Scipedia: Documents published in 2020

Chats About Daily Traffic: Agentic Adaptability of Jabodetabek Commuters to Minimize Stress and Transcend Everyday Lives

Scipedia content — Mon, 22 Mar 2021 23:03:03 +0100

With the increasing number of people invading Greater Jakarta and the ongoing improvement of infrastructure in Greater Jakarta or Jabodetabek, one of the challenges faced by the community is traffic congestion. Previous studies revealed the negative impact of traffic congestion on community welfare and mental health. Thus, the present study aims to shed light on how Jabodetabek inhabitants and commuters experience, make sense, and adapt to daily traffic congestion. Data were obtained from discussions in six WhatsApp groups, which included a total of 160 respondents. The study supports the findings of previous studies, that is, traffic congestion leads to increased costs and losses and causes distress. However, the subjective perception of time management enables commuters to adapt to the situation. Nevertheless, the paper presents a novel finding: agentic adaptability of Jabodetabek commuters, which is evidenced by the ability to discover various means of adjusting to traffic congestion. Although effective policies are required to mitigate congestion, the good news is that many opportunities for adjustment await the community in terms of being stuck in traffic.

Document type: Article

Evidence from Nanjing, China

Scipedia content — Mon, 22 Mar 2021 22:55:36 +0100

Promoting a transition in individuals&rsquo

travel mode from car to an integrated metro and bikeshare systems is expected to effectively reduce the traffic congestion that results mainly from commute trips performed by individual automobiles. This paper focuses on the use frequency of an integrated metro&ndash

bikeshare by individuals, and presents empirical evidence from Nanjing, China. Using one-week GPS data collected from the Mobike company, the spatiotemporal characteristics of origin/destination for cyclists who would likely to use shared bike as a feeder mode to metro are examined. Three areas of travel-related spatiotemporal information were extracted including (1) the distribution of walking distances between metro stations and shared bike parking lots

(2) the distribution of cycling times between origins/destinations and metro stations

and (3) the times when metro&ndash

bikeshare users pick up/drop off shared bikes to transfer to/from a metro. Incorporating these three features into a questionnaire design, an intercept survey of possible factors on the use of the combined mode was conducted at seven functional metro stations. An ordered logistic regression model was used to examine the significant factors that influence groupings of metro passengers. Results showed that the high-, medium- and low-frequency groups of metro&ndash

bikeshare users accounted for 9.92%, 21.98% and 68.1%, respectively. Education, individual income, travel purpose, travel time on the metro, workplace location and bike lane infrastructure were found to have significant impacts on metro passengers&rsquo

use frequency of integrated metro&ndash

bikeshares. Relevant policies and interventions for metro passengers of Nanjing are proposed to encourage the integration of metro and bikeshare systems.

Document type: Article

Are Existing Battery Electric Vehicles Adoption Studies Able to Inform Policy? A Review for Policymakers

Scipedia content — Mon, 22 Mar 2021 22:51:16 +0100

Accelerating the adoption of electric vehicles provides a rare historic opportunity for reducing the dependence on fossil fuel and decarbonising road networks in the field of transport. Many countries have introduced various policy packages on both national and local levels to encourage electric vehicle adoption, but their market shares remain low. For better understanding the reasons behind this evidence, exploring the determinants that influence consumers�� adoption intentions is significant. Previous literature reviews have made clear and elaborated syntheses of influential factors; however, a summary of how evidence can be translated into policy through these factors is lacking. In response, this paper synthesises the main policies of various countries, summarises the previous research results, and forms corresponding policy tools, which can provide a reference to policymakers and guide the policy-making process.

Document type: Article

Collaborative Multidepot Petrol Station Replenishment Problem with Multicompartments and Time Window Assignment

Scipedia content — Mon, 22 Mar 2021 22:42:12 +0100

Energy supply is an important system that affects the overall efficiency of urban transportation. To improve the system operational efficiency and reduce costs, we formulate and solve a collaborative multidepot petrol station replenishment problem with multicompartments and time window assignment by establishing a mixed-integer linear programming model. The hybrid heuristic algorithm composed of genetic algorithm and particle swarm optimization is used as a solution, and then the Shapley value method is applied to analyze the profit allocation of each petrol depot under different coalitions. The optimal membership sequence of the cooperation is determined according to the strict monotone path. To analyze and verify the effectiveness of the proposed method, a regional petrol supply network in Chongqing city in China is investigated. Through cooperation between petrol depots in the supply network, the utilization of customer clustering, time window coordination, and distribution truck sharing can significantly reduce the total operation costs and improve the efficiency of urban transportation energy supply. This approach can provide theoretical support for relevant government departments and enterprises to make optimal decisions. The implementation of the joint distribution of energy can promote the sustainable development of urban transportation.

