu-lier des dérapages. Cependant, l'exploitation de ces données est rendue difficile par le fait que les algorithmes statistiques connus, même ceux basés sur des données fonctionnelles, ne sont pas capables de distinguer les situations réellement dangereuses des déviations au comportement standard qui sont sans gravité. Dans cette étude, nous proposons un chan-gement de paradigme en représentant les trajectoires comme des points dans un espace de formes. Dans ce nouveau cadre, il est possible de construire des distances de type Fins-ler, prenant explicitement en compte les dérivées secondes des trajectoires, et qui sont en mesure de bien séparer les trajectoires présentant un dérapage de celles dont la déviation par rapport au comportement nominal n'est pas due à un manque d'adhérence. Cette métrique est ensuite utilisée dans des méthodes de clustering pour détecter un mauvais état de la piste d'atterrissage. Des résultats sur des jeux de données de trajectoires syn-thétiques et réelles sont présentés ainsi qu'une comparaison avec des métriques existantes. Mots-clés. Similarité entre courbes, espace de formes, données fonctionnelles, classification non supervisée de courbes, sécurité aéroportuaire.

Abnormal behavior detection in LWIR surveillance of railway platforms

Scipedia content — Tue, 02 Feb 2021 07:28:21 +0100

In this paper we present a framework that is able to reliably and completely autonomously detect abnormal behavior in surveillance images. As input, we rely solely on a long-wave infrared (LWIR) image sensor. Our abnormal behavior detection pipeline consists of two consecutive stages. In a first stage, we perform efficient and fast pedestrian detection and tracking. In a second step, the detected paths are fed into a semi-supervised classifier that detects abnormal behavior. As test-case we recorded a unique real-life LWIR train station dataset -- which will be made publicly available -- containing natural occurrences of both normal and abnormal behavior. Our experiments indicate that our proposed framework achieves excellent accuracy results at real-time processing speeds. ispartof: Proceedings of the 14th IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS) ispartof: The IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS) location:Lecce, Italy date:29 Aug - 1 Sep 2017 status: published

Integrated urban freight logistics combining passenger and freight flows – mathematical model proposal

Scipedia content — Tue, 02 Feb 2021 07:24:20 +0100

The aim of this research is to propose an urban logistics distribution service which benefits from the already installed passenger transport network. This service is based upon the concept of integration of the existing passenger transport network with the urban freight process. The aim is to reduce the number of fossil combustion powered commercial vehicles traveling within city boundaries, solely for goods transportation, thus contributing to reduce negative effects of urban logistics activities, namely pollution, noise, traffic congestion and accidents. Also, integrating goods and passenger flows will promote higher efficiency rates for the passenger transport network and enhance living conditions within major urban centers. A mathematical model for the operational planning of the proposed urban logistics distribution service is proposed. This model consists of assigning origins loads (or requests) to inbound hubs (bus operator centers), transferring the inbound hubs loads to a bus service, and transferring the bus loads to bus stops, to be collected by micro-logistics operators operating environmentally friendly vehicle fleets. The objective is to minimize the total service time while assuring services synchronization along the network and balancing the loads with the system capacities. (undefined)

Exploration of a method to validate surrogate safety measures with a focus on vulnerable road users

Scipedia content — Tue, 02 Feb 2021 07:10:46 +0100

Background. Traditional crash-based analysis of road safety at individual sites has its shortcomings due to low numbers and the random nature of crashes at individual sites and the related statistical issues, as well as the under-reporting of crashes and lack of information on contributing factors and the process preceding crashes. To get around the problem, road safety analysis based on surrogate measures of safety, i.e. not based on crashes, can be used. However, the question whether surrogate measures are valid indicators for safety remains unanswered and only a few attempts have actually been made to carry out proper large-scale validation studies. Aim. This work presents a methodological approach for a large-scale validation study of surrogate safety indicators focusing on vulnerable road users. With only one site analyzed so far, it presents the exploration of the data and of the performance of the technical tools used in the study. Method. Video-filming and consequent video analysis are used to measure the surrogate safety indicators. In the first step, the video is “condensed” using a watchdog software RUBA that selects situations with an encounter of a cyclist or pedestrian and a motor vehicle. At a later stage, the trajectories of the individual road users are produced using a semi-automated tool T-Analyst and several surrogate safety indicators are tested to set a severity score for an encounter. The performance of the surrogate indicators will be compared to the expected number of accidents at each site and availability of the data for developing a safety performance function (SPF) that is country-, manoeuvreand type of VRU-specific are explored. Results & Conclusion. From methodological perspective, limited accident data available seriously complicates building a reliable SPF (“ground truth”) against which the surrogate safety measures could be validated; some other, “indirect” methods of validation might be required. We present also the performance of the software tools and applicability of the various surrogate safety indicators that were tested.

Using Segmented Standard Taxi Routes to Integrate Unmanned Aircraft Systems at Civil Airports

Scipedia content — Tue, 02 Feb 2021 07:10:02 +0100

Cargo airlines and other aircraft operating agencies are interested in commercially exploiting and benefiting from the technical possibilities provided by unmanned aircraft systems. Use cases could be long-range unmanned air transport, flight calibration, or surveillance missions. It is natural that, depending on weight and size, unmanned aircraft are going to use the existing ground infrastructure together with manned aircraft. But it is also a well-known fact that remotely piloted or automatic / autonomous unmanned aircraft do not have the same abilities and behavior than manned aircraft. A way has to be elaborated to achieve a safe, orderly and expeditious flow of a mixed traffic constellation even when more than one unmanned aircraft are involved in aerodrome operations at the same time. Unfortunately, due to a lack of international standardization and regulation, it is still unknown which abilities a commercial unmanned aircraft will have. This makes it very difficult to define operational procedures already. In the frame of the SESAR 2020 project ‘Surface Management Operations’ (SuMO), a procedural concept for ground movements of unmanned aircraft together with manned aircraft was elaborated. This concept uses so called segmented standard taxi routes and aims at realizing mixed traffic with an equal level of safety compared to pure manned traffic as well as very low system requirements for unmanned aircraft systems. In November 2017 this concept was validated together with Tower Controllers, Conventional Pilots, Remotely Piloted Aircraft Operators and an air traffic management expert from the German Air Navigation Service Provider DFS in a gaming workshop over several days; covering departures, arrivals and non-nominal situations like C2 link loss or lost communication. Results showed that this concept likely allows a first and easy integration of unmanned aircraft systems and it was rated as very practical and realistic. This paper gives basic information about the procedure of segmented standard taxi routes, briefly describes the used validation methodology and illustrates first results, closing with a short discussion and an outlook.

