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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 (30 journals)
    - TRANSPORTATION (95 journals)

TRANSPORTATION (95 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 75)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 2)
Archives of Transport     Open Access   (Followers: 16)
Botswana Journal of Technology     Full-text available via subscription  
Case Studies on Transport Policy     Hybrid Journal   (Followers: 7)
Cities in the 21st Century     Open Access   (Followers: 13)
Economics of Transportation     Partially Free   (Followers: 12)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 9)
European Transport Research Review     Open Access   (Followers: 21)
Geosystem Engineering     Hybrid Journal   (Followers: 1)
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: 7)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 7)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 1)
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: 2)
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: 10)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 10)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 14)
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: 5)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 168)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 8)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 1)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 6)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 10)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
Journal of Transport History     Full-text available via subscription   (Followers: 15)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 8)
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   (Followers: 2)
Logistique & Management     Full-text available via subscription  
Modern Transportation     Open Access   (Followers: 10)
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: 2)
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: 12)
Public Transport     Hybrid Journal   (Followers: 17)
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   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 11)
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: 4)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
Transport Problems     Open Access   (Followers: 1)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 9)
Transportation     Hybrid Journal   (Followers: 27)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 12)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 31)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 20)
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: 4)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
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: 26)
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: 2.062]   [H-I: 72]   [20 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0968-090X
   Published by Elsevier Homepage  [3038 journals]
  • Algorithms to find shortest and alternative paths in free flow and
           congested traffic regimes
    • Authors: Alberto Faro; Daniela Giordano
      Pages: 1 - 29
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Alberto Faro, Daniela Giordano
      Location-based systems can be very helpful to mobile users if they are able to suggest shortest paths to destination taking into account the actual traffic conditions. This would allow to inform the drivers not only about the current shortest paths to destination but also about alternative, timely computed paths to avoid being trapped in the traffic jams signaled by cyber-physical-social systems. To this aim, the paper proposes a set of algorithms that solve very fast the All Pair Shortest Paths problem in both the free flow and congested traffic regimes, for road networks of medium-large size, thus enabling location-based systems to deal with emergencies and critical traffic conditions in city and metropolitan areas, whose transport networks typically range from some hundreds to many thousands of nodes, respectively. The paths to avoid being trapped in the traffic jams are computed by using a simulation of the shockwave propagation, instead of historical data. A parallel version of the algorithms is also proposed to solve the All Pair Shortest Paths problem for metropolitan areas with very large road networks. A time performance analysis of the proposed algorithms for transport networks of various size is carried out.

      PubDate: 2016-10-21T18:03:15Z
      DOI: 10.1016/j.trc.2016.09.009
      Issue No: Vol. 73 (2016)
  • Information-traffic coupled cell transmission model for information
           spreading dynamics over vehicular ad hoc network on road segments
    • Authors: Lili Du; Siyuan Gong; Lu Wang; Xiang-Yang Li
      Pages: 30 - 48
      Abstract: Publication date: December 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 73
      Author(s): Lili Du, Siyuan Gong, Lu Wang, Xiang-Yang Li
      Vehicular Ad Hoc Network (VANET) makes real-time traffic information accessible to vehicles en routes, thus possesses a great potential to improve traffic safety and mobility in the near future. Existing literature shows that we are still lack of approaches to track information spreading dynamics via VANET, which will prevent the potential applications from success. Motivated by this view, this research develops an information-traffic coupled cell transmission model (IT-CTM) to capture information spreading dynamics via VANET. More exactly, this study considers information spreading over a road segment forms a wave with a front and tail, each of which goes through the road segment following an intermittent transmission pattern due to traffic flow dynamics. The approach of IT-CTM discretizes a road segment into a number of cells. Each cell covers several intermittent transmissions. Mathematical methods are developed to capture the inner-cell and inter-cell movements of information front and tail, which enable us to track the information spreading dynamics along cells. Numerical experiments based on simulation and field data indicate that the IT-CTM can closely track the dynamic movements of information front and tail as well as the dynamic information coverage as a single or multiple piece(s) of information propagating via VANET on a one-way or two-way road segment. The mean absolute error (MAE) for tracking dynamic information coverage is <5% across all experiments in this study.

      PubDate: 2016-10-21T18:03:15Z
      DOI: 10.1016/j.trc.2016.10.007
      Issue No: Vol. 73 (2016)
  • Estimating potential increases in travel with autonomous vehicles for the
           non-driving, elderly and people with travel-restrictive medical conditions
    • Authors: Corey D. Harper; Chris T. Hendrickson; Sonia Mangones; Constantine Samaras
      Pages: 1 - 9
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Corey D. Harper, Chris T. Hendrickson, Sonia Mangones, Constantine Samaras
      Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19–64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.

      PubDate: 2016-09-24T11:26:00Z
      DOI: 10.1016/j.trc.2016.09.003
      Issue No: Vol. 72 (2016)
  • Emergence of cooperation in congested road networks using ICT and future
           and emerging technologies: A game-based review
    • Authors: Ido Klein; Eran Ben-Elia
      Pages: 10 - 28
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Ido Klein, Eran Ben-Elia
      Information and communications technologies (ICT) and future and emerging technologies (FET) are expected to revolutionize transportation in the next generation. Travelers’ behavioral adaptation is a key to their success. We discuss the notion of managing traffic congestion by enhancing cooperation in road networks enabled with ICT and FET. Cooperation is an emergent social state related to the dynamics and complexity of road traffic and reinforced learning. Game theory and research in behavioral economics show that cooperation can be leveraged to efficiently solve social dilemmas similar to traffic congestion. We review the applicability of behavioral economics and game theory concepts to route, mode and departure time choice problems. Beyond advancing theory, research on cooperation in the context of transportation is still in its infancy. We discuss state-of-the-art methodologies and their weaknesses and review the unexplored opportunities inherent in game-based methodologies. A behavioral-technological research agenda for FET is also discussed.

      PubDate: 2016-09-24T11:26:00Z
      DOI: 10.1016/j.trc.2016.09.005
      Issue No: Vol. 72 (2016)
  • A model and optimization-based heuristic for the operational aircraft
           maintenance routing problem
    • Authors: Nayla Ahmad Al-Thani; Mohamed Ben Ahmed; Mohamed Haouari
      Pages: 29 - 44
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Nayla Ahmad Al-Thani, Mohamed Ben Ahmed, Mohamed Haouari
      This paper investigates the Operational Aircraft Maintenance Routing Problem (OAMRP). Given a set of flights for a specific homogeneous fleet type, this short-term planning problem requires building feasible aircraft routes that cover each flight exactly once and that satisfy maintenance requirements. Basically, these requirements enforce an aircraft to undergo a planned maintenance at a specified station before accumulating a maximum number of flying hours. This stage is significant to airline companies as it directly impacts the fleet availability, safety, and profitability. The contribution of this paper is twofold. First, we elucidate the complexity status of the OAMRP and we propose an exact mixed-integer programming model that includes a polynomial number of variables and constraints. Furthermore, we propose a graph reduction procedure and valid inequalities that aim at improving the model solvability. Second, we propose a very large-scale neighborhood search algorithm along with a procedure for computing tight lower bounds. We present the results of extensive computational experiments that were carried out on real-world flight networks and attest to the efficacy of the proposed exact and heuristic approaches. In particular, we provide evidence that the exact model delivers optimal solutions for instances with up to 354 flights and 8 aircraft, and that the heuristic approach consistently delivers high-quality solutions while requiring short CPU times.

