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  Subjects -> TRANSPORTATION (Total: 164 journals)
    - AIR TRANSPORT (7 journals)
    - AUTOMOBILES (21 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (29 journals)
    - TRANSPORTATION (96 journals)

TRANSPORTATION (96 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 64)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 1)
Archives of Transport     Open Access   (Followers: 15)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 6)
Cities in the 21st Century     Open Access   (Followers: 11)
Economics of Transportation     Partially Free   (Followers: 11)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 6)
European Transport Research Review     Open Access   (Followers: 21)
Geosystem Engineering     Hybrid Journal  
IATSS Research     Open Access  
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 8)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 7)
IFAC-PapersOnLine     Open Access  
International Innovation - Transport     Open Access   (Followers: 8)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 7)
International Journal of e-Navigation and Maritime Economy     Open Access  
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 8)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 9)
International Journal of Micro-Nano Scale Transport     Full-text available via subscription   (Followers: 1)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 9)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 9)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 13)
International Journal of Transportation Science and Technology     Full-text available via subscription   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
International Journal of Vehicular Technology     Open Access   (Followers: 4)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 11)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 4)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 5)
Journal of Navigation     Hybrid Journal   (Followers: 157)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 7)
Journal of Sustainable Mobility     Full-text available via subscription  
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 4)
Journal of Transport & Health     Hybrid Journal   (Followers: 5)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 6)
Journal of Transport Geography     Hybrid Journal   (Followers: 21)
Journal of Transport History     Full-text available via subscription   (Followers: 14)
Journal of Transport Literature     Open Access   (Followers: 6)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 9)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 13)
Journal of Transportation Technologies     Open Access   (Followers: 14)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 6)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access  
Logistique & Management     Full-text available via subscription  
Mobility in History     Full-text available via subscription   (Followers: 2)
Modern Transportation     Open Access   (Followers: 9)
Nonlinear Dynamics     Hybrid Journal   (Followers: 5)
Open Journal of Safety Science and Technology     Open Access   (Followers: 7)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 1)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 9)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 11)
Public Transport     Hybrid Journal   (Followers: 15)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access  
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 10)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 1)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 2)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Hybrid Journal   (Followers: 13)
Transport and Telecommunication Journal     Open Access   (Followers: 3)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Problems     Open Access  
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 11)
Transportation     Hybrid Journal   (Followers: 29)
Transportation Geotechnics     Full-text available via subscription   (Followers: 2)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 7)
Transportation Journal     Full-text available via subscription   (Followers: 11)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 32)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 30)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 21)
Transportation Research Procedia     Open Access   (Followers: 4)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 33)
Transportation Science     Full-text available via subscription   (Followers: 20)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 5)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 3)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 5)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 24)
Vehicular Communications     Full-text available via subscription   (Followers: 2)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part C: Emerging Technologies
  [SJR: 1.943]   [H-I: 55]   [21 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [2970 journals]
  • An inference engine for smartphones to preprocess data and detect
           stationary and transportation modes
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Hamid Reza Eftekhari, Mehdi Ghatee
      A smartphone can be utilized as a cost-effective device for the purposes of intelligent transportation system. To detect the movement and the stationary statuses in the motorized and non-motorized modes, this study develops a new inference engine, including two sets of rules. The first sets of rules are defined by the related thresholds on the features of smartphone sensors while the second sets are extracted from the human knowledge to improve the results of the first rules. The experimental results reveal that by utilizing Inertial Measurement Unit (IMU) sensors in the proposed inference engine, it is possible to save 40% energy in comparison with the previous research. Moreover, this engine increases the accuracy of the motorized mode detection to 95.2% and determines the stationary states in motorized mode with 97.1% accuracy.


      PubDate: 2016-06-24T22:44:36Z
       
  • Calibration of nonlinear car-following laws for traffic oscillation
           prediction
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Christine Rhoades, Xin Wang, Yanfeng Ouyang
      Frequency-domain analysis has been successfully used to (i) predict the amplification of traffic oscillations along a platoon of vehicles with nonlinear car-following laws and (ii) measure traffic oscillation properties (e.g., periodicity, magnitude) from field data. This paper proposes a new method to calibrate nonlinear car-following laws based on real-world vehicle trajectories, such that oscillation prediction (based on the calibrated car-following laws) and measurement from the same data can be compared and validated. This calibration method, for the first time, takes into account not only the driver’s car-following behavior but also the vehicle trajectory’s time-domain (e.g., location, speed) and frequency-domain properties (e.g., peak oscillation amplitude). We use Newell’s car-following model (1961) as an example and calibrate its parameters based on a penalty-based maximum likelihood estimation procedure. A series of experiments using Next Generation Simulation (NGSIM) data are conducted to illustrate the applicability and performance of the proposed approach. Results show that the calibrated car-following models are able to simultaneously reproduce observed driver behavior, time-domain trajectories, and oscillation propagation along the platoon with reasonable accuracy.


      PubDate: 2016-06-24T22:44:36Z
       
  • Optimal recharging strategies for electric vehicle fleets with duration
           constraints
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): I-Lin Wang, Yiqi Wang, Ping-Cheng Lin
      Electrical vehicles (EVs) have become a popular green transportation means recently because they have lower energy consumption costs and produce less pollution. The success of EVs relies on technologies to extend their driving range, which can be achieved by the good deployment of EV recharging stations. This paper considers a special EV network composed of fixed routes for an EV fleet, where each EV moves along its own cyclic tour of depots. By setting up a recharging station on a depot, an EV can recharge its battery for no longer than a pre-specified duration constraint. We seek an optimal deployment of recharging stations and an optimal recharging schedule for each EV such that all EVs can continue their tours in the planning horizon with minimum total costs. To solve this difficult location problem, we first propose a mixed integer program (MIP) formulation and then derive four new valid inequalities to shorten the solution time. Eight MIP models, which were created by adding different combinations of the four valid inequalities to the basic model, have been implemented to test their individual effectiveness and synergy over twelve randomly generated EV networks. Valuable managerial insights into the usage of valid inequalities and the relations between the battery capacity and the total costs, number of recharging facilities to be installed, and running time are analyzed.


      PubDate: 2016-06-20T22:38:39Z
       
  • Operational analysis of the contraflow left-turn lane design at signalized
           intersections in China
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jiaming Wu, Pan Liu, Zong Z. Tian, Chengcheng Xu
      The primary objective of the study was to evaluate the impacts of an unconventional left-turn treatment called contraflow left-turn lane (CLL) on the operational performance of left-turn movement at signalized intersections. An analytical model was developed for estimating the capacity of left-turn movement at signalized intersections with the CLL design. The capacity model was calibrated and validated using field data collected at six approaches at five signalized intersections in the city of Handan, China. The results of field data analyses showed that the use of CLL design improved the capacity of left-turn movements. However, the capacity gains with the CLL design were quite stochastic considering the randomness in the arrivals of left-turning vehicles. Analytical delay models were proposed for estimating the delay to left-turning vehicles at intersections with the CLL design. A procedure was also proposed for optimizing the location of the upstream median opening and the green interval of the pre-signal. Simulation analyses were conducted to compare the delay experienced by the left-turning and through vehicles at signalized intersections with the conventional left-turn lane, the CLL and another unconventional left-turn treatment entitled “tandem design”. The results showed that both CLL and tandem designs outperformed conventional left-turn lane design; and the CLL design generated less delay to both the left-turning and through vehicles as compared with the tandem design.