The role of societal resistance in transportation innovation

Scipedia content — Tue, 02 Feb 2021 07:06:17 +0100

8th International Congress on Transportation Research: Transportation by 2030: Trends and perspectives, THESSALONIKI, GRECE, 27-/09/2017 - 29/09/2017; This paper focuses on the description of societal trends related to mobility and on the way that these trends can be perceived from the society, when implemented. This action represents the starting point of the European project Mobility4EU that focuses on creating an action plan for the coherent implementation of innovative transport and mobility solutions in Europe. In Mobility4EU we have defined a set of possible societal aspects that might lead to societal resistance to the implementation of the future transport megatrends that have been defined. This paper aims to highlight the possibility of societal resistance to a wider implementation of innovative transport solutions, related to foreseen megatrends for the 2030. In consequence the list has not the ambition to be comprehensive, but rather provide a first overview of the societal reaction to widespread diffusion of foreseen solutions.

Document type: Conference object

Cooperative Longitudinal Positioning at Intersections Using DSRC

Scipedia content — Tue, 02 Feb 2021 07:05:42 +0100

Cooperative driver assistance systems (CoDAS) allow automated vehicles to perform cooperative driving maneuvers using vehicle to vehicle communication (V2V). For planning, negotiation and execution, these functions require precise localization of the vehicle itself and of other vehicles in the surroundings. Most vehicles today are equipped with Global Navigation Satellite System receivers (GNSS). However GNSS are prone to errors up to several meters, far exceeding CoDAS requirements. Yet, most of these errors are similar for vehicles in close proximity as they are caused by the satellite clock or atmospheric effects. In this paper we show how these characteristics can be used to improve absolute position of connected cars fusing GNSS and map data. Map matching is used to determine the GNSS offset of vehicles that share their position through V2V. The lateral error correction of a map matched vehicle that drives in perpendicular direction to the ego vehicle at an intersection is converted to a longitudinal error correction for the ego vehicle. We present an evaluation of this approach in simulation environment and real-world test drives using a LiDAR-based ground truth. We show that the cooperative positioning can reduce the mean GPS error below one meter.

Towards welfare optimal operation of innovative mobility concepts: External cost pricing in a world of shared autonomous vehicles

Scipedia content — Tue, 02 Feb 2021 07:04:23 +0100

Autonomous vehicles (AV) create new opportunities to traffic planners and policy-makers. In the case of shared autonomous vehicles (SAVs), dynamic pricing, vehicle routing and dispatch strategies may aim for the maximization of the overall system welfare instead of the operator’s profit. In this study, an existing congestion pricing methodology is applied to the SAV transport mode. On the SAV operator’s side, the routing- and dispatch-relevant cost are extended by the time and link-specific congestion charge. On the users’ side, the congestion costs are added to the fare. Simulation experiments are carried out for Berlin, Germany in order to investigate the impact of SAVs and different pricing setups on the transport system. For the pricing setup, where SAV users only pay the base fare and there is no congestion charge added to the user costs, the model predicts an SAV share of 17.7% within the inner-city Berlin service area. The level of traffic congestion increases, air pollution levels decrease and noise levels slightly increase in the inner-city area. The SAV congestion charge pushes users from SAVs to the walk, bicycle and conventional (driver-controlled) private car (CC) mode. The latter effect is avoided by applying the same congestion charge also to CC users. Overall, this study highlights the importance to control both, the SAV and CC mode in order to improve a city’s transport system.

Owning or sharing autonomous vehicles: comparing different ownership and usage scenarios

Scipedia content — Tue, 02 Feb 2021 07:04:00 +0100

EURO Working Group on Vehicle Routing and Logistics Optimization (https://verolog2017.sciencesconf.org/); International audience; Emerging challenges, such as finite oil supplies, rising gas prices and traffic congestion, going in hand with environmental concerns are the reason for new transport innovations, like autonomous vehicles, which will play a major role in future mobility systems. Regarding autonomous vehicles (AVs), two ownership models are being considered for future transportation systems. These are: autonomous vehicles as a public service or privately owning them. Furthermore, they can be used in a private or shared mode. As such, we study the different cases of using autonomous vehicles and the potential use of such vehicles in a ride-sharing application. In the first case, AVs can be used as a public service. In such case, we consider that there is a fleet of such vehicles located on specific locations (depots). AVs are invoked from their stations to satisfy mobility demands appearing in an urban area such that one single AV can serve multiple demands before getting back to a depot. On the other hand, privately owned AVs cannot just bring their owners from their homes to their work locations in the morning and bring them back in the evening while providing ride-sharing opportunities to other users, but they can also serve other users when their owners do not need them (e.g. while they are at work). Extending work on vehicle sharing by [Stiglic et al., 2015], we propose different approaches for planning AV trips aiming at studying and comparing the different ownership and usage scenarios for autonomous vehicles in an urban context.

Document type: Article

On demand QoS with a SDN traffic engineering management (STEM) module

Scipedia content — Tue, 02 Feb 2021 06:54:15 +0100

Software Defined Networking (SDN) allows new approaches to provide Quality of Service (QoS). In legacy networks, strict QoS guarantees often result in bandwidth over-provisioning. Then, QoS enforcement either consumes too many resources, or is not flexible enough. We present a solution to provide QoS based on the creation of on-demand MPLS tunnels with guaranteed bandwidths across an SDN network. We introduce an SDN Traffic Engineering Management (STEM) module that interacts with the northbound applications to satisfy their requests to forward QoS-guaranteed traffic flows. STEM delegates the path selection to a Path Computation Element (PCE), and the path enforcement to an SDN controller. We rely on a stateful PCE to record the attributed resources and estimate the remaining network capacity, avoiding overloading the network with monitoring traffic. Upon STEM requests, the SDN controller enforces the QoS policy in the data plane. User flows are aggregated into MPLS tunnels and packets are labeled with a priority depending on the flow effective bandwidth. We highlight the shortfalls of several material and software OpenFlow compatible switches and detail an implementation based on a pica8 switch to overcome them. The experimental results demonstrate that this solution efficiently enforces bandwidth sharing in SDN networks.