      PubDate: 2016-09-24T11:26:00Z
      DOI: 10.1016/j.trc.2016.09.004
      Issue No: Vol. 72 (2016)
  • Headway-based bus bunching prediction using transit smart card data
    • Authors: Haiyang Yu; Dongwei Chen; Zhihai Wu; Xiaolei Ma; Yunpeng Wang
      Pages: 45 - 59
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Haiyang Yu, Dongwei Chen, Zhihai Wu, Xiaolei Ma, Yunpeng Wang
      Bus bunching severely deteriorates the quality of transit service with poor on-time performance and excessive waiting time. To mitigate bus bunching, this paper presents a predictive framework to capture the stop-level headway irregularity based on transit smart card data. Historical headway, passenger demands, and travel time are utilized to model the headway fluctuation at the following stops. A Least Squares Support Vector Machine regression is established to detect bus bunching with the predicted headway pattern. An empirical experiment with two bus routes in Beijing is conducted to demonstrate the effectiveness of the proposed approach. The predictive method can successfully identify more than 95% of bus bunching occurrences in comparison with other well-established prediction algorithms. Moreover, the detection accuracy does not significantly deteriorate as the prediction lead time increases. Instead of regularizing the headways at all costs by adopting certain correction actions, the proposed framework can provide timely and accurate information for potential bus bunching prevention and inform passengers when the next bus will arrive. This feature will greatly increase transit ridership and reduce operating costs for transit authorities.

      PubDate: 2016-09-30T14:34:26Z
      DOI: 10.1016/j.trc.2016.09.007
      Issue No: Vol. 72 (2016)
  • Vehicular ad-hoc network simulations of overtaking maneuvers on two-lane
           rural highways
    • Authors: Michael Motro; Alice Chu; Junil Choi; Patricia S. Lavieri; Abdul Rawoof Pinjari; Chandra R. Bhat; Joydeep Ghosh; Robert W. Heath
      Pages: 60 - 76
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Michael Motro, Alice Chu, Junil Choi, Patricia S. Lavieri, Abdul Rawoof Pinjari, Chandra R. Bhat, Joydeep Ghosh, Robert W. Heath
      The objective of this paper is to evaluate the effectiveness of a dedicated short-range communication (DSRC)-based wireless vehicle-to-vehicle (V2V) communication system, called the overtaking assistant, devised for improving safety during overtaking (also referred to as passing) maneuvers on two-lane rural highways. Specifically, the paper examines the influence of vehicular kinematics (vehicle speeds, accelerations and distances), driver behavior (drivers’ perception/reaction time and overtaking rate), and DSRC characteristics (power settings, communication range, packet errors, sensor errors, and estimation inaccuracy) on the effectiveness of DSRC systems in predicting unsafe overtaking maneuvers. To this end, the paper utilizes a microscopic traffic simulator called VEhicles In Network Simulation (VEINS) that supports the simulation of wireless communication protocols in Vehicular Ad-hoc NEtworks (VANETs). 18,000 overtaking maneuvers – with roughly 10,000 collision maneuvers – were simulated to consider heterogeneity in vehicular kinematics, driver behavior, and DSRC performance. The overtaking assistant predicts whether a collision will occur and warns the driver before the maneuver begins. A descriptive analysis followed by a multivariate analysis (using binary discrete outcome models) of the simulated data reveals that the majority of collisions that could not be detected were due to the vehicles being out of communication range for the communication power settings used in the simulation. Packet errors, or failed communications, at a rate of up to 50% did not have a significant influence on the ability to detect collisions. These results suggest that the most important step in paving the way toward advanced driver assistance systems for rural highway overtaking maneuvers is to broaden the communication range of DSRC devices.

      PubDate: 2016-09-30T14:34:26Z
      DOI: 10.1016/j.trc.2016.09.006
      Issue No: Vol. 72 (2016)
  • Probabilistic analysis of the release of liquefied natural gas (LNG)
           tenders due to freight-train derailments
    • Authors: Xiang Liu; Bryan W. Schlake
      Pages: 77 - 92
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Xiang Liu, Bryan W. Schlake
      Liquefied natural gas (LNG) has emerged as a possible alternative fuel for freight railroads in the United States, due to the availability of cheap domestic natural gas and continued pursuit of environmental and energy sustainability. A safety concern regarding the deployment of LNG-powered trains is the risk of breaching the LNG tender car (a special type of hazardous materials car that stores fuel for adjacent locomotives) in a train accident. When a train is derailed, an LNG tender car might be derailed or damaged, causing a release and possible fire. This paper describes the first study that focuses on modeling the probability of an LNG tender car release incident due to a freight train derailment on a mainline. The model accounts for a number of factors such as FRA track class, method of operation, annual traffic density level, train length, the point of derailment, accident speed, the position(s) of the LNG tender(s) in a train, and LNG tender car design. The model can be applied to any specified route or network with LNG-fueled trains. The implementation of the model can be undertaken by the railroad industry to develop proactive risk management solutions when using LNG as an alternative railroad fuel.

      PubDate: 2016-09-30T14:34:26Z
      DOI: 10.1016/j.trc.2016.08.017
      Issue No: Vol. 72 (2016)
  • Road network inference through multiple track alignment
    • Authors: Xingzhe Xie; Kevin Bing-Yung Wong; Hamid Aghajan; Peter Veelaert; Wilfried Philips
      Pages: 93 - 108
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Xingzhe Xie, Kevin Bing-Yung Wong, Hamid Aghajan, Peter Veelaert, Wilfried Philips
      Road networks are a critical aspect of both path optimization and route planning. This paper proposes to generate the road network automatically from GPS traces through jointly aligning tracks for each road segment. First, intersections are clustered from turning points where the road users’ moving directions change. GPS traces are partitioned into small tracks for individual road segments by directly-connected intersections. The tracks for each road segment are aligned using a greedy method based on successor classification. A “forward-track” procedure is proposed to locate a warp path through jointly traversing all tracks in a way which keeps the points associated by the path element spatially close to each other. This involves an iterative procedure to cluster successor points on the tracks. The warp path produced during the alignment is used to average the tracks as the geometric representation of the road segment, and to analyze the velocity variation along the road segment. Experimental results show our method outperforms other existing methods in producing no spurious road edges and more accurate geometric road representation.

      PubDate: 2016-09-30T14:34:26Z
      DOI: 10.1016/j.trc.2016.09.010
      Issue No: Vol. 72 (2016)
  • Isolated intersection control for various levels of vehicle technology:
           Conventional, connected, and automated vehicles
    • Authors: Kaidi Yang; S. Ilgin Guler; Monica Menendez
      Pages: 109 - 129
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Kaidi Yang, S. Ilgin Guler, Monica Menendez
      Connected vehicle technology can be beneficial for traffic operations at intersections. The information provided by cars equipped with this technology can be used to design a more efficient signal control strategy. Moreover, it can be possible to control the trajectory of automated vehicles with a centralized controller. This paper builds on a previous signal control algorithm developed for connected vehicles in a simple, single intersection. It improves the previous work by (1) integrating three different stages of technology development; (2) developing a heuristics to switch the signal controls depending on the stage of technology; (3) increasing the computational efficiency with a branch and bound solution method; (4) incorporating trajectory design for automated vehicles; (5) using a Kalman filter to reduce the impact of measurement errors on the final solution. Three categories of vehicles are considered in this paper to represent different stages of this technology: conventional vehicles, connected but non-automated vehicles (connected vehicles), and automated vehicles. The proposed algorithm finds the optimal departure sequence to minimize the total delay based on position information. Within each departure sequence, the algorithm finds the optimal trajectory of automated vehicles that reduces total delay. The optimal departure sequence and trajectories are obtained by a branch and bound method, which shows the potential of generalizing this algorithm to a complex intersection. Simulations are conducted for different total flows, demand ratios and penetration rates of each technology stage (i.e. proportion of each category of vehicles). This algorithm is compared to an actuated signal control algorithm to evaluate its performance. The simulation results show an evident decrease in the total number of stops and delay when using the connected vehicle algorithm for the tested scenarios with information level of as low as 50%. Robustness of this algorithm to different input parameters and measurement noises are also evaluated. Results show that the algorithm is more sensitive to the arrival pattern in high flow scenarios. Results also show that the algorithm works well with the measurement noises. Finally, the results are used to develop a heuristic to switch between the different control algorithms, according to the total demand and penetration rate of each technology.