      PubDate: 2016-06-20T22:38:39Z
       
  • Updating origin–destination matrices with aggregated data of GPS
           traces
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Qian Ge, Daisuke Fukuda
      The practice of estimating origin–destination (OD) demand usually requires large-scale travel surveys. To reduce the cost and time spent on surveys, individual trajectory data obtained from mobile devices has been used as an alternative dataset since the last two decades for OD estimation but also constrained in practice in some countries. To estimate OD matrices while protecting privacy, this study uses aggregated data of mobile phone traces to estimate work-related trips. The proposed approach is a sequential updater based on the maximum entropy principle. Trip production and attraction are firstly calculated by a non-linear programming problem followed by a matrix fitting problem to distribute trips to each OD pair. Numerical study shows that updated values are much closer to the synthesize real values than the referred ones. The case study in Tokyo further demonstrates that the proposed updating approach can track the change of travel pattern.


      PubDate: 2016-06-20T22:38:39Z
       
  • Global convergence of the trial-and-error method for the traffic-restraint
           congestion-pricing scheme with day-to-day flow dynamics
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Min Xu, Qiang Meng, Zhongxiang Huang
      The traffic-restraint congestion-pricing scheme (TRCPS) aims to maintain traffic flow within a desirable threshold for some target links by levying the appropriate link tolls. In this study, we propose a trial-and-error method using observed link flows to implement the TRCPS with the day-to-day flow dynamics. Without resorting to the origin–destination (O–D) demand functions, link travel time functions and value of time (VOT), the proposed trial-and-error method works as follows: tolls for the traffic-restraint links are first implemented each time (trial) and they are subsequently updated using observed link flows in a disequilibrium state at any arbitrary time interval. The trial-and-error method has the practical significance because it is necessary only to observe traffic flows on those tolled links and it does not require to wait for the network flow pattern achieving the user equilibrium (UE) state. The global convergence of the trial-and-error method is rigorously demonstrated under mild conditions. We theoretically show the viability of the proposed trial-and-error method, and numerical experiments are conducted to evaluate its performance. The result of this study, without doubt, enhances the confidence of practitioners to adopt this method.


      PubDate: 2016-06-20T22:38:39Z
       
  • Multiple-phase train trajectory optimization with signalling and
           operational constraints
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Pengling Wang, Rob M.P. Goverde
      The train trajectory optimization problem aims at finding the optimal speed profiles and control regimes for a safe, punctual, comfortable, and energy-efficient train operation. This paper studies the train trajectory optimization problem with consideration of general operational constraints as well as signalling constraints. Operational constraints refer to time and speed restrictions from the actual timetable, while signalling constraints refer to the influences of signal aspects and automatic train protection on train operation. A railway timetable provides each train with a train path envelope, which consists of a set of positions on the route with a specified target time and speed point or window. The train trajectory optimization problem is formulated as a multiple-phase optimal control model and solved by a pseudospectral method. This model is able to capture varying gradients and speed limits, as well as time and speed constraints from the train path envelope. Train trajectory calculation methods under delay and no-delay situations are discussed. When the train follows the planned timetable, the train trajectory calculation aims at minimizing energy consumption, whereas in the case of delays the train trajectory is re-calculated to track the possibly adjusted timetable with the aim of minimizing delays as well as energy consumption. Moreover, the train operation could be affected by yellow or red signals, which is taken into account in the train speed regulation. For this purpose, two optimization policies are developed with either limited or full information of the train ahead. A local signal response policy ensures that the train makes correct and quick responses to different signalling aspects, while a global green wave policy aims at avoiding yellow signals and thus proceed with all green signals. The method is applied in a case study of two successive trains running on a corridor with various delays showing the benefit of accurate predictive information of the leading train on energy consumption and train delay of the following train.


      PubDate: 2016-06-20T22:38:39Z
       
  • A methodology for identifying similar days in air traffic flow management
           initiative planning
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Kenneth D. Kuhn
      This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.
      Graphical abstract image

      PubDate: 2016-06-15T13:10:40Z
       
  • Validating and improving public transport origin–destination
           estimation algorithm using smart card fare data
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Azalden Alsger, Behrang Assemi, Mahmoud Mesbah, Luis Ferreira
      Smart card data are increasingly used for transit network planning, passengers’ behaviour analysis and network demand forecasting. Public transport origin–destination (O–D) estimation is a significant product of processing smart card data. In recent years, various O–D estimation methods using the trip-chaining approach have attracted much attention from both researchers and practitioners. However, the validity of these estimation methods has not been extensively investigated. This is mainly because these datasets usually lack data about passengers’ alighting, as passengers are often required to tap their smart cards only when boarding a public transport service. Thus, this paper has two main objectives. First, the paper reports on the implementation and validation of the existing O–D estimation method using the unique smart card dataset of the South-East Queensland public transport network which includes data on both boarding stops and alighting stops. Second, the paper improves the O–D estimation algorithm and empirically examines these improvements, relying on this unique dataset. The evaluation of the last destination assumption of the trip-chaining method shows a significant negative impact on the matching results of the differences between actual boarding/alighting times and the public transport schedules. The proposed changes to the algorithm improve the average distance between the actual and estimated alighting stops, as this distance is reduced from 806m using the original algorithm to 530m after applying the suggested improvements.


      PubDate: 2016-06-15T13:10:40Z
       
  • Sequencing twin automated stacking cranes in a block at automated
           container terminal
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Zhi-Hua Hu, Jiuh-Biing Sheu, Jack Xunjie Luo
      In the considered automated container terminal (ACT) that is designed for Shanghai Yangsha Terminal, two automated stacking cranes (ASCs) are configured for each block and they interact with automated lifting vehicles (ALVs) at the two ends of a block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal’s shoreline are considered. To utilize the yard spaces, the twin ASCs are devised to share the same tracks installed at the two sides of a block, while interferences between the ASCs challenge the routing and sequencing operations. To isolate the control and simplify the coordination of the two ASCs, the interference between ASCs is formulated by analyzing the minimal temporal intervals between any two tasks. Three models are then established to sequence the container handling tasks under the minimization of the makespan. An exact algorithm and a genetic algorithm are designed to solve the problem. Numerical experiments show that the algorithms are competitive comparing to on-the-shelf solvers. Practical implications are investigated based on the formulations and experimental results. The managerial implications and technological aspects of applying the formulations and algorithms to practical situations to real-world ACTs are discussed.


      PubDate: 2016-06-15T13:10:40Z
       
  • Editorial Board/Copyright Information
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68




      PubDate: 2016-06-15T13:10:40Z
       
  • Integrated solution for anomalous driving detection based on
           BeiDou/GPS/IMU measurements
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Rui Sun, Ke Han, Jun Hu, Yanjun Wang, Minghua Hu, Washington Yotto Ochieng
      There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.