Using Dynamic Neural Networks for Battery State of Charge Estimation in Electric Vehicles

Scipedia content — Tue, 02 Feb 2021 06:49:13 +0100

Due to urban pollution, transport electrification is being currently promoted in different countries. Electric Vehicles (EVs) sales are growing all over the world, but there are still some challenges to be solved before a mass adoption of this type of vehicles occurs. One of the main drawbacks of EVs are their limited range, for that reason an accurate estimation of the state-of-charge (SOC) is required. The main contribution of this work is the design of a Nonlinear Autoregressive with External Input (NARX) artificial neural network to estimate the SOC of an EV using real data extracted from the car during its daily trips. The network is trained using voltage, current and four different battery pack temperatures as input and SOC as output. This network has been tested using 54 different real driving cycles, obtaining highly accurate results, with a mean squared error lower than 1e-6 in all situations This work has been partially financed by the Spanish Ministry of Economy and Competitiveness within the framework of the project DEMS: “Sistema distribuido de gestión de energía en redes eléctricas inteligentes (TEC2015-66126-R)".

Effects of Linear Filter on Stability and Performance of Human-in-the-Loop Model Reference Adaptive Control Architectures

Scipedia content — Tue, 02 Feb 2021 06:42:34 +0100

Date of Conference: 11–13 October 2017 Conference Name: ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 Model reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop settings, MRAC may cause unstable system trajectories. Basing on our recent work on the stability of MRAC-human dynamics, here we follow an optimization based computations to design a linear filter and study whether or not this filter inserted between the human model and MRAC could help remove such instabilities, and potentially improve performance. To this end, we present a mathematical approach to study how the error dynamics of MRAC could favorably or detrimentally influence human operator's error dynamics in performing a certain task. An illustrative numerical example concludes the study.

Exploring Genomic Datasets

Scipedia content — Tue, 02 Feb 2021 06:31:09 +0100

Genomic data management is focused on achieving high performance over big datasets using batch, cloud-based architectures; this enables the execution of massive pipelines, but hampers the capability of exploring the solution space when it is not well-defined, by choosing different experimental samples or query extraction parameters. We present PyGMQL, a Python-based interoperability software layer that enables testing of experimental pipelines; PyGMQL solves the impedance mismatch between a batch execution environment and the agile programming style of Python, and provides transparency of access when exploration requires integrating local and remote resources. Wrapping PyGMQL and Python primitives within Jupyter notebooks guarantees reproducibility of the pipeline when used in different contexts or by different scientists. The software is freely available at https://github.com/DEIB-GECO/PyGMQL.

EAST: An Efficient and Accurate Scene Text Detector

Scipedia content — Tue, 02 Feb 2021 06:30:19 +0100

Previous approaches for scene text detection have already achieved promising performances across various benchmarks. However, they usually fall short when dealing with challenging scenarios, even when equipped with deep neural network models, because the overall performance is determined by the interplay of multiple stages and components in the pipelines. In this work, we propose a simple yet powerful pipeline that yields fast and accurate text detection in natural scenes. The pipeline directly predicts words or text lines of arbitrary orientations and quadrilateral shapes in full images, eliminating unnecessary intermediate steps (e.g., candidate aggregation and word partitioning), with a single neural network. The simplicity of our pipeline allows concentrating efforts on designing loss functions and neural network architecture. Experiments on standard datasets including ICDAR 2015, COCO-Text and MSRA-TD500 demonstrate that the proposed algorithm significantly outperforms state-of-the-art methods in terms of both accuracy and efficiency. On the ICDAR 2015 dataset, the proposed algorithm achieves an F-score of 0.7820 at 13.2fps at 720p resolution.

Comment: Accepted to CVPR 2017, fix equation (3)

Research on Air Traffic Center Control Effectiveness Evaluation Based on Cloud Model

Scipedia content — Tue, 02 Feb 2021 06:25:08 +0100

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

Scipedia content — Tue, 02 Feb 2021 06:14:02 +0100

Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic

Scipedia content — Tue, 02 Feb 2021 05:58:42 +0100

Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was...

ROLE AND EFFECTIVENESS OF STATE TRANSPORT: AN ANALYSIS OF PEPSU ROAD TRANSPORT CORPORATION (P.R.T.C) PUNJAB. (INDIA).

Scipedia content — Tue, 02 Feb 2021 05:58:07 +0100

Road transport plays a key role in socio- economic development. Most suitable for short and medium distances, it offers a number of advantages such as flexibility, reliability, speed and door to door service. Over the years, share of transport in overall traffic handling has been continuously increasing on the one hand and on the other especially public passenger transport is bearing losses year after year. The present paper is an attempt to find out the reasons of loss making of Pepsu road transport corporation (P.R.T.C) in Punjab. And it has been observed that due to government policies and lethargic attitude of some staff members this is corporation is bearing loss year after year and becoming liability on the government.

Why Reinvent the Wheel

Scipedia content — Tue, 02 Feb 2021 05:52:22 +0100

Modern question answering (QA) systems need to flexibly integrate a number of components specialised to fulfil specific tasks in a QA pipeline. Key QA tasks include Named Entity Recognition and Disambiguation, Relation Extraction, and Query Building. Since a number of different software components exist that implement different strategies for each of these tasks, it is a major challenge to select and combine the most suitable components into a QA system, given the characteristics of a question. We study this optimisation problem and train classifiers, which take features of a question as input and have the goal of optimising the selection of QA components based on those features. We then devise a greedy algorithm to identify the pipelines that include the suitable components and can effectively answer the given question. We implement this model within Frankenstein, a QA framework able to select QA components and compose QA pipelines. We evaluate the effectiveness of the pipelines generated by Frankenstein using the QALD and LC-QuAD benchmarks. These results not only suggest that Frankenstein precisely solves the QA optimisation problem but also enables the automatic composition of optimised QA pipelines, which outperform the static Baseline QA pipeline. Thanks to this flexible and fully automated pipeline generation process, new QA components can be easily included in Frankenstein, thus improving the performance of the generated pipelines.