      PubDate: 2016-09-30T14:34:26Z
      DOI: 10.1016/j.trc.2016.08.009
      Issue No: Vol. 72 (2016)
  • A Spatial Hazard-Based analysis for modelling vehicle selection in
           station-based carsharing systems
    • Authors: Sisi Jian; Taha Hossein Rashidi; Kasun P. Wijayaratna; Vinayak V. Dixit
      Pages: 130 - 142
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Sisi Jian, Taha Hossein Rashidi, Kasun P. Wijayaratna, Vinayak V. Dixit
      Carsharing, as an alternative to private vehicle ownership, has spread worldwide in recent years due to its potential of reducing congestion, improving auto utilization rate and limiting the environmental impact of emissions release. To determine the most efficient allocation of resources within a carsharing program, it is critical to understand what factors affect the users’ behavior when selecting vehicles. This study attempts to investigate the importance of users’ attributes and fleet characteristics on choice set formation behavior in selecting vehicles using a Spatial Hazard Based Model (SHBM). In the SHBM model, “distance to a vehicle” is considered as the prospective decision criteria that carsharing users follow when evaluating the set of alternative vehicles. This variable is analogous to the duration in a conventional hazard-based model. In addition, user socio-demographic attributes, vehicle characteristics, land use type of the trip origin, etc., collected from the Australian carsharing company GoGet are utilized to parameterize the shape/scale/location parameter of the hazard function. A number of forms of parametric SHBMs are tested to determine the best fit to the data. The accelerated failure time model with a Log-logistic distribution was found to provide the best fit. The estimation results of the coefficients of the parameters can provide a starting point for carsharing organizations to optimize their pod locations and types of cars available at different pods to maximize usage.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.008
      Issue No: Vol. 72 (2016)
  • Optimal deployment of autonomous vehicle lanes with endogenous market
    • Authors: Zhibin Chen; Fang He; Lihui Zhang; Yafeng Yin
      Pages: 143 - 156
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Zhibin Chen, Fang He, Lihui Zhang, Yafeng Yin
      This paper develops a mathematical approach to optimize a time-dependent deployment plan of autonomous vehicle (AV) lanes on a transportation network with heterogeneous traffic stream consisting of both conventional vehicles (CVs) and AVs, so as to minimize the social cost and promote the adoption of AVs. Specifically, AV lanes are exclusive lanes that can only be utilized by AVs, and the deployment plan specifies when, where, and how many AV lanes to be deployed. We first present a multi-class network equilibrium model to describe the flow distributions of both CVs and AVs, given the presence of AV lanes in the network. Considering that the net benefit (e.g., reduced travel cost) derived from the deployment of AV lanes will further promote the AV adoption, we proceed to apply a diffusion model to forecast the evolution of AV market penetration. With the equilibrium model and diffusion model, a time-dependent deployment model is then formulated, which can be solved by an efficient solution algorithm. Lastly, numerical examples based on the south Florida network are presented to demonstrate the proposed models.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.013
      Issue No: Vol. 72 (2016)
  • A low-cost alternative for higher capacities at four-way signalized
    • Authors: Peter Kozey; Yiguang Xuan; Michael J. Cassidy
      Pages: 157 - 167
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Peter Kozey, Yiguang Xuan, Michael J. Cassidy
      Protecting left-turn movements on all four approaches to a signalized intersection conventionally requires a minimum of two extra phases per cycle. Losses in capacity often result. Various intersection designs have been proposed to combat those losses. Perhaps the best known of these designs is the continuous flow intersection. It features specially-configured approach lanes and mid-block pre-signals. These enable opposing left-turn and through-moving vehicles to proceed through the intersection free of conflicts, and without need for additional protected-turn phases. The present paper offers an alternative design for four-way intersections, which to our knowledge has not previously been proposed. The design furnishes lower capacities than do continuous flow intersections, but spares the expense of having to reconfigure approach lanes. Pre-signals store queues and route traffic through the intersection much as in a continuous flow design. The distinguishing feature of the alternative is that it enables all four turn movements to be served during a single protected phase. Only one additional phase is therefore required per cycle. Numerical analysis shows that the plan regularly achieves higher intersection capacities than do conventional designs. Capacity gains as high as 80% are predicted. The proposed design is rather mentally taxing to drivers. Hence, opportunities for deploying the design in real settings are discussed with an eye toward the more connected and automated driving expected in the future.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.012
      Issue No: Vol. 72 (2016)
  • An efficient realization of deep learning for traffic data imputation
    • Authors: Yanjie Duan; Yisheng Lv; Yu-Liang Liu; Fei-Yue Wang
      Pages: 168 - 181
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Yanjie Duan, Yisheng Lv, Yu-Liang Liu, Fei-Yue Wang
      Traffic data provide the basis for both research and applications in transportation control, management, and evaluation, but real-world traffic data collected from loop detectors or other sensors often contain corrupted or missing data points which need to be imputed for traffic analysis. For this end, here we propose a deep learning model named denoising stacked autoencoders for traffic data imputation. We tested and evaluated the model performance with consideration of both temporal and spatial factors. Through these experiments and evaluation results, we developed an algorithm for efficient realization of deep learning for traffic data imputation by training the model hierarchically using the full set of data from all vehicle detector stations. Using data provided by Caltrans PeMS, we have shown that the mean absolute error of the proposed realization is under 10veh/5-min, a better performance compared with other popular models: the history model, ARIMA model and BP neural network model. We further investigated why the deep leaning model works well for traffic data imputation by visualizing the features extracted by the first hidden layer. Clearly, this work has demonstrated the effectiveness as well as efficiency of deep learning in the field of traffic data imputation and analysis.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.015
      Issue No: Vol. 72 (2016)
  • Optimizing signals for arterials experiencing heavy mixed scooter-vehicle
    • Authors: Chien-Lun Lan; Gang-Len Chang
      Pages: 182 - 201
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Chien-Lun Lan, Gang-Len Chang
      Recognizing the increasing popularity of scooters among urban commuters in developing countries and the significant impacts of their dynamic maneuverability on the progression of mixed traffic, this study presents a simulation-based signal optimization model for arterials experiencing heavy scooter-vehicle flows. The proposed model consists of a macroscopic simulation and a signal optimization module, where the former functions to capture the interactions between scooter and passenger-car flows over the process of discharging, propagation, and formation of intersection queues. The latter offers a specially-designed algorithm to search for the optimal signal plan and arterial offsets, based on the complex departure and arrival patterns of mixed flows estimated with the simulation module. To account for scooters’ unique parallel moving and queue patterns in a travel lane, the proposed signal module has adopted the sub-lane concept in estimating the mixed-flow queue distribution across lanes and their discharging flow rates. The results of extensive experimental analyses with various mixed-flow scenarios confirm that the proposed model offers the potential for signal design for arterials plagued by heavy scooter-vehicle mixed flows.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.011
      Issue No: Vol. 72 (2016)
  • Adaptive traffic parameter prediction: Effect of number of states and
           transferability of models
    • Authors: Gurcan Comert; Anton Bezuglov; Mecit Cetin
      Pages: 202 - 224
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Gurcan Comert, Anton Bezuglov, Mecit Cetin
      Traffic parameters can show shifts due to factors such as weather, accidents, and driving characteristics. This study develops a model for predicting traffic speeds under these abrupt changes within regime switching framework. The proposed approach utilizes Hidden Markov, Expectation Maximization, Recursive Least Squares Filtering, and ARIMA methods for an adaptive forecasting method. The method is compared with naive and mean updating linear and nonlinear time series models. The model is fitted and tested extensively using 1993 I-880 loop data from California and January 2014 INRIX data from Virginia. Analysis for number of states, impact of number of states on forecasting, prediction scope, and transferability of the model to different locations are investigated. A 5-state model is found to be providing best results. Developed model is tested for 1-step to 45-step forecasts. The accuracy of predictions are improved until 15-step over nonadaptive and mean adaptive models. Except 1-step predictions, the model is found to be transferable to different locations. Even if the developed model is not retrained on different datasets, it is able to provide better or close results with nonadaptive and adaptive models that are retrained on the corresponding dataset.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.014
      Issue No: Vol. 72 (2016)
  • A gradient boosting logit model to investigate driver’s stop-or-run
           behavior at signalized intersections using high-resolution traffic data
    • Authors: Chuan Ding; Xinkai Wu; Guizhen Yu; Yunpeng Wang
      Pages: 225 - 238
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Chuan Ding, Xinkai Wu, Guizhen Yu, Yunpeng Wang
      Driver’s stop-or-run behavior at signalized intersection has become a major concern for the intersection safety. While many studies were undertaken to model and predict drivers’ stop-or-run (SoR) behaviors including Yellow-Light-Running (YLR) and Red-Light-Running (RLR) using traditional statistical regression models, a critical problem for these models is that the relative influences of predictor variables on driver’s SoR behavior could not be evaluated. To address this challenge, this research proposes a new approach which applies a recently developed data mining approach called gradient boosting logit model to handle different types of predictor variables, fit complex nonlinear relationships among variables, and automatically disentangle interaction effects between influential factors using high-resolution traffic and signal event data collected from loop detectors. Particularly, this research will first identify a series of related influential factors including signal timing information, surrounding traffic information, and surrounding drivers’ behaviors using thousands drivers’ decision events including YLR, RLR, and first-to-stop (FSTP) extracted from high-resolution loop detector data from three intersections. Then the research applies the proposed data mining approach to search for the optimal prediction model for each intersection. Furthermore, a comparison was conducted to compare the proposed new method with the traditional statistical regression model. The results show that the gradient boosting logit model has superior performance in terms of prediction accuracy. In contrast to other machine learning methods which usually apply ‘black-box’ procedures, the gradient boosting logit model can identify and rank the relative importance of influential factors on driver’s stop-or-run behavior prediction. This study brings great potential for future practical applications since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly.