      PubDate: 2016-06-15T13:10:40Z
       
  • Transit signal priority accommodating conflicting requests under Connected
           Vehicles technology
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jia Hu, Byungkyu Brian Park, Young-Jae Lee
      In this research, a person-delay-based optimization method is proposed for an intelligent Transit Signal Priority (TSP) logic that resolves multiple conflicting TSP requests at an isolated intersection. This TSP with Connected Vehicles accommodating Conflicting Requests (TSPCV-CR) overcomes the challenge bore by the conventional “first come first serve” strategy and presents significant improvement on bus service performance. The feature of TSPCV-CR includes green time re-allocation, simultaneous multiple buses accommodation, and signal-transit coordination. These features help maximize the transit TSP service rate and minimize adverse effect on competing travel directions. The TSPCV-CR is also designed to be conditional. That is, TSP is granted only when the bus is behind schedule and the grant of TSP causes no extra total person delay. The optimization is formulated as a Binary Mixed Integer Linear Program (BMILP) which is solved by standard branch-and-bound routine. Minimizing per person delay is the objective of the optimization model. The logic developed in this research is evaluated using both analytical and microscopic traffic simulation approaches. Both analytical tests and simulation evaluations compared three scenarios: without TSP (NTSP), conventional TSP (CTSP), and TSP with Connected Vehicles that resolves Conflicting Requests (TSPCV-CR). The measures of effectiveness used include bus delay and total travel time of all travelers. The performance of TSPCV-CR is compared against conventional TSP (CTSP) under four congestion levels and three different conflicting scenarios. The results show that the TSPCV-CR greatly reduces bus delay at signalized intersection for all congestion levels and conflicting scenarios considered. Simulation based evaluation results show that the TSPCV-CR logic reduces average bus delay between 5% and 48% compared to the conventional TSP. The range of improvement corresponding to the four different v/c ratios tested, which are 0.5, 0.7, 0.9 and 1.0, respectively. No statistically significant negative effects are observed.


      PubDate: 2016-06-15T13:10:40Z
       
  • Evacuation planning for disaster responses: A stochastic programming
           framework
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Li Wang, Lixing Yang, Ziyou Gao, Shukai Li, Xuesong Zhou
      Some disasters such as earthquakes, floods and hurricanes may result in evacuation for people in an affected area. This paper focuses on finding the a priori evacuation plans by considering side constraints and scenario-based stochastic link travel times and capacities. Hence a stochastic programming framework is developed so as to provide a reorganization of the traffic routing for a disaster response. Considering the different preferences of decision-makers, three evaluation criteria are introduced to formulate the objective function. Crisp linear equivalents for different evacuation strategies are further deduced to simplify solution methodologies. A heuristic algorithm combining the Lagrangian relaxation-based approach with K-shortest path techniques is designed to solve the expected disutility model. The experimental results indicate that the algorithm can solve large-scale instances for the problem of interest efficiently and effectively.


      PubDate: 2016-06-15T13:10:40Z
       
  • Influence of priority taking and abstaining at single-lane roundabouts
           using cellular automata
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Nathan P. Belz, Lisa Aultman-Hall, James Montague
      Existing roundabout simulation models fail to consider all types of driver behavior which compromises their accuracy and ability to accurately evaluate roundabout performance. Further, these non-compliant driver behaviors, including priority taking and priority abstaining, are inconsistent with existing traffic flow theories. In this paper, a new cellular automata model, C.A.Rsim, is developed and calibrated with field data from five single-lane roundabouts in four northeastern states. Model results indicate that approximately 20% of the individuals in the driver population are inclined to priority taking and approximately 20% are inclined to priority abstaining behavior, though the observed levels of these types of behavior are naturally lower and vary with traffic volume. The model results also corroborate other research indicating that current models can overestimate capacity at higher circulating volumes, possibly a result of the jamming effect produced by priority taking behavior. The reduction in priority abstaining behavior, which is observed at older roundabouts, significantly reduces delay and queue length in certain traffic volumes. C.A.Rsim is also more parsimonious than many existing microsimulation models. These results provide insight on how variations in conflicting flow (i.e., traffic volume and turning movement balance) impact the amount of observed non-compliant behavior.


      PubDate: 2016-06-15T13:10:40Z
       
  • A double standard model for allocating limited emergency medical service
           vehicle resources ensuring service reliability
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Yi Liu, Zongzhi Li, Jingxian Liu, Harshingar Patel
      This paper introduces a new double standard model (DSM), along with a genetic algorithm (GA), for solving the emergency medical service (EMS) vehicle allocation problem that ensures acceptable service reliability with limited vehicle resources. Without loss of generality, the model is formulated to address emergency services to human injuries caused by vehicle crashes at intersections within an urban street network. The EMS fleet consists of basic life support (BLS) and advanced life support (ALS) vehicles suited for treating crashes with different severity levels within primary and secondary service coverage standards corresponding to extended response times. The model ensures that all demand sites are covered by at least one EMS vehicle within the secondary standard and a portion of which also meets the service reliability requirement. In addition, a portion of demand sites can be covered by at least one of each type of EMS vehicles within the primary standard. Meanwhile, it aims to achieve maximized coverage of demand sites within the primary standard that complies with the required service reliability. A computational experiment is conducted using 2004–2010 data on top two hundred high crash intersections in the city of Chicago as demand sites for model application. With an EMS fleet size of 15 BLS and 60 ALS ambulances maintained by the Chicago Fire Department, at best 92.4–95.5% of demand could be covered within the secondary standard at 90% of service reliability; and 65.5–68.4% of high severity demand and 50.2–54.5 low severity demand could be covered within the primary standard at 90% of service reliability. The model can help optimize EMS vehicle allocation in urban areas.


      PubDate: 2016-06-15T13:10:40Z
       
  • Integrated multi-track station layout design and train scheduling models
           on railway corridors
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Jianguo Qi, Lixing Yang, Yuan Gao, Shukai Li, Ziyou Gao
      The dwelling capacity of the station (mainly determined by its multi-track layout) is a practically significant factor to influence the quality of the train schedules, especially in a busy railway corridor with heterogeneous trains and complex operations. To improve the passing capacity and transportation efficiency, this paper focuses on a network design problem over a railway corridor, in which some critical stations are considered to enlarge the number of siding tracks or platforms within the budget constraints. To evaluate the quality of design strategies, the construction cost and total travel time in the corresponding optimal train schedule are adopted as evaluation indexes. Based on two specific modeling methodologies, two types of optimization models are particularly formulated with different considerations. One is a single-level linear mixed-integer programming (S-LMIP) model based on the space–time network representation method; the other is a bi-level programming model associated with the platform choice-based method, where the upper level of the proposed model aims to design new siding tracks/platforms in the candidate stations, and the lower level is a train scheduling model with assigning the tracks for each train at each station. The commercial software GAMS with CPLEX solver and local searching based heuristic with integrated CPLEX solver are respectively employed to solve the near-optimal solutions for these two types of models. Finally, two sets of examples, in which a sample railway corridor and the Wuhan–Guangzhou high-speed railway corridor are adopted as the experimental environments, are implemented to illustrate the performance and effectiveness of the proposed approaches.