DCCast: Efficient Point to Multipoint Transfers Across Datacenters

Scipedia content — Tue, 02 Feb 2021 05:44:33 +0100

Using multiple datacenters allows for higher availability, load balancing and reduced latency to customers of cloud services. To distribute multiple copies of data, cloud providers depend on inter-datacenter WANs that ought to be used efficiently considering their limited capacity and the ever-increasing data demands. In this paper, we focus on applications that transfer objects from one datacenter to several datacenters over dedicated inter-datacenter networks. We present DCCast, a centralized Point to Multi-Point (P2MP) algorithm that uses forwarding trees to efficiently deliver an object from a source datacenter to required destination datacenters. With low computational overhead, DCCast selects forwarding trees that minimize bandwidth usage and balance load across all links. With simulation experiments on Google's GScale network, we show that DCCast can reduce total bandwidth usage and tail Transfer Completion Times (TCT) by up to $50\\%$ compared to delivering the same objects via independent point-to-point (P2P) transfers.

Comment: 9th USENIX Workshop on Hot Topics in Cloud Computing, https://www.usenix.org/conference/hotcloud17/program/presentation/noormohammadpour

Document type: Conference object

SDN-enabled traffic engineering and advanced blackholing at IXPs

Scipedia content — Tue, 02 Feb 2021 05:41:39 +0100

While the clean slate approach proposed by Software Defined Networking (SDN) promises radical changes in the stagnant state of network management, SDN innovation has not gone beyond the intra-domain level. For the inter-domain ecosystem to benefit from the advantages of SDN, Internet Exchange Points (IXPs) are the ideal place: a central interconnection hub through which a large share of the Internet can be affected. In this demo, we showcase the ENDEAVOUR platform: a new software defined exchange approach readily deployable in commercial IXPs. We demonstrate here our implementations of traffic engineering and Distributed Denial of Service mitigation, as well as how member networks cash in on the advanced SDN-features of ENDEAVOUR, typically not available in legacy networks.

Exploring potential of crowdsourced geographic information in studies of active travel and health: Strava data and cycling behaviour

Scipedia content — Tue, 02 Feb 2021 05:21:24 +0100

In development of sustainable transportation and green city, policymakers encourage people to commute by cycling and walking instead of motor vehicles in cities. One the one hand, cycling and walking enables decrease in air pollution emissions. On the other hand, cycling and walking offer health benefits by increasing people’s physical activity. Earlier studies on investigating spatial patterns of active travel (cycling and walking) are limited by lacks of spatially fine-grained data. In recent years, with the development of information and communications technology, GPS-enabled devices are popular and portable. With smart phones or smart watches, people are able to record their cycling or walking GPS traces when they are moving. A large number of cyclists and pedestrians upload their GPS traces to sport social media to share their historical traces with other people. Those sport social media thus become a potential source for spatially fine-grained cycling and walking data. Very recently, Strava Metro offer aggregated cycling and walking data with high spatial granularity. Strava Metro aggregated a large amount of cycling and walking GPS traces of Strava users to streets or intersections across a city. Accordingly, as a kind of crowdsourced geographic information, the aggregated data is useful for investigating spatial patterns of cycling and walking activities, and thus is of high potential in understanding cycling or walking behavior at a large spatial scale. This study is a start of demonstrating usefulness of Strava Metro data for exploring cycling or walking patterns at a large scale.

Document type: Conference object

The design of traffic signal coordinated control

Scipedia content — Tue, 02 Feb 2021 05:14:31 +0100

Traffic as the tertiary industry is an important pillar industry to support the normal development of the economy. But now China’s road traffic development and economic development has shown a great imbalance and fault phenomenon, which greatly inhibited the normal development of China’s economy. Now in many large and medium-sized cities in China are implementing green belt construction. The so-called green band is when the road conditions to meet the conditions for the establishment of the green band, the sections of the intersection of several planning to a traffic coordination control system, so that when the driver at a specific speed can be achieved without stopping the continuous Through the intersection. Green belt can effectively reduce the delay and queuing length of vehicle driving, the normal function of urban roads and reduce the economic losses caused by traffic congestion is a great help. In this paper, the theoretical basis of the design of the coordinated control system is described. Secon...

Low cost rollback to improve fault-tolerance in VLSI circuits

Scipedia content — Tue, 02 Feb 2021 04:43:26 +0100

International audience; In nanometer technologies, circuits are more and more sensitive to various kinds of perturbations. Alpha particles and atmospheric neutrons are affecting storage elements as well as the combinational logic. In the past, the major efforts were related on memories. However, as the whole situation is getting worse, solutions that protect the entire design are mandatory. Solutions for detecting the error in logic functions already exist, but there are only few of them that allow the correction, leading to a lot of hardware overhead in non-processor design. In this paper, we present a novel hardware architecture that reduces the cost of rollback in any kinds of circui

Test of FBG sensors for monitoring high pressure pipes

Scipedia content — Tue, 02 Feb 2021 04:42:23 +0100

Fibre Bragg Grating (FBG) sensors are increasingly being used on a wide range of civil, industrial and aerospace structures. The sensors are created inside optical fibres (usually standard telecommunication fibres); the optical fibres technology allows to install the sensors on structures working in harsh environments, since the materials are almost insensitive to corrosion, the monitoring system can be positioned far away from the sensors without sensible signal losses, and there is no risk of electric discharge. FBG sensors can be used to create strain gages, thermometers or accelerometers, depending on the coating on the grating, on the way the grating is fixed to the structure, and on the presence of a specifically designed interface that can act as a transducer. This paper describes a test of several different FBG sensors to monitor an high pressure pipe that feeds the hydraulic actuators of a 6 degrees-of-freedom shaking table at the ENEA Casaccia research centre. A bare FBG sensor and a copper coated FBG sensor have been glued on the pipe. A third sensor has been mounted on a special interface to amplify the vibrations; this last sensor can be placed on the steel pipe by a magnetic mounting system, that also allows the its removal. All the sensor are placed parallel to the axis of the pipe. The analysis of the data recorded when the shaking table is operated will allow to determine which kind of sensor is best suited for structural monitoring of high pressure pipelines.