Document type: Article

Li-Ion Batteries: A Review of a Key Technology for Transport Decarbonization

Scipedia content — Mon, 22 Mar 2021 22:38:17 +0100

Lithium ion batteries are experiencing an increased success thanks to their interesting performances, in particular for electric vehicles applications. Their continuous technological improvements in the last years are providing higher energy density and lower manufacturing costs. However, the environmental performance of their supply chain is of paramount importance to guarantee a cleaner alternative to fossil-based solutions on the entire life cycle of the applications. This paper carries out a comprehensive review on the main aspects related to Li-ion batteries manufacturing, to support the readers in understanding the complexity of the subject and the main challenges and opportunities for the future developments of this technology. The paper discusses the expected future demand of batteries; the main aspects related to the supply chain, including existing assets, input materials and alternative technologies; the end-of-life of batteries; the environmental impacts; and the main geopolitical implications.

Document type: Article

Assessing the Impacts of Autonomous Bus-on-Demand Based on Agent-Based Simulation: A Case Study of Fuyang, Zhejiang, China

Scipedia content — Mon, 22 Mar 2021 22:29:50 +0100

This paper envisions and assesses the performance of an autonomous bus-on-demand (ABoD) system. We take Fuyang, Zhejiang, China, as the study area to investigate the spatiotemporal distribution of bus travel demand during workdays, and we propose replacing inefficient bus routes with the ABoD system. Agent-based models with various bus dispatching and operation control strategies are constructed to evaluate the performance of the ABoD system. The behaviors and interactions of the agents, passengers, autonomous buses, and a control center are designed. After the verification of the simulated bus travel demand with real-world demand, a series of scenarios with various ABoD operation strategies are simulated. The simulation results show that, in comparison with both current fixed-schedule bus services and the optimized bus dispatching strategies, the ABoD system occupies fewer road resources and utilizes bus vehicles more efficiently. Besides, the system is adaptive to the sudden surge in bus travel demand and is economically sustainable.

Document type: Article

Exploring everyday mobility in a living lab based on economic interventions

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

New mobility solutions, such as Mobility as a Service, have been suggested to have the potential to reduce car ownership and be part of a transition towards a more sustainable transportation system. However, research suggests that governance measures such as taxation and policies will be needed to ensure sustainability aspects. This paper explores everyday mobility by use of interventions in people��s everyday lives. The focus is on identifying underlying factors that may motivate or hinder changes that are positive from a sustainability perspective. This is then put in the perspective of new mobility services and policy making. Our findings support the view that privately owned cars are hard to replace with new mobility services that contribute to sustainability and are not based on individual cars. Economic interventions for increased sustainability will likely have limited effects, since the alternatives do not offer what car owners value most. Also, limited understanding of the car��s full costs may make the new services appear comparatively more expensive. Furthermore, urban planning to reduce the need for travel, and the capacity of the physical public transport infrastructure will continue to be important. Long vacation trips and ��medium sized flows�� are identified as opportunities for further research and for new solutions to support sustainable mobility transitions.

Document type: Article

Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China

Scipedia content — Mon, 22 Mar 2021 22:18:29 +0100

Since the number of bicycles is critical to the sustainable development of dockless PBS, this research practiced the introduction of a machine learning approach to quantity management using OFO bike operation data in Shenzhen. First, two clustering algorithms were used to identify the bicycle gathering area, and the available bike number and coefficient of available bike number variation were analyzed in each bicycle gathering area��s type. Second, five classification algorithms were compared in the accuracy of distinguishing the type of bicycle gathering areas using 25 impact factors. Finally, the application of the knowledge gained from the existing dockless bicycle operation data to guide the number planning and management of public bicycles was explored. We found the following. (1) There were 492 OFO bicycle gathering areas that can be divided into four types: high inefficient, normal inefficient, high efficient, and normal efficient. The high inefficient and normal inefficient areas gathered about 110,000 bicycles with low usage. (2) More types of bicycle gathering area will affect the accuracy of the classification algorithm. The random forest classification had the best performance in identifying bicycle gathering area types in five classification algorithms with an accuracy of more than 75%. (3) There were obvious differences in the characteristics of 25 impact factors in four types of bicycle gathering areas. It is feasible to use these factors to predict area type to optimize the number of available bicycles, reduce operating costs, and improve utilization efficiency. This work helps operators and government understand the characteristics of dockless PBS and contributes to promoting long-term sustainable development of the system through a machine learning approach.