      PubDate: 2016-10-08T19:18:02Z
      DOI: 10.1016/j.trc.2016.09.016
      Issue No: Vol. 72 (2016)
  • Meeting points in ridesharing: A privacy-preserving approach
    • Authors: Ulrich Matchi Aïvodji; Sébastien Gambs; Marie-José Huguet; Marc-Olivier Killijian
      Pages: 239 - 253
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Ulrich Matchi Aïvodji, Sébastien Gambs, Marie-José Huguet, Marc-Olivier Killijian
      Nowadays, problems of congestion in urban areas due to the massive usage of cars, last-minute travel needs and progress in information and communication technologies have fostered the rise of new transportation modes such as ridesharing. In a ridesharing service, a car owner shares empty seats of his car with other travelers. Recent ridesharing approaches help to identify interesting meeting points to improve the efficiency of the ridesharing service (i.e., the best pick-up and drop-off points so that the travel cost is competitive for both driver and rider). In particular, ridesharing services, such as Blablacar or Carma, have become a good mobility alternative for users in their daily life. However, this success has come at the cost of user privacy. Indeed in current’s ridesharing services, users are not in control of their own data and have to trust the ridesharing operators with the management of their data. In this paper, we aim at developing a privacy-preserving service to compute meeting points in ridesharing, such that each user remains in control of his location data. More precisely, we propose a decentralized architecture that provides strong security and privacy guarantees without sacrificing the usability of ridesharing services. In particular, our approach protects the privacy of location data of users. Following the privacy-by-design principle, we have integrated existing privacy enhancing technologies and multimodal shortest path algorithms to privately compute mutually interesting meeting points for both drivers and riders in ridesharing. In addition, we have built a prototype implementation of the proposed approach. The experiments, conducted on a real transportation network, have demonstrated that it is possible to reach a trade-off in which both the privacy and utility levels are satisfactory.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.09.017
      Issue No: Vol. 72 (2016)
  • Collecting ambient vehicle trajectories from an instrumented probe vehicle
    • Authors: Benjamin Coifman; Mo Wu; Keith Redmill; Douglas A. Thornton
      Pages: 254 - 271
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Benjamin Coifman, Mo Wu, Keith Redmill, Douglas A. Thornton
      This paper presents the methodology and results from a study to extract empirical microscopic vehicular interactions from a probe vehicle instrumented with sensors to monitor the ambient vehicles as it traverses a 28mi long freeway corridor. The contributions of this paper are two fold: first, the general method and approach to seek a cost-effective balance between automation and manual data reduction that transcends the specific application. Second, the resulting empirical data set is intended to help advance traffic flow theory in general and car following models in particular. Generally the collection of empirical microscopic vehicle interaction data is either too computationally intensive or labor intensive. Historically automatic data extraction does not provide the precision necessary to advance traffic flow theory, while the labor demands of manual data extraction have limited past efforts to small scales. Key to the present study is striking the right balance between automatic and manual processing. Recognizing that any empirical microscopic data for traffic flow theory has to be manually validated anyway, the present study uses a “pretty good” automated processing algorithm followed by detailed manual cleanup using an efficient user interface to rapidly process the data. The study spans roughly two hours of data collected on a freeway during the afternoon peak of a typical weekday that includes recurring congestion. The corresponding data are being made available to the research community to help advance traffic flow theory in general and car following models in particular.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.09.001
      Issue No: Vol. 72 (2016)
  • Battery capacity design for electric vehicles considering the diversity of
           daily vehicles miles traveled
    • Authors: Zhiheng Li; Shan Jiang; Jing Dong; Shoufeng Wang; Zhennan Ming; Li Li
      Pages: 272 - 282
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Zhiheng Li, Shan Jiang, Jing Dong, Shoufeng Wang, Zhennan Ming, Li Li
      In this paper, we study battery capacity design for battery electric vehicles (BEVs). The core of such design problems is to find a good tradeoff between minimizing the capacity to reduce financial costs of drivers and increasing the capacity to satisfy daily travel demands. The major difficulty of such design problems lies in modeling the diversity of daily travel demands. Based on massive trip records of taxi drivers in Beijing, we find that the daily vehicle miles traveled (DVMT) of a driver (e.g., a taxi driver) may change significantly in different days. This investigation triggers us to propose a mixture distribution model to describe the diversity in DVMT for various driver in different days, rather than the widely employed single distribution model. To demonstrate the merit of this new model, we consider value-at-risk and mean-variance battery capacity design problems for BEV, with respect to conventional single and new mixture distribution models of DVMT. Testing results indicate that the mixture distribution model better leads to better solutions to satisfy various drivers.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.10.001
      Issue No: Vol. 72 (2016)
  • Efficient intersection control for minimally guided vehicles: A
           self-organised and decentralised approach
    • Authors: Bo Yang; Christopher Monterola
      Pages: 283 - 305
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Bo Yang, Christopher Monterola
      An important question for the practical applicability of the highly efficient traffic intersection control is about the minimal level of intelligence the vehicles need to have so as to move beyond the traffic light control. We propose an efficient intersection traffic control scheme without the traffic lights, that only requires a majority of vehicles on the road to be equipped with a simple driver assistance system. The algorithm of our scheme is completely decentralised, and takes into full account the non-linear interaction between the vehicles at high density. For vehicles approaching the intersection in different directions, our algorithm imposes simple interactions between vehicles around the intersection, by defining specific conditions on the real-time basis, for which the involved vehicles are required to briefly adjust their dynamics. This leads to a self-organised traffic flow that is safe, robust, and efficient. We also take into account of the driver comfort level and study its effect on the control efficiency. The scheme has low technological barrier, minimal impact on the conventional driving behaviour, and can coexist with the traffic light control. It also has the advantages of being easily scalable, and fully compatible with both the conventional road systems as well as the futuristic scenario in which driverless vehicles dominate the road. The mathematical formulation of our scheme permits large scale realistic numerical simulations of busy intersections, allowing a more complete evaluation of the control performance, instead of just the collision avoidance at the intersection.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.10.004
      Issue No: Vol. 72 (2016)
  • Driving safety field theory modeling and its application in pre-collision
           warning system
    • Authors: Jianqiang Wang; Jian Wu; Xunjia Zheng; Daiheng Ni; Keqiang Li
      Pages: 306 - 324
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Jianqiang Wang, Jian Wu, Xunjia Zheng, Daiheng Ni, Keqiang Li
      The concept and contents of driving safety field theory were presented in our previous study. On this basis, this study focus on driving safety field theory modeling and application. First, a general model is presented, which considered the driver-vehicle-road interactions. The model include the following three parts: (i) driver behaviors, which are determined by driver characteristics, such as physical-psychological, cognition, driving skill, and traffic violations; (ii) vehicle characteristics, which are determined by velocity vectors and virtual masses of vehicles; (iii) road conditions, which are determined by virtual mass of on road non-moving objects, types of traffic signs, road adhesion coefficient, road slope, road curvature, and visibility. In order to establish concrete functional forms, the specific model is presented. This specific model provides a method for virtual mass calculation and describes the field strength and field force in detail. After that, a driving safety indicator namely DSI is defined. Finally, a vehicle collision warning algorithm based on driving safety field model is presented. This algorithm used a new index namely RDSI to evaluate the driving risk level. The effectiveness of this collision warning algorithm is verified by field experiments.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.10.003
      Issue No: Vol. 72 (2016)
  • Instantaneous communication capacities of vehicular ad hoc networks
    • Authors: Hao Yang; Wen-Long Jin
      Pages: 325 - 341
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Hao Yang, Wen-Long Jin
      Wireless communications among vehicles, roadside infrastructures, and traffic management centers can enable the development of next-generation Intelligent Transportation Systems so as to tackle basic traffic problems associated with driving safety, road congestion, and vehicle emissions. This paper analytically investigates the instantaneous communication capacities of vehicular ad hoc networks (VANETs), which measure the upper bounds of the message transmission rates of vehicles. Subject to interference among wireless transmissions, the broadcast capacity is defined by the maximum number of successful receivers, and the unicast capacity by the maximum number of successful senders. With the protocol communication model and uniform vehicular traffic patterns, we derive closed-form formulas for the capacities as functions of transmission range r, interference ratio δ , vehicular density ρ , and channel capacity W. We show that broadcast capacities are approximately W ( 2 + δ ) r ρ + 1 for uni-directional communications, and 2 W ( 2 + δ ) r ρ + 1 for bi-directional communications; while unicast capacities are approximately W ( 1 + δ ) r ρ + 1 for uni-directional communications, and W ( 1 + δ ) r ρ + 1 for bi-directional communications. For general vehicular traffic patterns, an optimization model is proposed to calculate the capacities, and a genetic algorithm integrated with the protocol communication model is developed to solve the optimization problem. Finally, the impacts of different transmission ranges, interference ratios, and shock waves on communication capacities are analyzed.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.10.005
      Issue No: Vol. 72 (2016)
  • Multi-stage stochastic program to optimize signal timings under
           coordinated adaptive control
    • Authors: Wanjing Ma; Kun An; Hong K. Lo
      Pages: 342 - 359
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Wanjing Ma, Kun An, Hong K. Lo
      In the wake of traffic congestion at intersections, it is imperative to shorten delays in corridors with stochastic arrivals. Coordinated adaptive control can adjust green time flexibly to deal with a stochastic demand, while maintaining a minimum through-band for coordinated intersections. In this paper, a multi-stage stochastic program based on phase clearance reliability (PCR) is proposed to optimize base timing plans and green split adjustments of coordinated intersections under adaptive control. The objective is to minimize the expected intersection delay and overflow of the coordinated approach. The overflow or oversaturated effect is explicitly addressed in the delay calculation, which greatly increases the modeling complexity due to the interaction of overflow delays across cycles. The notion of PCR separates the otherwise related green time settings of consecutive cycles into a number of stages, in which the base timing plan and actual timing plan in different cycles are handled sequentially. We then develop a PCR based solution algorithm to solve the problem, and apply the model and the solution algorithm to actual intersections in Shanghai to investigate its performance as compared with Allsop’s method and Webster’s method. Preliminary results show the PCR-based method can significantly shorten delays and almost eliminates overflow for the coordinated approaches, with acceptable delay increases of the non-coordinated approaches. A comparison between the proposed coordinated adaptive logic and a coordinated actuated logic is also conducted in the case study to show the advantages and disadvantages.