Integrating Kinematic- and Vision-Based Information to Better Understand Driving Behaviour

Scipedia content — Tue, 02 Feb 2021 04:38:21 +0100

This study explored the use of two types of advanced driver assistance systems (ADAS) as tools for observing driving behavior. The first was a kinematic-based ADAS that uses speed and acceleration data to detect driving events such as hard braking, speeding and sharp turning. The second was a vision-based ADAS that uses video data to provide lane departure warnings (LDW), headway warnings (HW) and forward collision warnings (FCW). Data was collected for more than 4,500 trips and 2,200 driving hours during a period of 70 days. The sample consisted of 10 drivers that used both types of ADAS simultaneously. The information collected also included more than 17,000 records of various types of driving events. First, the events rates were estimated by the Poisson and the Poisson-lognormal models. Then, Pearson correlation and factor analysis were implemented to study the relationships among the events and to evaluate whether different types of events converged to describe the same behaviors. Significant correlations were observed between the braking and turning kinematic-based events and the FCW vision-based event, which converged under the same factor. High rates of these events may indicate that the person is driving in an urban style. The LDW, HW and speeding events converged to the second factor, which is more relevant in inter-urban areas. These findings, although based on a small-scale study, point to a potential for the use of commercial ADAS for driving behavior analysis. The integration of kinematic-based and vision-based information can provide deeper understanding of the measured behavior.

An Intelligent Road Traffic Control System for Passenger Safety

Scipedia content — Tue, 02 Feb 2021 04:38:03 +0100

Evaluating the Presence of In-Vehicle Devices on Driver Performance: Methodological Issues

Scipedia content — Tue, 02 Feb 2021 04:35:54 +0100

central concern of Intelligent Transportation Systems (ITS) is the effect of in-vehicle devices (e.g., cell phones, navigation systems, radios) on driver performance and safety. As diverse and innovative technologies are designed and implemented for in-vehicle use, questions regarding the presence and use of these devices assume progressively greater importance. Concern for driver safety and advanced driver training require us to develop and validate reliable and effective procedures for assessing such effects. This work examines a number of candidate procedures, in particular the evaluation of cognitive workload as a strategy by which such goals might be achieved.

Multi-objective Particle Swarm Optimization to Solve Energy Scheduling with Vehicle-to-Grid in Office Buildings Considering Uncertainties

Scipedia content — Tue, 02 Feb 2021 04:29:16 +0100

This paper presents a Multi-Objective Particle Swarm Optimization (MOPSO) methodology to solve the problem of energy resource management in buildings with a penetration of Distributed Generation (DG) and Electric Vehicles (EVs). The proposed methodology consists in a multi-objective function, in which it is intended to maximize the profit and minimize CO2 emissions. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind energy sources. This uncertainty is modeled with the use of a robust optimization approach in the metaheuristic. A case study is presented using a real building facility from Portugal, in order to verify the feasibility of the implemented robust MOPSO. This work has received funding from the Project NetEffiCity (ANI|P2020 18015), and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.

Exploiting optical flow field properties for 3D structure identification

Scipedia content — Tue, 02 Feb 2021 04:20:52 +0100

International audience; This paper deals with a new method that exploits optical flow field properties to simplify and strengthen the original c-velocity approach (Bouchafa and Zavidovique, 2012). C-velocity is a cumulative method based on a Hough-like transform adapted to velocities that allows 3D structure identification. In case of moving cameras, the 3D scene is assumed to be composed by a set of 3D planes that could be categorized in 3 main models: horizontal, lateral and vertical planes. We prove in this paper that, by using directly pixel coordinates to create what we will call the uv-velocity space, it is possible to detect 3D planes efficiently. We conduct our experiments on the KITTI optical flow dataset (Menze and Geiger, 2015) to prove our new concept besides the effectiveness of uv-velocity in detecting planes. In addition, we show how our approach could be applied to detect free navigation area (road), urban structures like buildings and obstacles from a moving camera in the context of Advanced Driver Assistance Systems.

On the potential for interim storage in dense phase CO2 pipelines

Scipedia content — Tue, 02 Feb 2021 04:20:26 +0100

This paper investigates the flexibility that exists within a dense phase carbon dioxide (CO2) pipeline system to accommodate upset conditions in the Carbon Capture and Storage (CCS) network by utilising the pipeline as a storage vessel whilst still maintaining flow into the pipeline. This process is defined in the pipeline industry as “line-packing” and the time available to undertake line-packing is termed the line-packing time. The longer the line-packing time, the more resilient the pipeline system is to flow variations or short term operational issues at the capture or storage site. The aims of the study were; to investigate the impact of typical CO2 pipeline design parameters (diameter, wall thickness and length) as well as CO2 mass flow rate and pipeline inlet and outlet pressure on the available line-packing time and; to derive relationships between the key variables to allow designers to optimise the line-packing time for a pipeline system. The study was undertaken by developing a viable study set of dense phase CO2 pipelines using steady state hydraulic analysis and stress based design principles. The study set was designed to cover the range of design parameters, flow rates and pressures considered to be typical of dense phase pipelines in CCS systems. For each of the pipelines in the study set, the line-packing time was calculated using a transient hydraulic analysis approach. Although by interrogating the results, individual relationships could be identified between key input parameters and the line-packing time, the integration of all of the critical parameters could not be achieved through simple regression analysis techniques. Consequently, using the dataset of pipelines and line-packing times developed, an Artificial Neural Network (ANN) was designed to enable a comprehensive sensitivity analysis of the line-packing time to the input data to be conducted. It is also demonstrated how the ANN can be used as a design tool for the prediction of line-packing time. As would be expected, the line-packing capacity of the pipeline can be increased by increasing the available internal volume of the pipeline, reducing the mass flow rate into the pipeline, increasing the allowable operating stress and managing the inlet pressure and outlet pressures. However, one of the key findings of the work is that, in the dense phase, line-packing times of only up to 8 h can be achieved for pipeline dimensions typical of those considered for CCS schemes. Consequently it has been confirmed that the pipeline does not represent a long-term storage option for CCS systems. However, if line-packing capability is considered at the design stage then the level of flexibility for the pipeline to act as short-term storage in the network increases. In particular, it is recommended that the effect of increasing the wall thickness on the line-packing time is considered at the design stage to determine the benefits of this option in enabling the pipeline to be used as a short-term storage option in the CCS system and prevent venting of CO2 during short-term outage events at the capture or storage site.