      PubDate: 2016-06-15T13:10:40Z
       
  • Optimal planning of liquefied natural gas deliveries
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Sara Al-Haidous, Mohamed Kais Msakni, Mohamed Haouari
      We investigate the problem of designing an optimal annual delivery plan for Liquefied Natural Gas (LNG). This problem requires determining the long-term cargo delivery dates and the assignment of vessels to the cargoes while accommodating several constraints, including berth availability, liquefaction terminal inventory, planned maintenance, and bunkering requirements. We describe a novel mixed-integer programming formulation that captures important industry requirements and constraints with the objective of minimizing the vessel fleet size. A peculiar property of the proposed formulation is that it includes a polynomial number of variables and constraints and is, in our experience, computationally tractable for large problem instances using a commercial solver. Extensive computational runs demonstrate the efficacy of the proposed model for real instances provided by a major energy company that involve up to 118 cargoes and a 373-day planning horizon.


      PubDate: 2016-06-15T13:10:40Z
       
  • Modeling chain collisions in vehicular networks with variable penetration
           rates
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Daxin Tian, Jianshan Zhou, Yunpeng Wang, Zhengguo Sheng, Haiying Xia, Zhenguo Yi
      The vehicular ad hoc network has great potential in improving traffic safety. One of the most important and interesting issues in the research community is the safety evaluation with limited penetration rates of vehicles equipped with inter-vehicular communications. In this paper, a stochastic model is proposed for analyzing the vehicle chain collisions. It takes into account the influences of different penetration rates, the stochastic nature of inter-vehicular distance distribution, and the different kinematic parameters related to driver and vehicle. The usability and accuracy of this model is tested and proved by comparative experiments with Monte Carlo simulations. The collision outcomes of a platoon in different penetration rates and traffic scenarios are also analyzed based on this model. These results are useful to provide theoretical insights into the safety control of a heterogeneous platoon.


      PubDate: 2016-06-15T13:10:40Z
       
  • Online distributed cooperative model predictive control of energy-saving
           trajectory planning for multiple high-speed train movements
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Xihui Yan, Baigen Cai, Bin Ning, Wei ShangGuan
      The cooperative energy-efficient trajectory planning for multiple high-speed train movements is considered in this paper. We model all the high-speed trains as the agents that can communicate with others and propose a local trajectory planning control model using the Model Predictive Control (MPC) theory. After that we design an online distributed cooperative optimization algorithm for multiple train trajectories planning, under which each train agent can regulate the trajectory planning procedure to save energy using redundancy trip time through tuning ACO’s heuristic information parameter. Compared to the existing literature, the vital distinctions of our work lies not only on the online cooperative trajectory planning but also on the distributed mechanism for multiple high-speed trains. Experimental studies are given to illustrate the effectiveness of the proposed methods with the practical operational data of Wuhan-Guangzhou High-speed Railway in China.


      PubDate: 2016-06-15T13:10:40Z
       
  • Modeling duration choice in space–time multi-state supernetworks for
           individual activity-travel scheduling
    • Abstract: Publication date: August 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 69
      Author(s): Feixiong Liao
      Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured.


      PubDate: 2016-06-15T13:10:40Z
       
  • A joint optimization model for liner container cargo assignment problem
           using state-augmented shipping network framework
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Hua Wang, Xiaoning Zhang, Shuaian Wang
      This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, we develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, we take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.


      PubDate: 2016-05-17T03:59:28Z
       
  • Distributed model predictive control for railway traffic management
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Bart Kersbergen, Ton van den Boom, Bart De Schutter
      Every day small delays occur in almost all railway networks. Such small delays are often called “disturbances” in literature. In order to deal with disturbances dispatchers reschedule and reroute trains, or break connections. We call this the railway management problem. In this paper we describe how the railway management problem can be solved using centralized model predictive control (MPC) and we propose several distributed model predictive control (DMPC) methods to solve the railway management problem for entire (national) railway networks. Furthermore, we propose an optimization method to determine a good partitioning of the network in an arbitrary number of sub-networks that is used for the DMPC methods. The DMPC methods are extensively tested in a case study using a model of the Dutch railway network and the trains of the Nederlandse Spoorwegen. From the case study it is clear that the DMPC methods can solve the railway traffic management problem, with the same reduction in delays, much faster than the centralized MPC method.


      PubDate: 2016-05-17T03:59:28Z
       
  • Path-constrained traffic assignment: A trip chain analysis under range
           anxiety
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Tong-Gen Wang, Chi Xie, Jun Xie, Travis Waller
      This paper proposes and analyzes a distance-constrained traffic assignment problem with trip chains embedded in equilibrium network flows. The purpose of studying this problem is to develop an appropriate modeling tool for characterizing traffic flow patterns in emerging transportation networks that serve a massive adoption of plug-in electric vehicles. This need arises from the facts that electric vehicles suffer from the “range anxiety” issue caused by the unavailability or insufficiency of public electricity-charging infrastructures and the far-below-expectation battery capacity. It is suggested that if range anxiety makes any impact on travel behaviors, it more likely occurs on the trip chain level rather than the trip level, where a trip chain here is defined as a series of trips between two possible charging opportunities (Tamor et al., 2013). The focus of this paper is thus given to the development of the modeling and solution methods for the proposed traffic assignment problem. In this modeling paradigm, given that trip chains are the basic modeling unit for individual decision making, any traveler’s combined travel route and activity location choices under the distance limit results in a distance-constrained, node-sequenced shortest path problem. A cascading labeling algorithm is developed for this shortest path problem and embedded into a linear approximation framework for equilibrium network solutions. The numerical result derived from an illustrative example clearly shows the mechanism and magnitude of the distance limit and trip chain settings in reshaping network flows from the simple case characterized merely by user equilibrium.


      PubDate: 2016-05-17T03:59:28Z
       
  • Modeling the impacts of mandatory and discretionary lane-changing
           maneuvers
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): T.L. Pan, William H.K. Lam, A. Sumalee, R.X. Zhong
      In this paper, a novel mesoscopic multilane model is proposed to enable simultaneous simulation of mandatory and discretionary lane-changing behaviors to realistically capture multilane traffic dynamics. The model considers lane specific fundamental diagrams to simulate dynamic heterogeneous lane flow distributions on expressways. Moreover, different priority levels are identified according to different lane-changing motivations and the corresponding levels of urgency. Then, an algorithm is proposed to estimate the dynamic mandatory and discretionary lane-changing demands. Finally, the lane flow propagation is defined by the reaction law of the demand–supply functions, which can be regarded as an extension of the Incremental-Transfer and/or Priority Incremental-Transfer principles. The proposed mesoscopic multilane cell transmission model is calibrated and validated on a complex weaving section of the State Route 241 freeway in Orange County, California, showing both the positive and negative impact of lane changing maneuvers, e.g., balancing effect and capacity drop, respectively. Moreover, the empirical study verifies that the model requires no additional data other than the cell transmission model does. Thus, the proposed model can be deployed as a simple simulation tool for accessing dynamic mesoscopic multilane traffic state from data available to most management centers, and also the potential application in predicting the impact of traffic incident or lane control strategy.