Document type: Article

Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms

Scipedia content — Mon, 22 Mar 2021 22:14:05 +0100

The recent trend for vehicles to be connected to unspecified devices, vehicles, and infrastructure increases the potential for external threats to vehicle cybersecurity. Thus, intrusion detection is a key network security function in vehicles with open connectivity, such as self-driving and connected cars. Specifically, when a vehicle is connected to an external device through a smartphone inside the vehicle or when a vehicle communicates with external infrastructure, security technology is required to protect the software network inside the vehicle. Existing technology with this function includes vehicle gateways and intrusion detection systems. However, it is difficult to block malicious code based on application behaviors. In this study, we propose a machine learning-based data analysis method to accurately detect abnormal behaviors due to malware in large-scale network traffic in real time. First, we define a detection architecture, which is required by the intrusion detection module to detect and block malware attempting to affect the vehicle via a smartphone. Then, we propose an efficient algorithm for detecting malicious behaviors in a network environment and conduct experiments to verify algorithm accuracy and cost through comparisons with other algorithms.

Document type: Article

A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China

Scipedia content — Mon, 22 Mar 2021 22:10:24 +0100

An airport gate is the core resource of an airport operation, which is an important place for passengers to get on and off the aircraft and for maintaining aircraft. It is the prerequisite for other related dispatch. Effective and reasonable allocation of gates can reduce airport operating costs and increase passenger satisfaction. Therefore, an airport gate assignment problem (AGAP) needs to be urgently solved in the actual operation of the airport. In this paper, considering the actual operation of the airport, we formulate an integer programming model for AGAP by considering multiple constraints. The model aims to maximize the number of passengers on flights parked at the gate. A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. A unique neighborhood structure and search strategy for tabu search are designed. The algorithm can adapt to the dynamic scheduling of airports. Finally, tests are performed using actual airport data selected from Kunming Changshui International Airport in China. The experimental results indicate that the proposed method can enhance the local search ability and global search ability and get satisfactory results in a limited time. These results provide an effective support for the actual gate assignment in airport operations.

Document type: Article

Optimization of a physical internet based supply chain using reinforcement learning

Scipedia content — Mon, 22 Mar 2021 21:57:41 +0100

Physical Internet based supply chains create open, global logistics systems that enable new types of collaboration among participants. The open system allows the logistical examination of vehicle technology innovations such as the platooning concept. This article explores the multiple platoon collaboration. For the reconfiguration of two platoons a heuristic and a reinforcement learning (RL) based models have been developed. To our knowledge, this work is the first attempt to apply an RL-based decision model to solve the problem of controlling platoon cooperation. Vehicle exchange between platoons is provided by a virtual hub. Depending on the various input parameters, the efficiency of the model was examined through numerical examples in terms of the target function based on the transportation cost. Models using platoon reconfiguration are also compared to the cases where no vehicle exchange is implemented. We have found that a reinforcement learning based model provides a more efficient solution for high incoming vehicle numbers and low dispatch interval, although for low vehicle numbers heuristics model performs better.

Document type: Article

A Cost and Passenger Responsible Optimization Method for the Operation Plan of Additional High-Speed Trains in a Peak Period

Scipedia content — Mon, 22 Mar 2021 21:55:21 +0100

In the peak period of a railway system, operators typically add additional trains to provide increased capacity to satisfy the increasing passenger demand. The paper proposes a new optimization framework for designing the operation plan, which includes the number of additional trains, train type, stop plan, and timetable, for additional trains in a peak period. A space-time network representation is used to obtain a feasible primary operation plan by finding a set of feasible space-time paths in the space-time network. Considering simultaneously the passenger demand and the trains�� total travel times, we formulate a biobjective integer programming model for generating a cost and passenger responsible primary operation plan. A set of loading capacity constraints are formulated in the model to guarantee a suitable loading capacity for each station��s passenger demand and better service for passengers. The CPLEX solver is used to solve the proposed model and to generate the optimal operation plan. Two sets of numerical experiments are conducted on a small-scale rail corridor and on the Wuhan-Guangzhou rail corridor to evaluate the performance of the proposed method. The results of the experiments show that the primary operation plan can be obtained within an acceptable computation time.

Document type: Article

A Theoretical Research Framework of Future Sustainable Urban Freight Transport for Smart Cities

Scipedia content — Mon, 22 Mar 2021 21:38:16 +0100

This paper aims to construct a theoretical research framework for sustainable urban freight transport (SUFT) from the perspectives of future urban development and distribution innovations, and appropriate research methods are discussed, as well. Urban freight transport plays a critical role in the promotion of sustainable and livable cities. According to the literature review, considerable research on SUFT has focused on resolving some specific problems with a short-term perspective. The existence of an urban freight transport strategy is noted, which should be embedded in an overall sustainable development strategy with a long-term perspective (approximately 20&ndash

30 years). Nevertheless, considerable research has paid scant attention to the long-term planning of SUFT. Given this, this paper contributes to the closure of this gap. First, this paper presents a systematic literature review (SLR) to highlight published papers involving foresight research within the past 16 years (2003&ndash

2018). This step contributes to the understanding of research methods that can be used in foresight research. Subsequently, this paper discusses the impacts of both urban development and distribution innovations on future SUFT, and these effects are used to select the appropriate methods to construct the theoretical research framework. Finally, the theoretical research framework of long-term planning for SUFT is developed on the basis of two future perspectives: the trends of urban development and the application of urban distribution innovations. This framework is intended to provide an approach to designing sustainable urban logistics, taking into account urban development and distribution innovations.