Towards detection of pipeline integrity threats using a SmarT fiber-OPtic surveillance system: PIT-STOP project blind field test results

Scipedia content — Tue, 02 Feb 2021 04:19:34 +0100

4 pags., 1 fig., 1 tab.

This paper presents the first report on on-line and final blind field test results of a pipeline integrity threat surveillance system. The system integrates a machine+activity identification mode, and a threat detection mode. Two different pipeline sections were selected for the blind tests: One close to the sensor position, and the other 35 km away from it. Results of the machine+activity identification mode showed that about 46% of the times the machine, the activity or both were correctly identified. For the threat detection mode, 8 out of 10 threats were correctly detected, with 1 false alarm.

This work was mainly supported by three GERG partners (Fluxys, Statoil, and Gassco) under project PIT-STOP, and was also supported in part by: the European Research Council through project UFINE (Grant #307441); the EC Horizon 2020 program through the FINESSE project MSCA-ITN-ETN-722509; the DOMINO Water JPI project, under the WaterWorks2014 cofounded call by EC Horizon 2020 and Spanish MINECO; the Spanish MINECO through projects TEC2013-45265-R, TEC2015-71127-C2-2-R, and TIN2013-47630-C2-1-R; and the regional program SINFOTON-CM: S2013/MIT-2790. The work of HFM was supported by EU funding through the FP7 ITN ICONE program (Grant #608099). The work of JPG and SML was supported by the Spanish MINECO through FPI and \\Ramón y Cajal" contract, respectively.

Peer Reviewed

Shortening the turnaround times of aircraft by improving ground handling processes through a simulation study

Scipedia content — Tue, 02 Feb 2021 03:52:14 +0100

This paper focuses on the prioritization of certain ground vehicles and improving turnaround times of airplanes at the apron of the Riga International Airport. This leads to a hastening of ground operations at the viewed airport. Performance indicators to measure delay and delay improvement within the system are the non-operation period of an airplane, the distance and time by ground vehicles needed to get to their assigned task. Due to the rising number of passengers within the next years, the effectiveness of these indicators needs to rise. Based on the conceptual model, a rough calculation containing time for necessary tasks at an airport as well as data about airplanes, which departure and arrive at Riga International Airport. Based on the rough calculation and the conceptual model a simulation model will built, with which new insights and new ideas for future simulation studies might be gained.

OSLO 2019: A CAR-FREE CITY CENTRE

Scipedia content — Tue, 02 Feb 2021 03:51:58 +0100

In June 2016, a climate and energy strategy for Oslo was enacted by the city council. The overall climate targets adopted for Oslo 2030–2050 were to reduce greenhouse gas emissions by 50% (2030) and to zero in 2050. To achieve these goals, several measures for the various municipal sectors have to be implemented. For the transport sector, the most important measure is to ensure transition from individual car transport to public transport, cycling and walking, green goods transportation. Having a fossil free society in 2050, then it is crucial to reverse trends to changing people’s behaviour. If car traffic inside the city centre will be banned, then the consequences need to be evaluated. The concern for the disabled, goods transportation, public transit and residents must be safeguarded. Through comparison with other cities that are partially car-free, we have described some consequences that must be taken into account when implementing the green policy. Several methods are used, a literature review and face-to-face interviews. A study-tour to Germany and France included city-walks, and interviews with urban and transport planners and politicians from the cities of Nuremberg, Freiburg, and Strasbourg. These cities were chosen because of their log experience with implementation of pedestrianized city centres. The provision of pedestrianized city centre in Oslo may at first glance seem like a political stunt from an inexperienced visionary political party. Drastic measures must be implemented, that requires thoughtful planning and participation. A car-free city centre cannot be completed at the expense of the population, and to have a good planning phase will be more important than the goal of implementing the measures within a certain time limit. Achieving good accessibility for all affected may potentially lead to a vibrant cityscape, suitable for many. publishedVersion

Real World Driving: Emissions in Highly Congested Traffic

Scipedia content — Tue, 02 Feb 2021 03:49:24 +0100

The emissions from vehicles in real world driving are of current concern, as they are often higher than on legislated test cycles and this may explain why air quality in cities has not improved in proportion to the reduction in automotive emissions. This has led to the Real Driving Emissions (RDE) legislation in Europe. RDE involves journeys of about 90km with roughly equal proportion of urban, rural and motorway driving. However, air quality exceedances occur in cities with urban congested traffic driving as the main source of the emissions that deteriorate the air quality. Thus the emissions measured on RDE journeys may not be relevant to air quality in cities. A Temet FTIR and Horiba exhaust mass flow measurement system was used for the mass emissions measurements in a Euro 4 SI vehicle. A 5km urban journey on a very congested road was undertaken 29 times at various times so that different traffic congestion was encountered. Each journey was split into ten sections in order that the location and traffic conditions of the highest emissions could be determined. It was found that low speed stop-start traffic has much higher emissions than for freely moving traffic and most of the higher emissions on the longer 5km journeys occurred in relatively short sections of slow moving stop/start traffic. The journey used passed a roadside air quality monitor that exceeded the EU NO2 and PM standards on an annual basis and it was located by the most congested part of the route, where the traffic emissions are shown in this work to be at their highest.

PACAS: A gamified platform for participatory change management in ATM systems

Scipedia content — Tue, 02 Feb 2021 03:48:35 +0100

In this paper, we report on the development of a webbased platform for Participatory Architectural Change Management in Air Traffic Management Systems (ATM) as part of the SESAR H2020 project PACAS. The platform is the result of an iterative requirements engineering process that actively involves ATM domain experts, starting from stakeholder analysis, to requirements elicitation, scenario definition, and validation.