      PubDate: 2016-10-15T02:57:37Z
      DOI: 10.1016/j.trc.2016.10.002
      Issue No: Vol. 72 (2016)
  • Understanding the impacts of mobile phone distraction on driving
           performance: A systematic review
    • Authors: Oscar Oviedo-Trespalacios; Md. Mazharul Haque; Mark King; Simon Washington
      Pages: 360 - 380
      Abstract: Publication date: November 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 72
      Author(s): Oscar Oviedo-Trespalacios, Md. Mazharul Haque, Mark King, Simon Washington
      The use of mobile phones while driving—one of the most common driver distractions—has been a significant research interest during the most recent decade. While there has been a considerable amount research and excellent reviews on how mobile phone distractions influence various aspects of driving performance, the mechanisms by which the interactions with mobile phone affect driver performance is relatively unexamined. As such, the aim of this study is to examine the mechanisms involved with mobile phone distractions such as conversing, texting, and reading and the driving task, and subsequent outcomes. A novel human-machine framework is proposed to isolate the components and various interactions associated with mobile phone distracted driving. The proposed framework specifies the impacts of mobile phone distraction as an inter-related system of outcomes such as speed selection, lane deviations and crashes; human-car controls such as steering control and brake pedal use and human-environment interactions such as visual scanning and navigation. Eleven literature-review/meta-analyses papers and 62 recent research articles from 2005 to 2015 are critically reviewed and synthesised following a systematic classification scheme derived from the human-machine system framework. The analysis shows that while many studies have attempted to measure system outcomes or driving performance, research on how drivers interactively manage in-vehicle secondary tasks and adapt their driving behaviour while distracted is scant. A systematic approach may bolster efforts to examine comprehensively the performance of distracted drivers and their impact over the transportation system by considering all system components and interactions of drivers with mobile phones and vehicles. The proposed human-machine framework not only contributes to the literature on mobile phone distraction and safety, but also assists in identifying the research needs and promising strategies for mitigating mobile phone-related safety issues. Technology based countermeasures that can provide real-time feedback or alerts to drivers based on eye/head movements in conjunction with vehicle dynamics should be an important research direction.