Document type: Article

Efficiency of Telematics Systems in Management of Operational Activities in Road Transport Enterprises

Scipedia content — Mon, 22 Mar 2021 21:35:03 +0100

Implemented in road transport enterprises (RTEs) on a large scale, telematics systems are dedicated both to the particular aspects of their operation and to the integrated fields of the total operational functioning of such entities. Hence, a research problem can be defined as the identification of their efficiency levels in the context of operational activities undertaken by RTEs (including more holistic effects, e.g., lowering fuel/energy consumption and negative environmental impacts). Current research studies refer to the efficiency of some particular modules, but there have not been any publications focused on describing the efficiency of telematics systems in a more integrated (holistic) way, due to the lack of a universal tool that could be applied to provide this type of measurement. In this paper, an attempt at filling the identified cognitive gap is presented through empirical research analysing the original matrix developed by the authors that refers to the efficiency rates of organisational activities undertaken by RTEs. The purpose of this paper is to present a tool that has been designed to provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The results are presented in a form of an individual (ontogenetic) matrix of the analysed companies, for which a determinant was calculated with the use of Sarrus�� rule. Obtained in such a way, the set of values identified for the determinants of the subsequent ontogenetic matrices came as an arithmetic progression that characterised the scope and the level of the influence exerted by the implemented IT (information technology) systems on the organisational efficiency of operational activities undertaken by the analysed RTEs. We present a hypothesis stating that the originally developed matrix can be viewed as a reliable tool used for comparative analysis in the field of efficiency of telematics systems in RTEs, and this hypothesis was positively verified during the research. The obtained results prove the significant potential for the wide application of the discussed matrix, which can be used as a universal tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by RTEs.

Document type: Article

Evaluating Active Traffic Management (ATM) Strategies under Non-Recurring Congestion: Simulation-Based with Benefit Cost Analysis Case Study

Scipedia content — Mon, 22 Mar 2021 21:32:48 +0100

Dynamic hard shoulder running and ramp closure are two active traffic management (ATM) strategies that are used to alleviate highway traffic congestion. This study aims to evaluate the effects of these two strategies on congested freeways under non-recurring congestion. The study��s efforts can be considered in two parts. First, we performed a detailed microsimulation analysis to quantify the potential benefits of these two ATM strategies in terms of safety, traffic operation, and environmental impact. Second, we evaluated the implementation feasibility of these two strategies. The simulation results indicated that the implementation of the hard shoulder showed a 50%�C57% reduction in delay, a 41%�C44% reduction in fuel consumption and emissions, and a 15%�C18% increase in bottleneck throughput. By contrast, the implementation of ramp closure showed a 20%�C34% decrease in travel time, a 6%�C9% increase in bottleneck throughput, and an 18%�C32% reduction in fuel consumption and emissions. Eventually, both strategies were found to be economically feasible.

Document type: Article

Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

Scipedia content — Mon, 22 Mar 2021 21:30:43 +0100

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle&ndash

vehicle collision scenario and a vehicle&ndash

pedestrian collision scenario.

Document type: Article

Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania

Scipedia content — Mon, 22 Mar 2021 21:19:45 +0100

Abstract. Due to their widespread and continuous expansion, transportation networks are considerably exposed to natural hazards such as earthquakes, floods, landslides or hurricanes. The vulnerability of specific segments and structures among bridges, tunnels, pumps or storage tanks can translate not only into direct losses but also into significant indirect losses at the systemic level. Cascading effects such as post-event traffic congestion, building debris or tsunamis can contribute to an even greater level of risk. To support the effort of modeling the natural hazards' implications at the full transportation network scale, we developed a new applicable framework, relying on (i)?GIS to define, analyze and represent transportation networks; (ii)?methods for determining the probability of network segments to fail due to natural-hazard effects; (iii)?Monte Carlo simulation for multiple scenario generation; (iv)?methods to analyze the implications of connectivity loss on emergency intervention times and transit disruption; and (v)?correlations with other vulnerability and risk indicators. Currently, the framework is integrated into ArcGIS Desktop as a toolbox entitled ��Network-risk��, which makes use of the ModelBuilder functions and is free to download and modify. Network-risk is an attempt to bring together interdisciplinary research with the goal of creating an automated solution to deliver insights on how a transportation network can be affected by natural hazards, directly and indirectly, assisting in risk evaluation and mitigation planning. In this article we present and test Network-risk at the full urban scale for the road network of Bucharest. This city is one of Europe's most exposed capitals to earthquakes, with high seismic-hazard values and a vulnerable building stock but also significant traffic congestion problems not yet accounted for in risk analyses and risk reduction strategies.