Japan’s transport planning at national level, natural disasters, and their interplays

Scipedia content — Tue, 02 Feb 2021 03:47:07 +0100

This research aims to give an overview of Japan’s national-level transport planning schemes, and to discuss interplays between them and recoveries from natural disasters. In the first part, Japan’s national spatial development plans and long-term planning schemes for railway, road, port and airport infrastructures are reviewed and compared. In the second part, imbalance embedded in the current planning scheme for different modes are demonstrated making use of recent post-disaster reconstruction processes. A literature-based desktop research is carried out focusing on Japanese literature. These include, but not limited to, official government reports and planning documents, statistical data, and handbooks for experts in the field. All of the long-distance modes have their planning schemes with different levels of comprehensiveness and robustness for each mode. Expressways and high-speed railways have the most comprehensive and robust network plans, while conventional railway, airports and seaports have ones with limited extent. Because of this, post-disaster reconstruction processes from damages to the infrastructure work differently in particular for conventional railways and for expressways in rural areas, which are competitors against each other. Strong framework for intermodal and multimodal transport is still in lack in Japan. Important structural imbalance between modes, in particular between conventional railway and expressway exist, and it becomes obvious in case of a natural disaster. Multimodal planning, frameworks for flexible adjustment of once-made long-term plans, and addressing imbalances regarding robustness between railways and expressways are identified as future challenges of the country’s planning schemes.

Document type: Article

Optimal Local Routing Strategies for Community Structured Time Varying Communication Networks

Scipedia content — Tue, 02 Feb 2021 03:46:50 +0100

International audience; In time varying data communication networks (TVCN), traffic congestion, system utility maximization and network performance enhancement are the prominent issues. All these issues can be resolved either by optimizing the network structure or by selecting efficient routing approaches. In this paper, we focus on the design of a time varying network model and propose an algorithm to find efficient user route in this network. Centrality plays a very important role in finding congestion free routes. Indeed, the more a node is central, the more it can be congested by the flow coming from or going to its neighborhood. For that reason, classically, routes are chosen such that the sum of centrality of the nodes coming in user’s route is minimum. In this paper, we show that closeness centrality outperforms betweenness centrality in the case of community structured time varying networks. Furthermore, Kelly’s optimization formulation for a rate allocation problem is used in order to compute optimal rates of distinct users at different time instants.

Fast sensitivity-based optimal trajectory updates for descent operations subject to time constraints

Scipedia content — Tue, 02 Feb 2021 03:43:47 +0100

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

37th DASC Best of session (ATM-L: TMA Operations) award, 2018; concedit per l'Institute of Electrical and Electronics Engineers.

The ability to meet a controlled time of arrival during a continuous descent operation will enable environmentally friendly and fuel efficient descent operations while simultaneously maintaining airport throughput. Previous work showed that guidance strategies based on a frequent recalculation of the optimal trajectory during the descent result in excellent environmental impact mitigation figures while meeting operational constraints in the presence of modelling errors. However, the time lag of recalculating the trajectory using traditional optimisation algorithms could lead to performance degradation and stability issues. This paper proposes an alternative strategy, which allows for fast updates of the optimal trajectory based on parametric sensitivities. Promising results show that the performance of this method is comparable to that of instantaneously recalculating the optimal descent trajectory at each time sample.

Peer Reviewed

Award-winning

Document type: Conference object

Toward a non-destructive diagnostic analysis tool of exercises pipelines: models and experiences

Scipedia content — Tue, 02 Feb 2021 03:43:31 +0100

Strategic networks of hydrocarbon pipelines, in long time service, are adversely affected by the action of aggressive chemicals transported with the fluids and dissolved in the environment. Material degradation phenomena are amplified in the presence of hydrogen and water, elements that increase the material brittleness and reduce the safety margins. The risk of failure during operation of these infrastructures can be reduced, if not prevented, by the continuous monitoring of the integrity of the pipe surfaces and by the tracking of the relevant bulk properties. A fast and potentially non-destructive diagnostic tool of material degradation, which may be exploited in this context, is based on the instrumented indentation tests that can be performed on metals at different scales. Preliminary validation studies of the significance of this methodology for the assessment of pipeline integrity have been carried out with the aid of interpretation models of the experiments. The main results of this ongoing activity are illustrated in this contribution.

Fast Stochastic Non-linear Model Predictive Control for Electric Vehicle Advanced Driver Assistance Systems

Scipedia content — Tue, 02 Feb 2021 03:41:55 +0100

International audience; Semi-autonomous driving assistance systems have a high potential to improve the safety and efficiency of the battery electric vehicles that are enduring limited cruising range. This paper presents an ecologically advanced driver assistance system to extend the functionality of the adaptive cruise control system. A real-time stochastic non-linear model predictive controller with probabilistic constraints is presented to compute on-line the safe and energy-efficient cruising velocity profile. The individual chance-constraint is reformulated into a convex second-order cone constraint which is robust for a general class of probability distributions. Finally, the performance of proposed approach in terms of states regulation, constraints fulfilment, and energy efficiency is evaluated on a battery electric vehicle.

A Market Framework for Enabling Electric Vehicles Flexibility Procurement at the Distribution Level Considering Grid Constraints

Scipedia content — Tue, 02 Feb 2021 03:37:56 +0100

In a context of extensive electrification of the transport sector, the use of flexibility services from electric vehicles (EVs) is becoming of paramount importance. This paper defines a market framework for enabling EVs flexibility at the distribution level, considering grid constraints. The main objective is to establish an adequate incentive system and proceed with an evaluation of EVs grid support for both users and DSOs, benchmarking it against the typical reinforcement solution. To exploit this framework, a billing process based on a two-price system is proposed for the controlled EV charging. The derived methodology is applied to a piece of semi-urban Danish distribution grid consisting of 42 customers. The service remuneration spans from 16 \\text{C}\\!\\!\\!\\!\\!\\!\\! {=}/year to 51 \\text{C}\\!\\!\\!\\!\\!\\!\\! {=} (year per customer, depending on the incentive scheme, and avoids a standard reinforcement of approximately 6200 \\text{C}\\!\\!\\!\\!\\!\\!\\! {=}/year. It is demonstrated the benefit for DSOs and society, proving a technical and economic feasible solution.