      PubDate: 2016-10-21T18:03:15Z
      DOI: 10.1016/j.trc.2016.10.006
      Issue No: Vol. 72 (2016)
  • Optimization of traffic flow at freeway sags by controlling the
           acceleration of vehicles equipped with in-car systems
    • Authors: Bernat Goñi-Ros; Victor L. Knoop; Toshimichi Takahashi; Ichiro Sakata; Bart van Arem; Serge P. Hoogendoorn
      Pages: 1 - 18
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Bernat Goñi-Ros, Victor L. Knoop, Toshimichi Takahashi, Ichiro Sakata, Bart van Arem, Serge P. Hoogendoorn
      Sags are bottlenecks in freeway networks. According to previous research, the main cause is that most drivers do not accelerate enough at sags. Consequently, they keep longer headways than expected given their speed, which leads to congestion in high demand conditions. Nowadays, there is growing interest in the development of traffic control measures for sags based on the use of in-car systems. This paper aims to determine the optimal acceleration behavior of vehicles equipped with in-car systems at sags and the related effects on traffic flow, thereby laying the theoretical foundation for developing effective traffic management applications. We formulate an optimal control problem in which a centralized controller regulates the acceleration of some vehicles of a traffic stream moving along a single-lane freeway stretch with a sag. The control objective is to minimize total travel time. The problem is solved for scenarios with different numbers of controlled vehicles and positions in the stream, assuming low penetration rates. The results indicate that the optimal behavior involves performing a deceleration-acceleration-deceleration-acceleration (DADA) maneuver in the sag area. This maneuver induces the first vehicles located behind the controlled vehicle to accelerate fast along the vertical curve. As a result, traffic speed and flow at the end of the sag (bottleneck) increase for a time. The maneuver also triggers a stop-and-go wave that temporarily limits the inflow into the sag, slowing down the formation of congestion at the bottleneck. Moreover, in some cases controlled vehicles perform one or more deceleration-acceleration maneuvers upstream of the sag. This additional strategy is used to manage congestion so that inflow is regulated more effectively. Although we cannot guarantee global optimality, our findings reveal a potentially highly effective and innovative way to reduce congestion at sags, which could possibly be implemented using cooperative adaptive cruise control systems.

      PubDate: 2016-07-12T23:40:56Z
      DOI: 10.1016/j.trc.2016.06.022
      Issue No: Vol. 71 (2016)
  • Non-recurrent congestion analysis using data-driven spatiotemporal
           approach for information construction
    • Authors: Zhuo Chen; Xiaoyue Cathy Liu; Guohui Zhang
      Pages: 19 - 31
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zhuo Chen, Xiaoyue Cathy Liu, Guohui Zhang
      A systematic approach to quantify Incident-Induced Delay (IID) is proposed in this study. The paper complements existing literature by developing a data-driven method to dynamically determine the spatiotemporal extent of individual incidents. The information construction process can be further used to uncover a variety of features that are associated with any specific incidents for optimal freeway management. Additionally, this study contributes two particular highlights: secondary incident identification and K-Nearest Neighbor (KNN) pattern matching. Secondary incident identification, as a pre-processing for IID estimation, disentangles the convoluted influences of subsequent incidents. The proposed method uses KNN pattern matching, an essentially heuristic search process to separate the delay solely induced by incidents from the recurrent congestion. The proposed algorithm on IID quantification was implemented on Interstate 15 in the state of Utah using data obtained from 2013. Results and implications are presented. Hot spot analysis is conducted that can be potentially used for incident mitigation and to inform investment decisions. The proposed methodology is easily transferable to any traffic operation system that has access to sensor data at a corridor level.

      PubDate: 2016-07-19T13:06:25Z
      DOI: 10.1016/j.trc.2016.07.002
      Issue No: Vol. 71 (2016)
  • A lane-level road network model with global continuity
    • Authors: Tao Zhang; Stefano Arrigoni; Marco Garozzo; Dian-ge Yang; Federico Cheli
      Pages: 32 - 50
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Tao Zhang, Stefano Arrigoni, Marco Garozzo, Dian-ge Yang, Federico Cheli
      An increasing number of Intelligent Transportation System (ITS) applications require high accurate vehicle positioning, e.g., positioning at the lane-level. This requirement motives the development of modeling the road network at the lane-level. In this paper we propose a novel lane-level road network model. It can be considered an improvement to existing models in its capability of representing the road and intersection details at the lane-level in a uniform and precise way. As a result, the model can guarantee the global continuity for arbitrary map route, which better approximates the real vehicle trajectory. In addition, the map construction algorithms are also developed. Following the proposed methods, the lane parameters can be extracted efficiently under flexible precision requirement, and intersections with varying appearances can be precisely modeled with limited extra data. Experiments were performed to verify the proposed model in representing the lane-level geometrical and topological details of an urban area of Milan. The results also demonstrate the effectiveness of the map construction methods.

      PubDate: 2016-07-19T13:06:25Z
      DOI: 10.1016/j.trc.2016.07.003
      Issue No: Vol. 71 (2016)
  • The influence of attitude towards individuals’ choice for a remotely
           piloted commercial flight: A latent class logit approach
    • Authors: Brett R.C. Molesworth; Tay T.R. Koo
      Pages: 51 - 62
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Brett R.C. Molesworth, Tay T.R. Koo
      The Remotely Piloted Commercial Passenger Aircraft Attitude Scale (RPCPAAS) was created to measure positive and negative attitudes towards a new and plausible form of air travel. This information was then used, in combination with a latent class logit model built on data generated from a stated choice experiment to gain insight into the choice behaviour between conventionally piloted aircraft (CPA) with a pilot on-board and remotely piloted aircraft (RPA) with a pilot on the ground. The results revealed that individuals, on-average, if presented a choice between a CPA and a RPA of equivalent attributes, would elect for the CPA option. However, there is variability in the passengers’ sensitivity to various flight attributes, and these sensitivities were influenced by individuals’ attitude towards the new technology (i.e., RPA). From an operational perspective, and assuming that one day passengers of commercial airlines are offered the choice between CPA and RPA, the strategies employed by airlines to encourage the use of the new technology need to be different, based on individuals’ attitude towards RPA.

      PubDate: 2016-07-19T13:06:25Z
      DOI: 10.1016/j.trc.2016.06.017
      Issue No: Vol. 71 (2016)
  • Uni- and bi-directional pedestrian flow in the view-limited condition:
           Experiments and modeling
    • Authors: Ning Guo; Qing-Yi Hao; Rui Jiang; Mao-Bin Hu; Bin Jia
      Pages: 63 - 85
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Ning Guo, Qing-Yi Hao, Rui Jiang, Mao-Bin Hu, Bin Jia
      In this paper, the impact of vision on the uni- and bi-directional flow has been investigated via experiment and modeling. In the experiments, pedestrians are asked to walk clockwise/anti-clockwise in a ring-shaped corridor under view-limited condition and normal view condition. As expected, the flow rate under the view-limited condition decreases comparing with that under the normal view condition, no matter in uni- or bi-directional flow. In bidirectional flow, pedestrians segregate into two opposite moving streams very quickly under the normal view condition, and clockwise/anti-clockwise walking pedestrians are always in the inner/outer ring due to right-walking preference. In the first set of experiment, spontaneous lane formation has not occurred under the view-limited condition. Pedestrian flow does not evolve into stationary state. Local congestion occurs and dissipates from time to time. However, in the later sets of experiments, spontaneous lane formation has re-occurred. This is because participants learned from the experience and adapted right-walking preference to avoid collision. To model the flow dynamics, an improved force-based model has been proposed. The driving force has been modified. The right-walking preference has been taken into account. The fact that pedestrians cannot judge the moving direction accurately under limited-view condition has been considered. Simulation results are in good agreement with the experimental ones.