      PubDate: 2016-05-11T10:37:50Z
       
  • A general corridor model for designing plug-in electric vehicle charging
           infrastructure to support intercity travel
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Mehrnaz Ghamami, Ali Zockaie, Yu (Marco) Nie
      This paper proposes to optimally configure plug-in electric vehicle (PEV) charging infrastructure for supporting long-distance intercity travel using a general corridor model that aims to minimize a total system cost inclusive of infrastructure investment, battery cost and user cost. Compared to the previous work, the proposed model not only allows realistic patterns of origin–destination demands, but also considers flow-dependent charging delay induced by congestion at charging stations. With these extensions, the model is better suited to performing a sketchy design of charging infrastructure along highway corridors. The proposed model is formulated as a mixed integer program with nonlinear constraints and solved by a specialized metaheuristic algorithm based on Simulated Annealing. Our numerical experiments show that the metaheuristic produces satisfactory solutions in comparison with benchmark solutions obtained by a mainstream commercial solver, but is more computationally tractable for larger problems. Noteworthy findings from numerical results are: (1) ignoring queuing delay inducted by charging congestion could lead to suboptimal configuration of charging infrastructure, and its effect is expected to be more significant when the market share of PEVs rises; (2) in the absence of the battery cost, it is important to consider the trade-off between the costs of charging delay and the infrastructure; and (3) building long-range PEVs with the current generation of battery technology may not be cost effective from the societal point of view.


      PubDate: 2016-05-11T10:37:50Z
       
  • A novel network approach to study communication activities of air traffic
           controllers
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Yanjun Wang, Jian Bu, Ke Han, Rui Sun, Minghua Hu, Chenping Zhu
      Air traffic controllers play critical roles in the safety, efficiency, and capacity of air traffic management. However, there is inadequate knowledge of the dynamics of the controllers’ activities, especially from a quantitative perspective. This paper presents a novel network approach to uncover hidden patterns of the controllers’ behavior based on the voice communication data. We convert the time series of the controllers’ communication activities, which contain flights’ information, into a time-varying network and a static network, referred to as temporal network and time-aggregated network, respectively. These networks reflect the interaction between the controllers and the flights on a sector level, and allow us to leverage network techniques to yield new and insightful findings regarding regular patterns and unique characteristics of the controllers’ communication activities. The proposed methodology is applied to three real-world datasets, and the resulting networks are closely examined and compared in terms of degree distribution, community structure, and motifs. This network approach introduces a “spatial” element to the conventional analysis of the controllers’ communication events, by identifying connectivity and proximity among flights. It constitutes a major step towards the quantitative description of the controller-flight dynamics, which is not widely seen in the literature.


      PubDate: 2016-05-11T10:37:50Z
       
  • Modeling railway disruption lengths with Copula Bayesian Networks
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Aurelius A. Zilko, Dorota Kurowicka, Rob M.P. Goverde
      Decreasing the uncertainty in the lengths of railway disruptions is a major help to disruption management. To assist the Dutch Operational Control Center Rail (OCCR) during disruptions, we propose the Copula Bayesian Network method to construct a disruption length prediction model. Computational efficiency and fast inference features make the method attractive for the OCCR’s real-time decision making environment. The method considers the factors influencing the length of a disruption and models the dependence between them to produce a prediction. As an illustration, a model for track circuit (TC) disruptions in the Dutch railway network is presented in this paper. Factors influencing the TC disruption length are considered and a disruption length model is constructed. We show that the resulting model’s prediction power is sound and discuss its real-life use and challenges to be tackled in practice.


      PubDate: 2016-04-29T23:25:05Z
       
  • Network sensor health problem
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Zhe Sun, Wen-Long Jin, ManWo Ng
      Many existing studies on the sensor health problem determine an individual sensor’s health status based on the statistical characteristics of collected data by the sensor. In this research, we study the sensor health problem at the network level, which is referred to as the network sensor health problem. First, based on the conservation principle of daily flows in a network, we separate all links into base links and non-base links, such that the flows on the latter can be calculated from those on the former. In reality, the network flow conservation principle can be violated due to the existence of unhealthy sensors. Then we define the least inconsistent base set of links as those that minimize the sum of squares of the differences between observed and calculated flows on non-base links. But such least inconsistent base sets may not be unique in a general road network. Finally we define the health index of an individual sensor as the frequency that it appears in all of the least inconsistent base sets. Intuitively, a lower health index suggests that the corresponding sensor is more likely to be unhealthy. We present the brute force method to find all least inconsistent base sets and calculate the health indices. We also propose a greedy search algorithm to calculate the approximate health indices more efficiently. We solve the network sensor health problem for a real-world example with 16 nodes and 30 links, among which 18 links are monitored with loop detectors. Using daily traffic count data from the Caltrans Performance Measurement System (PeMS) database, we use both the brute-force and greedy search methods to calculate the health indices for all the sensors. We find that all the four sensors flagged as unhealthy (high value) by PeMS have the lowest health indices. This confirms that a sensor with a lower health index is more likely to be unhealthy. Therefore, we can use such health indices to determine the relative reliability of different sensors’ data and prioritize the maintenance of sensors.


      PubDate: 2016-04-29T23:25:05Z
       
  • A global optimization algorithm for trajectory data based car-following
           model calibration
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Li Li, Xiqun (Micheal) Chen, Lei Zhang
      How to calibrate the parameters of car-following models based on observed traffic data is a vital problem in traffic simulation. Usually, the core of calibration is cast into an optimization problem, in which the decision variables are car-following model parameters and the objective function usually characterizes the difference between empirical vehicle movements and their simulated correspondences. Since the objective function is usually nonlinear and non-convex, various greedy or stochastic algorithms had been proposed during the last two decades. However, the performance of these algorithms remains to be further examined. In this paper, we revisit this important problem with a special focus on the geometric feature of the objective function. First, we prove that, from a global perspective, most existing objective functions are Lipschitz continuous. Second, we show that, from a local perspective, many of these objective functions are relatively flat around the global optimal solution. Based on these two features, we propose a new global optimization algorithm that integrates global direct search and local gradient search to find the optimal solution in an efficient manner. We compare this new algorithm with several existing algorithms, including Nelder–Mead (NM) algorithm, sequential quadratic programming (SQP) algorithm, genetic algorithm (GA), and simultaneous perturbation stochastic approximation (SPSA) algorithm, on NGSIM trajectory datasets. Results demonstrate that the proposed algorithm has a fast convergence speed and a high probability of finding the global optimal solution. Moreover, it has only two major configuration parameters that can be easily determined in practice.


      PubDate: 2016-04-29T23:25:05Z
       
  • Dynamics of modal choice of heterogeneous travelers with responsive
           transit services
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Xinwei Li, Hai Yang
      In this paper, we investigate travelers’ day-to-day modal choice in a bi-modal transportation system with responsive transit services under various economic objectives. A group of travelers with heterogeneous preferences adjust their modal choice each day based on their perceived travel cost of each mode, aiming to minimize their travel cost. Meanwhile, the transit operator sets frequency each period according to the realized transit demand and previous frequency, trying to achieve different profit targets. For a given profit target, the fixed point of equilibrium may not be unique. We establish the condition for existence of multiple fixed points and examine the stability of the fixed points in each case. Furthermore, in view of a socially desirable mode choice, we also investigate the impacts of total travel demand and bus size on the convergence of the system to various fixed points associated with different targeted mode split. Finally, we use several numerical examples to illustrate the theoretical results and their practical implications for the transit operator to design appropriate transit schemes in a dynamic transportation environment.