Improving Vision-based Self-positioning in Intelligent Transportation Systems via Integrated Lane and Vehicle Detection

Scipedia content — Tue, 02 Feb 2021 03:33:27 +0100

Traffic congestion is a widespread problem. Dynamic traffic routing systems and congestion pricing are getting importance in recent research. Lane prediction and vehicle density estimation is an important component of such systems. We introduce a novel problem of vehicle self-positioning which involves predicting the number of lanes on the road and vehicle's position in those lanes using videos captured by a dashboard camera. We propose an integrated closed-loop approach where we use the presence of vehicles to aid the task of self-positioning and vice-versa. To incorporate multiple factors and high-level semantic knowledge into the solution, we formulate this problem as a Bayesian framework. In the framework, the number of lanes, the vehicle's position in those lanes and the presence of other vehicles are considered as parameters. We also propose a bounding box selection scheme to reduce the number of false detections and increase the computational efficiency. We show that the number of box proposals decreases by a factor of 6 using the selection approach. It also results in large reduction in the number of false detections. The entire approach is tested on real-world videos and is found to give acceptable results.

Comment: WACV 2015

Low Cycle Fatigue of Subsea Mechanically Lined Pipeline With Liner Imperfections

Scipedia content — Tue, 02 Feb 2021 03:30:00 +0100

There is an ever-increasing demand for subsea transport of corrosive constituents which requires the use of corrosion resistant pipelines. This has generated interest in mechanically lined pipe (MLP) which consists of carbon steel pipe lined with a thin layer of corrosion resistant alloy (CRA), typically stainless steel. The CRA liner is adhered to the backing pipe by means of an interference fit."/jats:p" "jats:p"MLPs have been traditionally installed subsea using low strain methods such as towing, S-lay or J-lay. More recently, the efficient reel-lay method, typically used for pipelines up to 18” (457.2 mm) in diameter, has also been considered. To prevent damage to the MLP during high strain bending (i.e. wrinkling of CRA the liner) and thus allow reel-lay installation, TechnipFMC has qualified reeling of MLPs at ambient and elevated pressures. The ambient reeling approach, where the liner thickness is increased to prevent wrinkling during reeling, is appropriate for smaller diameter MLPs. For larger pipelines, it is generally more cost-effective to pressurise the MLP during reeling."/jats:p" "jats:p"Concerns have been expressed that liner imperfections such as small dents or wrinkles, introduced during manufacturing, installation or service, may compromise the integrity of the MLP subjected to high in-service cyclic loading. Therefore, this study was undertaken to examine the criticality of such flaws and determine the low cycle fatigue endurance of reeled MLPs with imperfections. First, a numerical study was undertaken to estimate in-service stress/strain ranges in the MLPs with liner flaws. Subsequently, small scale tests were carried out to quantify the fatigue performance of such MLPs. The obtained results confirmed that there is a negligible risk of failure of MLP flowlines due to crack initiation at liner imperfections and subsequent breach of the CRA layer, even for pipelines subjected to very severe inservice cyclic loading.

Coordinated Home Energy Management in Community Microgrids with Energy Sharing Among Smart Homes

Scipedia content — Tue, 02 Feb 2021 03:19:49 +0100

International audience; This paper presents a coordination mechanism for smart homes in community microgrids (smart neighborhoods) whether photovoltaics (PV), home battery storage and electric vehicles (EV) are available. The objective of the proposed method is to reduce the electricity cost of the users, as well as the aggregated peak load of the area by establishing an energy sharing ability among neighbors. A decentralized control algorithm deployed by the smart homes is used for battery control and appliance scheduling. It is assumed that the users are the owners of these resources and that they are selfish decision-makers who focus on increasing own benefit. For the neighborhood, a dynamic price model is used, where the price is associated to the aggregated consumption of the neighborhood area. Numerical results show that proposed coordination mechanism with energy sharing provides benefits for both the users and the utility.

Taking the Edge off with Espresso

Scipedia content — Tue, 02 Feb 2021 03:09:01 +0100

We present the design of Espresso, Google's SDN-based Internet peering edge routing infrastructure. This architecture grew out of a need to exponentially scale the Internet edge cost-effectively and to enable application-aware routing at Internet-peering scale. Espresso utilizes commodity switches and host-based routing/packet processing to implement a novel fine-grained traffic engineering capability. Overall, Espresso provides Google a scalable peering edge that is programmable, reliable, and integrated with global traffic systems. Espresso also greatly accelerated deployment of new networking features at our peering edge. Espresso has been in production for two years and serves over 22% of Google's total traffic to the Internet.

Bike share travel time modeling: San Francisco bay area case study

Scipedia content — Tue, 02 Feb 2021 03:04:15 +0100

Bike Share Systems (BSSs) are emerging in many US cities as a new sustainable transportation mode that provides a last-mile solution for short-distance transfers between different private and public transportation modes. In order to encourage the increased use of bikes as a mode of transportation, tools, measures, and planning techniques similar to those used for other transportation modes need to be developed. With precise information on the trip travel time, route planner systems can suggest optimal alternative routes, and manage and control traffic congestion. Although there is a growing body of literature dealing with BSSs, bike travel time has been studied sparingly up to this point. In this paper, we addressed this issue by developing different bike travel time models using random forest (RF), least square boosting (LSBoost) and artificial neural network (ANN) techniques. We studied 33 different predictors affecting bike travel time, including such predictors as travel distance, biker experience, time-of-day, and weather conditions. The RF model produced a reasonable prediction rate with a mean absolute error (MAE) of 84.01 sec and a mean absolute percentage error (MAPE) of 16.92%. We further improved the bike travel time prediction model by using RF and forward stepwise regression to select the best subset of predictors to explain the bike travel time variability. The resulting model, with only seven predictors, reduced the MAE to 82.04 sec and the MAPE to 16.2%.