Document type: Article

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

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

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

Document type: Article

A Proposal for Modeling Indoor�COutdoor Spaces through IndoorGML, Open Location Code and OpenStreetMap

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

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

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

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

Document type: Article

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

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

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

Electric Vehicles&ndash

Power Grid&ndash

Traffic Network&rsquo

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

charging behavior.

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Aberrant Driving Behaviours on Risk Involvement among Drivers in China

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Operators�� Load Monitoring and Management

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Project O2 - Macroscopic Fundamental Diagram Based Discrete Transportation Network Design

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

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

Document type: Article

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

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

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

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

health related to road transport variables for Sã

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

MLP, Extreme Learning Machines&mdash

ELM, and Echo State Neural Networks&mdash

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

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

good health and well-being, 7&mdash

affordable and clean energy, and 11&mdash

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

Document type: Article

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

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

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

versus after&mdash

activation of the automation on users&rsquo

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

sympathy&rdquo

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

Document type: Article

A Study on Public Adoption of Robo-Taxis in China

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

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

&rsquo

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

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

Document type: Article

Pedidos y transporte: Una unidad estrat��gica de estudio en indicadores log��sticos de la nueva era

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

La presente investigaci��n tiene como objetivo analizar las tendencias principales que comprende los pedidos y el transporte, para ello se ha considerado como referencia tres fuentes de an��lisis: 1) Investigaci��n de Campo, en el sector comercial de la zona 3 del Ecuador. 2) An��lisis gr��fico descriptivo del mercado 3) An��lisis estad��stico inferencial mediante la prueba de Friedman. La metodolog��a se enmarc�� en un an��lisis descriptivo explicativo, el instrumento de investigaci��n fue una encuesta aplicado a una muestra conformada de 373 empresas comerciales. Los resultados obtenidos reflejaron un nivel de significancia asint��tica de 0.092 mediante la prueba de Friedman para las variables consideradas en comparaci��n con el nivel cr��tico de 0.05 por lo cual se indica que no hay diferencias estad��sticas significativas entre las empresas en relaci��n a las dimensiones pedidos y transporte en las 4 provincias seleccionadas.?

Document type: Article

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

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

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

Document type: Article

Public Transport Quality, Safety, and Perceived Accessibility

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Environmental Sustainability in City Logistics Measures

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Welfare consequences of request stops at transport services with low demand

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

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

Document type: Article

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

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

Sustainable transport infrastructure can determine the effect of countries&rsquo

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

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

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

Document type: Article

General-purpose hierarchical optimisation of machine learning pipelines with grammatical evolution

Scipedia content — Tue, 16 Feb 2021 13:46:03 +0100

This paper introduces Hierarchical Machine Learning Optimisation (HML-Opt), an AutoML framework that is based on probabilistic grammatical evolution. HML-Opt has been designed to provide a flexible framework where a researcher can define the space of possible pipelines to solve a specific machine learning problem, which can range from high-level decisions about representation and features to low-level hyper-parameter values. The evaluation of HML-Opt is presented via two different case studies, both of which demonstrate that it is competitive with existing AutoML tools on a variety of benchmarks. Furthermore, HML-Opt can be applied to novel problems, such as knowledge extraction from natural language text, whereas other techniques are insufficiently flexible to capture the complexity of these scenarios. The source code for HML-Opt is available online for the research community. This research has been supported by a Carolina Foundation grant in agreement with University of Alicante and University of Havana. Moreover, it has also been partially funded by both aforementioned universities, the Generalitat Valenciana (Conselleria d��Educaci��, Investigaci��, Cultura i Esport) and the Spanish Government through the projects LIVING-LANG (RTI2018-094653-B-C22) and SIIA (PROMETEO/2018/089, PROMETEU/2018/089).