      PubDate: 2016-04-29T23:25:05Z
       
  • A unified-adaptive large neighborhood search metaheuristic for periodic
           location-routing problems
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Çağrı Koç
      This paper introduces three variants of the Periodic Location-Routing Problem (PLRP): the Heterogeneous PLRP with Time Windows (HPTW), the Heterogeneous PLRP (HP) and the homogeneous PLRP with Time Windows (PTW). These problems extend the well-known location-routing problem by considering a homogeneous or heterogeneous fleet, multiple periods and time windows. The paper develops a powerful Unified-Adaptive Large Neighborhood Search (U-ALNS) metaheuristic for these problems. The U-ALNS successfully uses existing algorithmic procedures and also offers a number of new advanced efficient procedures capable of handling a multi-period horizon, fleet composition and location decisions. Computational experiments on benchmark instances show that the U-ALNS is highly effective on PLRPs. The U-ALNS outperforms previous methods on a set of standard benchmark instances for the PLRP. We also present new benchmark results for the PLRP, HPTW, HP and PTW.


      PubDate: 2016-04-24T22:12:26Z
       
  • The promises of big data and small data for travel behavior (aka human
           mobility) analysis
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Cynthia Chen, Jingtao Ma, Yusak Susilo, Yu Liu, Menglin Wang
      The last decade has witnessed very active development in two broad, but separate fields, both involving understanding and modeling of how individuals move in time and space (hereafter called “travel behavior analysis” or “human mobility analysis”). One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists. Researchers in these two fields work with different datasets, apply different methodologies, and answer different but overlapping questions. It is our view that there is much, hidden synergy between the two fields that needs to be brought out. It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations between the two. It is our hope that this paper will stimulate many future cross-cutting studies that involve researchers from both fields.


      PubDate: 2016-04-24T22:12:26Z
       
  • Integrated optimal eco-driving on rolling terrain for hybrid electric
           vehicle with vehicle-infrastructure communication
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Jia Hu, Yunli Shao, Zongxuan Sun, Meng Wang, Joe Bared, Peter Huang
      This research presents an integrated optimal controller to maximize the fuel efficiency of a Hybrid Electric Vehicle (HEV) traveling on rolling terrain. The controller optimizes both the vehicle acceleration and the hybrid powertrain operation. It takes advantage of the emerging Connected Vehicle (CV) technology and utilizes present and future information as optimization input, which includes road topography, and dynamic speed limit. The optimal control problem was solved using Pontryagin’s Minimum Principle (PMP). Efforts were made to reduce the computational burden of the optimization process. The evaluation shows that the benefit of the proposed optimal controller is significant compared to regular HEV cruising at the speed limit on rolling terrain. The benefit ranges from 5.0% to 8.9% on mild slopes and from 15.7% to 16.9% on steep slopes. The variation is caused by the change of hilly road density.


      PubDate: 2016-04-20T05:50:20Z
       
  • Platoon based cooperative driving model with consideration of realistic
           inter-vehicle communication
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Dongyao Jia, Dong Ngoduy
      Recent developments of information and communication technologies (ICT) have enabled vehicles to timely communicate with each other through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Nevertheless, unreliable vehicular communications also introduce packet loss and transmission delay when vehicular kinetic information or control commands are disseminated among vehicles, which brings more challenges in the system modeling and optimization. Currently, no data has been yet available for the calibration and validation of a model for ITS, and most research has been only conducted for a theoretical point of view. Along this line, this paper focuses on the (theoretical) development of a more general (microscopic) traffic model which enables the cooperative driving behavior via a so-called inter-vehicle communication (IVC). To this end, we design a consensus-based controller for the cooperative driving system (CDS) considering (intelligent) traffic flow that consists of many platoons moving together. More specifically, the IEEE 802.11p, the de facto vehicular networking standard required to support ITS applications, is selected as the IVC protocols of the CDS, in order to investigate how the vehicular communications affect the features of intelligent traffic flow. This study essentially explores the relationship between IVC and cooperative driving, which can be exploited as the reference for the CDS optimization and design.


      PubDate: 2016-04-20T05:50:20Z
       
  • Prediction of vehicle CO2 emission and its application to eco-routing
           navigation
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Weiliang Zeng, Tomio Miwa, Takayuki Morikawa
      Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO2 emission per kilometer and determine an eco-friendly path that results in minimum CO2 emissions while satisfying travel time budget. The vehicle CO2 emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO2 emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO2 emission. Specifically, the benefit trade-off between CO2 emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO2 emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.
      Graphical abstract image

      PubDate: 2016-04-14T18:40:00Z
       
  • Extracting accurate location information from a highly inaccurate traffic
           accident dataset: A methodology based on a string matching technique
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Mario Miler, Filip Todić, Marko Ševrović
      The objective of this research was to develop a model for validating traffic accident locations that would be applicable worldwide, regardless of linguistic or cultural differences. In order to achieve this, a Volunteered Geographic Information (VGI) dataset was used, the OpenStreetMap (OSM) project. To test the developed model, a total of 8550 accidents with fatal or non-fatal injuries that occurred in the City of Zagreb from 2010 to 2014 were evaluated. Traffic accident data was collected using the pen-and-paper method while the traffic accident locations were determined using Global Positioning System (GPS) receivers embedded within police vehicles. This form of data entry invariably introduces errors in both geometric and contextual attributes. To fully counteract these errors, the developed model consists of two key concepts: the Jaro–Winkler string matching technique and the Inverse Distance Weighting method. Over 66% of traffic accident locations were validated, which is an increase of 15% when compared to the classical approach. The model outlined in this paper shows a significant improvement in estimating the correct location of traffic accidents. This in turn results in a drastic decrease in resources needed to estimate the quality of accident locations.


      PubDate: 2016-04-14T18:40:00Z
       
  • Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication
           in a heterogeneous wireless network – Performance evaluation
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Kakan Chandra Dey, Anjan Rayamajhi, Mashrur Chowdhury, Parth Bhavsar, James Martin
      Connected Vehicle Technology (CVT) requires wireless data transmission between vehicles (V2V), and vehicle-to-infrastructure (V2I). Evaluating the performance of different network options for V2V and V2I communication that ensure optimal utilization of resources is a prerequisite when designing and developing robust wireless networks for CVT applications. Though dedicated short range communication (DSRC) has been considered as the primary communication option for CVT safety applications, the use of other wireless technologies (e.g., Wi-Fi, LTE, WiMAX) allow longer range communications and throughput requirements that could not be supported by DSRC alone. Further, the use of other wireless technology potentially reduces the need for costly DSRC infrastructure. In this research, the authors evaluated the performance of Het-Net consisting of Wi-Fi, DSRC and LTE technologies for V2V and V2I communications. An application layer handoff method was developed to enable Het-Net communication for two CVT applications: traffic data collection, and forward collision warning. The handoff method ensures the optimal utilization of available communication options (i.e., eliminate the need of using multiple communication options at the same time) and corresponding backhaul communication infrastructure depending on the connected vehicle application requirements. Field studies conducted in this research demonstrated that the use of Het-Net broadened the range and coverage of V2V and V2I communications. The use of the application layer handoff technique to maintain seamless connectivity for CVT applications was also successfully demonstrated and can be adopted in future Het-Net supported connected vehicle applications. A long handoff time was observed when the application switches from LTE to Wi-Fi. The delay is largely due to the time required to activate the 802.11 link and the time required for the vehicle to associate with the RSU (i.e., access point). Modifying the application to implement a soft handoff where a new network is seamlessly connected before breaking from the existing network can greatly reduce (or eliminate) the interruption of network service observed by the application. However, the use of a Het-Net did not compromise the performance of the traffic data collection application as this application does not require very low latency, unlike connected vehicle safety applications. Field tests revealed that the handoff between networks in Het-Net required several seconds (i.e., higher than 200ms required for safety applications). Thus, Het-Net could not be used to support safety applications that require communication latency less than 200ms. However, Het-Net could provide additional/supplementary connectivity for safety applications to warn vehicles upstream to take proactive actions to avoid problem locations. To validate and establish the findings from field tests that included a limited number of connected vehicles, ns-3 simulation experiments with a larger number of connected vehicles were conducted involving a DSRC and LTE Het-Net scenario. The latency and packet delivery error trend obtained from ns-3 simulation were found to be similar to the field experiment results.