      PubDate: 2016-07-19T13:06:25Z
      DOI: 10.1016/j.trc.2016.07.001
      Issue No: Vol. 71 (2016)
  • Integrated traffic-transit stochastic equilibrium model with park-and-ride
    • Authors: Cristobal Pineda; Cristián E. Cortés; Pedro Jara-Moroni; Eduardo Moreno
      Pages: 86 - 107
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Cristobal Pineda, Cristián E. Cortés, Pedro Jara-Moroni, Eduardo Moreno
      We propose an Integrated Stochastic Equilibrium model that considers both private automobile traffic and transit networks to incorporate the interactions between these two modes in terms of travel time and generalized costs. In addition, in the general version of the model, travelers are allowed to switch from personal vehicles to mass transit at specific locations in a park-and-ride scheme. The assignment for traffic equilibrium is based on the Markovian Traffic Equilibrium model of Baillon and Cominetti (2008), whereas the equilibrium of the transit network is represented by the Stochastic Transit Equilibrium model of Cortés et al. (2013). Stochastic travel decisions are made at the node level, thereby avoiding the enumeration of routes or strategies and incorporating various perception and uncertainty issues. We propose a Method-of-Successive-Averages algorithm to calculate an Integrated Stochastic Equilibrium and conduct numerical experiments to highlight the effect of stochasticity on equilibrium flows and travel times. Our experiments show that higher stochasticity implies greater dispersion of equilibrium flows and longer expected travel times. Results on a real network with mode combination and park and ride facilities provide insights regarding the use of park and ride in terms of number and location, potential modal share of the combined mode option under different circumstances, and travel time impact due to the implementation of such park and ride facilities in a real setting.

      PubDate: 2016-07-19T13:06:25Z
      DOI: 10.1016/j.trc.2016.06.021
      Issue No: Vol. 71 (2016)
  • Multi-step prediction of experienced travel times using agent-based
    • Authors: Hao Chen; Hesham A. Rakha
      Pages: 108 - 121
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Hao Chen, Hesham A. Rakha
      This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.

      PubDate: 2016-07-27T13:10:39Z
      DOI: 10.1016/j.trc.2016.07.004
      Issue No: Vol. 71 (2016)
  • A discrete dynamical system of formulating traffic assignment: Revisiting
           Smith’s model
    • Authors: Ren-Yong Guo; Hai-Jun Huang
      Pages: 122 - 142
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Ren-Yong Guo, Hai-Jun Huang
      Through relaxing the behavior assumption adopted in Smith’s model (Smith, 1984), we propose a discrete dynamical system to formulate the day-to-day evolution process of traffic flows from a non-equilibrium state to an equilibrium state. Depending on certain preconditions, the equilibrium state can be equivalent to a Wardrop user equilibrium (UE), Logit-based stochastic user equilibrium (SUE), or boundedly rational user equilibrium (BRUE). These equivalence properties indicate that, to make day-to-day flows evolve to equilibrium flows, it is not necessary for travelers to choose their routes based on actual travel costs of the previous day. Day-to-day flows can still evolve to equilibrium flows provided that travelers choose their routes based on estimated travel costs which satisfy these preconditions. We also show that, under a more general assumption than the monotonicity of route cost function, the trajectory of the dynamical system converges to a set of equilibrium flows by reasonably setting these parameters in the dynamical system. Finally, numerical examples are presented to demonstrate the application and properties of the dynamical system. The study is helpful for understanding various processes of forming traffic jam and designing an algorithm for calculating equilibrium flows.

      PubDate: 2016-07-27T13:10:39Z
      DOI: 10.1016/j.trc.2016.07.005
      Issue No: Vol. 71 (2016)
  • Influence of connected and autonomous vehicles on traffic flow stability
           and throughput
    • Authors: Alireza Talebpour; Hani S. Mahmassani
      Pages: 143 - 163
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Alireza Talebpour, Hani S. Mahmassani
      The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.

      PubDate: 2016-08-02T00:51:22Z
      DOI: 10.1016/j.trc.2016.07.007
      Issue No: Vol. 71 (2016)
  • A probabilistic model of pedestrian crossing behavior at signalized
           intersections for connected vehicles
    • Authors: Yoriyoshi Hashimoto; Yanlei Gu; Li-Ta Hsu; Miho Iryo-Asano; Shunsuke Kamijo
      Pages: 164 - 181
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Yoriyoshi Hashimoto, Yanlei Gu, Li-Ta Hsu, Miho Iryo-Asano, Shunsuke Kamijo
      Active safety systems which assess highly dynamic traffic situations including pedestrians are required with growing demands in autonomous driving and Connected Vehicles. In this paper, we focus on one of the most hazardous traffic situations: the possible collision between a pedestrian and a turning vehicle at signalized intersections. This paper presents a probabilistic model of pedestrian behavior to signalized crosswalks. In order to model the behavior of pedestrian, we take not only pedestrian physical states but also contextual information into account. We propose a model based on the Dynamic Bayesian Network which integrates relationships among the intersection context information and the pedestrian behavior in the same way as a human. The particle filter is used to estimate the pedestrian states, including position, crossing decision and motion type. Experimental evaluation using real traffic data shows that this model is able to recognize the pedestrian crossing decision in a few seconds from the traffic signal and pedestrian position information. This information is assumed to be obtained with the development of Connected Vehicle.

      PubDate: 2016-08-02T00:51:22Z
      DOI: 10.1016/j.trc.2016.07.011
      Issue No: Vol. 71 (2016)
  • Modeling, calibrating, and validating car following and lane changing
    • Authors: Zuduo Zheng; Majid Sarvi
      Pages: 182 - 183
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zuduo Zheng, Majid Sarvi

      PubDate: 2016-08-06T01:51:32Z
      DOI: 10.1016/j.trc.2016.07.014
      Issue No: Vol. 71 (2016)
  • Data fusion algorithm for macroscopic fundamental diagram estimation
    • Authors: Lukas Ambühl; Monica Menendez
      Pages: 184 - 197
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Lukas Ambühl, Monica Menendez
      A promising framework that describes traffic conditions in urban networks is the macroscopic fundamental diagram (MFD), relating average flow and average density in a relatively homogeneous urban network. It has been shown that the MFD can be used, for example, for traffic access control. However, an implementation requires an accurate estimation of the MFD with the available data sources. Most scientific literature has considered the estimation of MFDs based on either loop detector data (LDD) or floating car data (FCD). In this paper, however, we propose a methodology for estimating the MFD based on both data sources simultaneously. To that end, we have defined a fusion algorithm that separates the urban network into two sub-networks, one with loop detectors and one without. The LDD and the FCD are then fused taking into account the accuracy and network coverage of each data type. Simulations of an abstract grid network and the network of the city of Zurich show that the fusion algorithm always reduces the estimation error significantly with respect to an estimation where only one data source is used. This holds true, even when we account for the fact that the probe penetration rate of FCD needs to be estimated with loop detectors, hence it might also include some errors depending on the number of loop detectors, especially when probe vehicles are not homogeneously distributed within the network.

      PubDate: 2016-08-06T01:51:32Z
      DOI: 10.1016/j.trc.2016.07.013
      Issue No: Vol. 71 (2016)
  • Understanding user acceptance factors of electric vehicle smart charging
    • Authors: Christian Will; Alexander Schuller
      Pages: 198 - 214
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Christian Will, Alexander Schuller
      Smart charging has been the focus of considerable research efforts but so far there is little notion of users’ acceptance of the concept. This work considers potentially influential factors for the acceptance of smart charging from the literature and tests their viability employing a structural equation model, following the partial least squares approach. For a sample of 237 early electric vehicle adopters from Germany our results show that contributing to grid stability and the integration of renewable energy sources are key motivational factors for acceptance of smart charging. In addition, the individual need for flexibility should not be impaired through charging control. Further well known influential factors like economic incentives do not seem to have a significant impact in the sample group under scrutiny. These and further findings should be taken into account by aggregators when designing attractive business models that incentivize the participation of early adopters and ease market rollout.