The most difficult at-fault fatal crashes to avoid with current active safety technology

Scipedia content — Tue, 16 Feb 2021 13:43:39 +0100

Objective: We studied which current fatal at-fault crashes would occur despite the most advanced current active safety devices (up to SAE level 2 of driving automation) and how frequent these crashes would be. Methods: We carried out a cross-sectional study of passenger cars that were first registered during the period 1st January 2010 to 31st December 2017 in Finland. To gain the true exposure for these cars, we accessed the national Vehicular and Driver Data Register to obtain the mileage information and the registration count for the study period of 2010-17. Similarly, we accessed the registry of Finnish road accident investigation teams and included all fatal at-fault crashes among the cars in our study for the same period. We used a real world reference technology for each active safety system in our analysis and chose one car brand as an example. This gave us exact system specifications and enabled testing the operation of the systems on the road. We performed field tests to gain further information on the precise operation of the safety systems in different operating conditions. Finally, we gathered all information on the studied active safety systems and analyzed the investigated at-fault fatal crashes case-by-case using our four level method. Results: Cars in our study were the primary party in 113 investigated fatal accidents during the years 2010-17. In 87 of the accidents, the leading cause of death was the injuries due to the crash, and these cases were classified as ��unavoidable�� (n = 58, 67 %), ��avoidable�� (n = 26, 30 %) or unsolved (n = 3, 3 %). Of the 58 ��unavoidable�� crashes 21 (36 %) were suicides, 21 (36%) involved active driver input which would have prevented the safety system operation, 15 (17 %) featured circumstances beyond the safety system performance and in one loss-of-control crash the driver had disabled the relevant safety system (electronic stability control). The registration years of the cars in our study (2010-17) totaled 3,772,864 and during this period, the cars travelled 75.9billion kilometers. The crash incidence of the ��unavoidable�� at-fault fatal crashes was 0.76-0.80 fatal crashes per billion kilometers and 15-16 fatal crashes per million registration years. Conclusions: We calculated a crash incidence for the ��unavoidable�� crashes which was 20�C27% smaller than the observed crash rate of ESC-fitted passenger cars in our previous study. We concluded that suicides, active driver input until the crash, and challenging weather and road conditions are the most difficult factors for current active safety systems. Our analysis did not account for issues such as system usability or driver acceptance and therefore our results should be regarded as something that is currently theoretically achievable. However, the observed incidence is a good reference for automated driving development and the crash rate of automated cars. Peer reviewed

Is the H2 economy realizable in the foreseeable future? Part II: H2 storage, transportation, and distribution

Scipedia content — Tue, 16 Feb 2021 13:42:04 +0100

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

A review of silhouette extraction algorithms for use within visual hull pipelines

Scipedia content — Tue, 16 Feb 2021 13:41:17 +0100

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

A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management

Scipedia content — Tue, 16 Feb 2021 13:40:55 +0100

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

What drives decarbonization of new passenger cars?

Scipedia content — Tue, 16 Feb 2021 13:37:47 +0100

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

Balancing responsibilities: Effects of growth of variable renewable energy, storage, and undue grid interaction

Scipedia content — Tue, 16 Feb 2021 13:15:34 +0100

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

Balancing responsibilities

Scipedia content — Tue, 16 Feb 2021 13:07:24 +0100

Liquid Organic Hydrogen Carriers and alternatives for international transport of renewable hydrogen

Scipedia content — Tue, 16 Feb 2021 13:06:31 +0100

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

A data driven typology of electric vehicle user types and charging sessions

Scipedia content — Tue, 16 Feb 2021 13:04:14 +0100

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

A Study on Cyclists behaviour and bicycles Kinematic

Scipedia content — Tue, 16 Feb 2021 12:44:21 +0100

study on cyclists�� behaviour and bicycle kinematic was conducted to determine the behavioural characteristics and kinetic representatives, as they are closely linked. The study focused on the behaviour of cyclists at road intersections and on cycle paths, including the crossing speeds, the accelerations, the time spent covering a fixed distance, as well as the most complex and dynamic part of the road transport system, the human factor. Whether the road users follow the laws of traffic and adopt a cautious and considerate driving attitude has a great impact on road safety. Video cameras placed at different locations were used to collect traffic data. A post processing phase to analyze the data followed. Interesting groups behaviour of cyclists were identified, as well as many characteristics curves related to the kinematic parameters. In general, a poor attitude towards compliance with behavioural rules has emerged in the medium-sized city of Bologna, Italy, especially for male cyclists. In addition, the average flow speed was observed under normal conditions, resulting in the order of 4 m/s. The results obtained are useful for understanding the performance of mixed traffic at intersection and on bicycle lanes, as well as building a basis for road accident reconstruction.