      PubDate: 2016-04-14T18:40:00Z
       
  • Using GPS data to analyse the distance travelled to the first accident at
           fault in pay-as-you-drive insurance
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Mercedes Ayuso, Montserrat Guillén, Ana María Pérez Marín
      In this paper we employ survival analysis methods to analyse the impact of driving patterns on distance travelled before a first claim is made by young drivers underwriting a pay-as-you-drive insurance scheme. An empirical application is presented in which we analyse real data collected by a GPS system from a leading Spanish insurer. We show that men have riskier driving patterns than women and, moreover, that there are gender differences in the impact driving patterns have on the risk of being involved in an accident. The implications of these results are discussed in terms of the ‘no-gender’ discrimination regulation.


      PubDate: 2016-04-14T18:40:00Z
       
  • Online calibration for microscopic traffic simulation and dynamic
           multi-step prediction of traffic speed
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Vasileia Papathanasopoulou, Ioulia Markou, Constantinos Antoniou
      Simulating driving behavior in high accuracy allows short-term prediction of traffic parameters, such as speeds and travel times, which are basic components of Advanced Traveler Information Systems (ATIS). Models with static parameters are often unable to respond to varying traffic conditions and simulate effectively the corresponding driving behavior. It has therefore been widely accepted that the model parameters vary in multiple dimensions, including across individual drivers, but also spatially across the network and temporally. While typically on-line, predictive models are macroscopic or mesoscopic, due to computational and data considerations, nowadays microscopic models are becoming increasingly practical for dynamic applications. In this research, we develop a methodology for online calibration of microscopic traffic simulation models for dynamic multi-step prediction of traffic measures, and apply it to car-following models, one of the key models in microscopic traffic simulation models. The methodology is illustrated using real trajectory data available from an experiment conducted in Naples, using a well-established car-following model. The performance of the application with the dynamic model parameters consistently outperforms the corresponding static calibrated model in all cases, and leads to less than 10% error in speed prediction even for ten steps into the future, in all considered data-sets.


      PubDate: 2016-04-14T18:40:00Z
       
  • A cell transmission model for dynamic lane reversal with autonomous
           vehicles
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Michael W. Levin, Stephen D. Boyles
      Autonomous vehicles admit consideration of novel traffic behaviors such as reservation-based intersection controls and dynamic lane reversal. We present a cell transmission model formulation for dynamic lane reversal. For deterministic demand, we formulate the dynamic lane reversal control problem for a single link as an integer program and derive theoretical results. In reality, demand is not known perfectly at arbitrary times in the future. To address stochastic demand, we present a Markov decision process formulation. Due to the large state size, the Markov decision process is intractable. However, based on theoretical results from the integer program, we derive an effective heuristic. We demonstrate significant improvements over a fixed lane configuration both on a single bottleneck link with varying demands, and on the downtown Austin network.


      PubDate: 2016-04-14T18:40:00Z
       
  • Infrastructure planning for fast charging stations in a competitive market
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Zhaomiao Guo, Julio Deride, Yueyue Fan
      Most existing studies on EV charging infrastructure planning take a central planner’s perspective, by assuming that investment decision on charging facilities can be controlled by a single decision entity. In this paper, we establish modeling and computational methods to support business-driven EV charging infrastructure investment planning problem, where the infrastructure system is shaped by collective actions of multiple decision entities who do not necessarily coordinate with each other. A network-based multi-agent optimization modeling framework is developed to simultaneously capture the selfish behaviors of individual investors and travelers and their interactions over a network structure. To overcome computational difficulty imposed by non-convexity of the problem, we rely on recent theoretical development on variational convergence of bivariate functions to design a solution algorithm with analysis on its convergence properties. Numerical experiments are implemented to study the performance of proposed method and draw practical insights.


      PubDate: 2016-04-14T18:40:00Z
       
  • Combining speed and acceleration to define car users’ safe or unsafe
           driving behaviour
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Laura Eboli, Gabriella Mazzulla, Giuseppe Pungillo
      Speed and acceleration describe the motion of a vehicle. Therefore, these parameters are fundamental to define the behaviour of a driver. To this aim, it is useful to analyse instantaneous and geo-referenced kinematic parameters of the vehicle recorded by real tests on the road. Among all the available methods in the scientific literature, a way for characterizing driver behaviour is the g–g diagram, that shows the longitudinal and lateral accelerations on the y and x-axes, normalized with respect to gravity, recorded on a vehicle during a real test on the road. However, we retain that also speed has to be considered for characterizing drivers’ behaviour, being acceleration and speed strictly interrelated. Starting from the g–g diagram, we propose a methodology which describes the relationship between lateral and longitudinal accelerations and speeds, and represents a tool to classify car drivers’ behaviour as safe or unsafe. An app for smartphone allows the geo-referenced kinematic parameters of the vehicle to be detected. The experimental survey supporting the methodology was carried out on a rural two-lane road in Southern Italy.


      PubDate: 2016-04-14T18:40:00Z
       
  • Management of intersections with multi-modal high-resolution data
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Ajith Muralidharan, Samuel Coogan, Christopher Flores, Pravin Varaiya
      A high-resolution (HR) data system for an intersection collects the location (lane), speed, and turn movement of every vehicle as it enters an intersection, together with the signal phase. Some systems also provide video monitoring; others measure pedestrian and bicycle movements; and some have vehicle to infrastructure (V2I) communication capability. The data are available in real time and archived. Real time data are used to implement signal control. Archived data are used to evaluate intersection, corridor, and network performance. The system operates 24 × 7 . Uses of a HR data system for assessing intersection performance and improving mobility and safety are discussed. Mobility applications include evaluation of intersection performance, and the design of better signal control. Safety applications include estimates of dilemma zones, red-light violations, and pedestrian–vehicle conflicts.


      PubDate: 2016-04-09T09:26:26Z
       
  • Development of distress condition index of asphalt pavements using LTPP
           data through structural equation modeling
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Xueqin Chen, Qiao Dong, Hehua Zhu, Baoshan Huang
      Traditional pavement distress index such as the Pavement Condition Index (PCI) developed by U.S. Army Corps of Engineers determines coefficients of distresses based on subjective ratings. This study proposed an asphalt pavement distress condition index based on various types of distress data collected from the Long-Term Pavement Performance (LTPP) database through Structural Equation Modeling (SEM). The SEM method treated the overall distress index as a latent variable while various distresses were treated as endogenous and other influence factors such as age, layer thickness, material type, weather, environment and traffic, were exogenous observed variables. The SEM method modeled the contributions of various distresses as well as the influence of other factors on the overall pavement distress condition. Influences of age, layer thickness, material type, environment and traffic on the latent distress condition were in accordance with previous studies. Compared with previous attempts to model latent pavement condition index utilizing SEM method, more pavement condition measurements and influencing factors were included. Specifically, this study adopted the robust maximum likelihood estimator (MLR) to estimate parameters for non-normally distributed data and derived the explicit expression of latent variables with intercepts. A multiple regression prediction model was built to calculate an overall condition index utilizing those measured distress data. The established pavement distress index prediction model provided a rational estimation of weighting coefficients for each distress type. The prediction model showed that alligator cracking, longitudinal cracking in wheel path, non-wheel path longitudinal cracking, transverse cracking, block cracking, edge cracking, patch and bleeding were significant for the latent pavement distress index.


      PubDate: 2016-04-09T09:26:26Z
       
  • Delivering improved alerts, warnings, and control assistance using basic
           safety messages transmitted between connected vehicles
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Jun Liu, Asad J. Khattak
      When vehicles share their status information with other vehicles or the infrastructure, driving actions can be planned better, hazards can be identified sooner, and safer responses to hazards are possible. The Safety Pilot Model Deployment (SPMD) is underway in Ann Arbor, Michigan; the purpose is to demonstrate connected technologies in a real-world environment. The core data transmitted through Vehicle-to-Vehicle and Vehicle-to-Infrastructure (or V2V and V2I) applications are called Basic Safety Messages (BSMs), which are transmitted typically at a frequency of 10Hz. BSMs describe a vehicle’s position (latitude, longitude, and elevation) and motion (heading, speed, and acceleration). This study proposes a data analytic methodology to extract critical information from raw BSM data available from SPMD. A total of 968,522 records of basic safety messages, gathered from 155 trips made by 49 vehicles, was analyzed. The information extracted from BSM data captured extreme driving events such as hard accelerations and braking. This information can be provided to drivers, giving them instantaneous feedback about dangers in surrounding roadway environments; it can also provide control assistance. While extracting critical information from BSMs, this study offers a fundamental understanding of instantaneous driving decisions. Longitudinal and lateral accelerations included in BSMs were specifically investigated. Varying distributions of instantaneous longitudinal and lateral accelerations are quantified. Based on the distributions, the study created a framework for generating alerts/warnings, and control assistance from extreme events, transmittable through V2V and V2I applications. Models were estimated to untangle the correlates of extreme events. The implications of the findings and applications to connected vehicles are discussed in this paper.


      PubDate: 2016-04-09T09:26:26Z
       
  • Mobility and environment improvement of signalized networks through
           Vehicle-to-Infrastructure (V2I) communications
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Gerard Aguilar Ubiergo, Wen-Long Jin
      Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned, and tons of toxic pollutants released to the atmosphere each year by idling engines. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with communication and computing devices. In this paper, we first presented an integrated simulator with V2I, a car-following model and an emission model to simulate the behavior of vehicles at signalized intersections and calculate travel delays in queues, vehicle emissions, and fuel consumption. We then present a hierarchical green driving strategy based on feedback control to smooth stop-and-go traffic in signalized networks, where signals can disseminate traffic signal information and loop detector data to connected vehicles through V2I communications. In this strategy, the control variable is an individual advisory speed limit for each equipped vehicle, which is calculated from its location, signal settings, and traffic conditions. Finally, we quantify the mobility and environment improvements of the green driving strategy with respect to market penetration rates of equipped vehicles, traffic conditions, communication characteristics, location accuracy, and the car-following model itself, both in isolated and non-isolated intersections. In particular, we demonstrate savings of around 15% in travel delays and around 8% in fuel consumption and greenhouse gas emissions. Different from many existing ecodriving strategies in signalized road networks, where vehicles’ speed profiles are totally controlled, our strategy is hierarchical, since only the speed limit is provided, and vehicles still have to follow their leaders. Such a strategy is crucial for maintaining safety with mixed vehicles.


      PubDate: 2016-04-09T09:26:26Z
       
  • An integrated approach for airline scheduling, aircraft fleeting and
           routing with cruise speed control
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Hüseyin Gürkan, Sinan Gürel, M. Selim Aktürk
      To place an emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers’ connection service levels are ensured via chance constraints. We propose a nonlinear mixed integer programming model due to the nonlinear fuel consumption and CO2 emission cost terms in the objective function, which is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of fuel efficient aircraft and even to decrease total number of aircraft needed while satisfying the same service level and maintenance requirements for aircraft fleeting and routing. There is a critical tradeoff between the number of aircraft needed to fulfill the required flights and overall operational expenses. We also propose two heuristic methods to solve larger size problems. Finally, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods.


      PubDate: 2016-04-05T03:25:38Z
       
  • Integration of Weigh-in-Motion (WIM) and inductive signature data for
           truck body classification
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Sarah V. Hernandez, Andre Tok, Stephen G. Ritchie
      Transportation agencies tasked with forecasting freight movements, creating and evaluating policy to mitigate transportation impacts on infrastructure and air quality, and furnishing the data necessary for performance driven investment depend on quality, detailed, and ubiquitous vehicle data. Unfortunately in the US, currently available commercial vehicle data contain critical gaps when it comes to linking vehicle and operational characteristics. Leveraging existing traffic sensor infrastructure, we developed a novel, readily implementable approach of integrating two complementary data collection devices, Weigh-in-Motion (WIM) systems and advanced inductive loop detectors (ILD), to produce high resolution truck data. For each vehicle traversing a WIM site, an inductive signature was collected along with WIM measurements such as axle spacing and weight which were then used as inputs to a series of truck body classification models that encompass all truck classes in the most common axle-based Federal Highway Administration (FHWA) classification scheme in the US. Since body configuration can be linked to commodity carried, drive and duty cycle, and other distinct operating characteristics, body class data is undeniably useful for freight planning and air quality monitoring. A multiple classifier systems (MCS) method was adopted to increase the classification accuracy for minority body classes. In all, eight separate body classifications models were developed from an extensive data set of 18,967 truck records distinguishing an unprecedented total of 23 single unit truck and 31 single and semi-trailer body configurations, each with over 80% correct classification rates (CCR). Remarkably, the body class model for five axle semi-tractor trailers – the most diverse truck category – achieved MCS CCRs above 85% for several industry specific classes including refrigerated and non-refrigerated intermodal containers, livestock, and logging trailers.


      PubDate: 2016-03-31T05:09:49Z
       
  • Experiment of boundedly rational route choice behavior and the model under
           satisficing rule
    • Abstract: Publication date: July 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 68
      Author(s): Chuan-Lin Zhao, Hai-Jun Huang
      In this paper, we study the boundedly rational route choice behavior under the Simon’s satisficing rule. A laboratory experiment was carried out to verify the participants’ boundedly rational route choice behavior. By introducing the concept of aspiration level which is specific to each person, we develop a novel model of the problem in a parallel-link network and investigate the properties of the boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Extensions to general networks are conducted. Numerical examples are presented to demonstrate the theoretical analyses.


      PubDate: 2016-03-31T05:09:49Z
       
 
 
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