Age effects on traffic sign comprehension

Scipedia content — Tue, 16 Feb 2021 12:23:25 +0100

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

Adaptive large neighborhood search for the time-dependent profitable pickup and delivery problem with time windows

Scipedia content — Tue, 16 Feb 2021 12:14:02 +0100

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

A framework for modelling and analysing coordination challenges in hinterland transport systems

Scipedia content — Tue, 16 Feb 2021 12:08:11 +0100

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

Liquefaction fragility of sewer pipes derived from the case study of Urayasu (Japan)

Scipedia content — Tue, 16 Feb 2021 12:00:09 +0100

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

Determining the Depth and Location of Buried Pipeline by Magnetometer Survey

Scipedia content — Tue, 16 Feb 2021 11:48:52 +0100

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

A scoping indicator identifying potential impacts of all-inclusive MaaS taxis on other modes in Manchester

Scipedia content — Tue, 16 Feb 2021 11:38:38 +0100

We present a spatial scoping indicator of the potential impacts of an all-inclusive taxi service as part of a plausible but hypothetical Mobility as a Service (MaaS) package in Manchester UK. Our indicator identifies the number of people in each area who have some potential for mode shift from walking, cycling, public transport or car commuting to an all-inclusive taxi service within a MaaS package. We find the method quick and straightforward. In our case study, potential to shift from walk to an all-inclusive taxi service within a MaaS package is almost double the potential shift away from car, which represents a risk of increased car use.

Fleet modelling in strategic multi-criteria decision-making of approved training organization from capacity building and resource dependency theory perspective: risk taxonomy methodology

Scipedia content — Tue, 16 Feb 2021 11:33:20 +0100

WOS: 000531158800001

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

Vision-Enhanced Low-Cost Localization In Crowdsourced Maps

Scipedia content — Tue, 16 Feb 2021 11:32:35 +0100

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

On the sustainable perishable food supply chain network design:A dairy products case to achieve sustainable development goals

Scipedia content — Tue, 16 Feb 2021 11:25:25 +0100

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

Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Scipedia content — Tue, 16 Feb 2021 11:20:58 +0100

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

Net emission reductions from electric cars and heat pumps in 59 world regions over time

Scipedia content — Tue, 16 Feb 2021 11:18:38 +0100

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

Online Driver Distraction Detection Using Long Short-Term Memory

Scipedia content — Tue, 16 Feb 2021 11:07:09 +0100

Lane-keeping assistance systems for vehicles may be more acceptable to users if the assistance was adaptive to the driver's state. To adapt systems in this way, a method for detection of driver distraction is needed. Thus, we propose a novel technique for online detection of driver's distraction, modeling the long-range temporal context of driving and head tracking data. We show that long short-term memory (LSTM) recurrent neural networks enable a reliable subject-independent detection of inattention with an accuracy of up to 96.6%. Thereby, our LSTM framework significantly outperforms conventional approaches such as support vector machines (SVMs).

User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions

Scipedia content — Tue, 16 Feb 2021 11:03:05 +0100

Purpose Precision cancer medicine is dependent on accurate prediction of disease and treatment outcome, requiring integration of clinical, imaging and interventional knowledge. User controlled pipelines are capable of feature integration with varied levels of human interaction. In this work we present two pipelines designed to combine clinical, radiomic (quantified imaging), and RTx-omic (quantified radiation therapy (RT) plan) information for prediction of locoregional failure (LRF) in head and neck cancer (HN and 2) a pipeline with minimal user input that utilizes deep learning convolutional neural networks to extract and combine CT imaging, RT dose and clinical features for model development. Results Clinical features with logistic regression in our highly user-driven pipeline had the highest precision recall area under the curve (PR-AUC) of 0.66 (0.33�C0.93), where a PR-AUC?=?0.11 is considered random. CONCLUSIONS: Our work demonstrates the potential to aggregate features from multiple specialties for conditional-outcome predictions using pipelines with varied levels of human interaction. Most importantly, our results provide insights into the importance of data curation and quality, as well as user, data and methodology bias awareness as it pertains to result interpretation in user controlled pipelines.

Influence of values attitudes towards transport modes and companions on travel behavior

Scipedia content — Tue, 16 Feb 2021 10:59:34 +0100

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

Potential advantages in heat and power production when biogas is collected from several digesters using dedicated pipelines - A case study in the "Province of West-Flanders" (Belgium)

Scipedia content — Tue, 16 Feb 2021 10:54:51 +0100

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

A variant of the split vehicle routing problem with simultaneous deliveries and pickups for inland container shipping in dry-port based systems

Scipedia content — Tue, 16 Feb 2021 10:54:06 +0100

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

Route and stopping intent prediction at intersections from car fleet data

Scipedia content — Tue, 16 Feb 2021 10:53:20 +0100

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

Operational flexibility of electrified transport and thermal units in distribution grid

Scipedia content — Tue, 16 Feb 2021 10:53:08 +0100

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

Cycling as a service assessed from a combined business-model and transitions perspective

Scipedia content — Tue, 16 Feb 2021 10:46:50 +0100

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

Polynomial Augmented Extended Kalman Filter to Estimate the State of Charge of Lithium-Ion Batteries

Scipedia content — Tue, 16 Feb 2021 10:34:43 +0100

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

Dataset for calculating the currents and voltages induced on underground pipelines by nonparallel overhead power lines

Scipedia content — Tue, 16 Feb 2021 10:20:43 +0100

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

The Covid-19 pandemic effects in rural areas

Scipedia content — Tue, 16 Feb 2021 10:15:56 +0100

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

Performance comparison of population-based optimization algorithms for air traffic control

Scipedia content — Tue, 16 Feb 2021 10:08:47 +0100

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

Distributed control of active cell balancing and low-voltage bus regulation in electric vehicles using hierarchical model-predictive control

Scipedia content — Tue, 16 Feb 2021 10:01:34 +0100

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

Evaluating urban logistics schemes using agent-based simulation

Scipedia content — Tue, 16 Feb 2021 09:59:13 +0100

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

Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives

Scipedia content — Tue, 16 Feb 2021 09:55:58 +0100

Highlights ? HSR had impacts on socio-economic, territorial and transport systems in several countries. ? The paper analyses the impacts induced by HSR services in Italy after ten years of operation. ? Italy represents the first case of competitive HSR market without public subsidies. ? Competition between HSR operators brought a significant decrease in ticket prices (-40%) ? HSR passengers/year passed from 15 to 45 millions (+200%) in 10?years. ? HSR contributed, in 10?years, to an increase of the rail-based transport accessibility up to?+?30% ? HSR contributed to an extra growth of per capita GDP of?+?2.6�C5.6% in 10?years. ? Regional equity in terms of travel time accessibility decreased by 11% in 10?years. ? Extension of the HSR network would increase accessibility (+18%), economic growth (+3.6%) and equity (+49%)

The deployment of HSR services in the recent decades has been, arguably, the most significant innovation for intercity travel around the globe. HSR has brought impacts which have been widely studied in different countries in relation to the different socioeconomic, territorial and transport characteristics. This paper analyses the economic growth, the transport accessibility and the social impacts observed in Italy after ten years of HSR operation, as well as the estimated impacts of the system completion. The Italian case study is of particular interest since along the 1,467?km of new high speed line (300?km/h), a combination of major cities distances and a unique HSR competitive market, producing prices reductions and more daily trains, brought a 200% increase of HSR demand (from 15 to 45 millions of passengers/year). Estimations results show that, on average, HSR in Italy contributed to a significant increase in transport accessibility (+32%) for the zones along the HSR network, while only marginal for the others (+6%). Impacts on the economic growth show that HSR has contributed to an extra growth of per capita GDP of?+?2.6% in 10?years and would have contributed to a further increase of 3.6% if the final project scenario (HSR_N) would had been completed by 2018. Regional (horizontal) equity impacts were evaluated in terms of the Gini indexes variations with respect to the distribution of the transport accessibility. It results that HSR in Italy has decreased equity in terms of users�� travel time accessibility of 11%, increasing the differences between the zones served by HSR and those not. If the HSR_N scenario would have been completed equity indices would have increased of 29% with respect to the pre-HSR 2008 scenario, thus reducing regional inequalities in the country. Results show that the HSR project was a country-level ��game changer�� in Italy, suggesting that the wider economic benefits, the assumptions on market regulation, the effects on regional disparities and the compensatory measures should be included in the ex ante and ex post evaluation of similar projects.

Air Traffic Control Capacity Planning Under Demand and Capacity Provision Uncertainty

Scipedia content — Tue, 16 Feb 2021 09:54:01 +0100

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

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

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

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

Document type: Article

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

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

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

Document type: Article

Train Type Identification at S&C

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

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

Document type: Article

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

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

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

Document type: Article

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

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

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

Document type: Article

Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles

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

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

Document type: Article

Taxi Demand Prediction Based on a Combination Forecasting Model in Hotspots

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

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

Document type: Article

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

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

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

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

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

Document type: Article

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

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

Electric mobility offers a low cost of travel along with energy and harmful emissions savings. Nevertheless, a comprehensive literature review is missing for the prospects of electric vehicles in developing countries. Such an overview would be instrumental for policymakers to understand the barriers and opportunities related to different types of electric vehicles (EVs). Considering the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a systematic review was performed of the electronic databases Google Scholar and Web of Science for the years 2010�C2020. The electric four-wheelers, hybrid electric vehicles and electric two-wheeler constituted the electric vehicles searched in the databases. Initially, 35 studies identified in the Web of Science that matched the criteria were studied. Later, 105 other relevant reports and articles related to barriers and opportunities were found by using Google Scholar and studied. Results reveal that electric four-wheelers are not a feasible option in developing countries due to their high purchase price. On the contrary, electric two-wheelers may be beneficial as they come with a lower purchase price.

Document type: Article