      PubDate: 2016-08-06T01:51:32Z
      DOI: 10.1016/j.trc.2016.07.006
      Issue No: Vol. 71 (2016)
  • Signal coordination models for long arterials and grid networks
    • Authors: Lihui Zhang; Ziqi Song; Xiaojun Tang; Dianhai Wang
      Pages: 215 - 230
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Lihui Zhang, Ziqi Song, Xiaojun Tang, Dianhai Wang
      This paper proposes two models to tackle traffic signal coordination problems for long arterials and grid networks. Both models, denoted as MaxBandLA and MaxBandGN, are built based on Little’s bandwidth maximization model, and the resulting formulations are both small-sized mixed-integer linear programs. Model MaxBandLA can optimize arterial partition plan and signal coordination plans of all the subsystems simultaneously. Model MaxBandGN directly optimizes the offsets for all the signals in a grid network, and as such, no ’cycle constraints’ need to be constructed. Numerical tests are presented to show that both models have the potential to produce coordination plans that are comparable to signal plans optimized by Synchro.

      PubDate: 2016-08-11T03:43:28Z
      DOI: 10.1016/j.trc.2016.07.015
      Issue No: Vol. 71 (2016)
  • Capturing the conditions that introduce systematic variation in
           bike-sharing travel behavior using data mining techniques
    • Authors: Maria Bordagaray; Luigi dell’Olio; Achille Fonzone; Ángel Ibeas
      Pages: 231 - 248
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Maria Bordagaray, Luigi dell’Olio, Achille Fonzone, Ángel Ibeas
      The potential of smart-card transactions within bike-sharing systems (BSS) is still to be explored. This research proposes an original offline data mining procedure that takes advantage of the quality of these data to analyze the bike usage casuistry within a sharing scheme. A difference is made between usage and travel behavior: the usage is described by the actual trip-chaining gathered with every smart-card transaction and is directly influenced by the limitations of the BSS as a public renting service, while the travel behavior relates to the spatio-temporal distribution, the travel time and trip purpose. The proposed approach is based on the hypothesis that there are systematic usage types which can be described through a set of conditions that permit to classify the rentals and reduce the heterogeneity in travel patterns. Hence, the proposed algorithm is a powerful tool to characterize the actual demand for bike-sharing systems. Furthermore, the results show that its potential goes well beyond that since service deficiencies rapidly arise and their impacts can be measured in terms of demand. Consequently, this research contributes to the state of knowledge on cycling behavior within public systems and it is also a key instrument beneficial to both decision makers and operators assisting the demand analysis, the service redesign and its optimization.

      PubDate: 2016-08-11T03:43:28Z
      DOI: 10.1016/j.trc.2016.07.009
      Issue No: Vol. 71 (2016)
  • Economic analysis of ride-sourcing markets
    • Authors: Liteng Zha; Yafeng Yin; Hai Yang
      Pages: 249 - 266
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Liteng Zha, Yafeng Yin, Hai Yang
      Ride-sourcing refers to an emerging urban mobility service that private car owners drive their own vehicles to provide for-hire rides. This paper analyzes the ride-sourcing market using an aggregate model where the matchings between customers and drivers are captured by an exogenous matching function. It is found that without any regulatory intervention a monopoly ride-sourcing platform will maximize the joint profit with its drivers. On the other hand, the first-best solution is not sustainable when the matching function exhibits increasing returns to scale and the cost function of the platform is subject to economies of scale. Regardless of the examined market scenarios, the average waiting time of customers is proportional to the average searching time of drivers. We establish conditions for regulators to solely regulate the commission charged by the platform to guarantee the second-best. We further investigate the competition of ride-sourcing platforms and find that competition does not necessarily lower the price level or improve social welfare. In the latter case, regulators may rather encourage the merger of the platforms and regulate them directly as a monopolist.

      PubDate: 2016-08-16T12:04:51Z
      DOI: 10.1016/j.trc.2016.07.010
      Issue No: Vol. 71 (2016)
  • Traffic signal control with partial grade separation for oversaturated
    • Authors: Qing He; Ramya Kamineni; Zhenhua Zhang
      Pages: 267 - 283
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Qing He, Ramya Kamineni, Zhenhua Zhang
      Increasing individual vehicular traffic is a major concern all around the world. This leads to more and more oversaturated intersections. Traffic signal control under oversaturated condition is a long-lasting challenge. To address this challenge thoroughly, this paper introduces grade separation at signalized intersections. A lane-based optimization model is developed for the integrated design of grade-separated lanes (e.g. tunnels), lane markings (e.g. left turns, through traffic, right turns, etc.) and signal timing settings. We take into account two types of lane configurations. One is conventional surface lanes controlled by signals, and the other is grade-separated lanes. This problem is formulated as a Mixed Integer Linear Program (MILP), and this can be solved using the regular branch-and-bound methods. The integer decision variables help in finding if the movement is on grade-separated or surface lanes, and also the successor functions to govern the order of signal display. The continuous variables include the assigned lane flow, common flow multiplier, cycle length, and start and duration of green for traffic movements and lanes. The optimized signal time settings and lane configurations are then represented in Vissim simulation. Numerical examples, along with a benefit-cost analysis show the good savings of the proposed optimization model for oversaturated traffic conditions. The benefit-cost ratio for installing 4 grade-separated lanes (as a tunnel) at a heavily oversaturated intersection (intersection capacity utilization rate equal to 1.57) exceeds 5.4.
      Graphical abstract image

      PubDate: 2016-08-16T12:04:51Z
      DOI: 10.1016/j.trc.2016.08.001
      Issue No: Vol. 71 (2016)
  • Spatial-temporal traffic flow pattern identification and anomaly detection
           with dictionary-based compression theory in a large-scale urban network
    • Authors: Zhenhua Zhang; Qing He; Hanghang Tong; Jizhan Gou; Xiaoling Li
      Pages: 284 - 302
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Zhenhua Zhang, Qing He, Hanghang Tong, Jizhan Gou, Xiaoling Li
      Traffic flow pattern identification, as well as anomaly detection, is an important component for traffic operations and control. To reveal the characteristics of regional traffic flow patterns in large road networks, this paper employs dictionary-based compression theory to identify the features of both spatial and temporal patterns by analyzing the multi-dimensional traffic-related data. An anomaly index is derived to quantify the network traffic in both spatial and temporal perspectives. Both pattern identifications are conducted in three different geographic levels: detector, intersection, and sub-region. From different geographic levels, this study finds several important features of traffic flow patterns, including the geographic distribution of traffic flow patterns, pattern shifts at different times-of-day, pattern fluctuations over different days, etc. Both spatial and temporal traffic flow patterns defined in this study can jointly characterize pattern changes and provide a good performance measure of traffic operations and management. The proposed method is further implemented in a case study for the impact of a newly constructed subway line. The before-and-after study identifies the major changes of surrounding road traffic near the subway stations. It is found that new metro stations attract more commute traffic in weekdays as well as entertaining traffic during weekends.

      PubDate: 2016-08-21T12:10:39Z
      DOI: 10.1016/j.trc.2016.08.006
      Issue No: Vol. 71 (2016)
  • A simple reservation and allocation model of shared parking lots
    • Authors: Chaoyi Shao; Hai Yang; Yi Zhang; Jintao Ke
      Pages: 303 - 312
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Chaoyi Shao, Hai Yang, Yi Zhang, Jintao Ke
      With increasing auto demands, efficient parking management is by no means less important than road traffic congestion control. This is due to shortages of parking spaces within the limited land areas of the city centers in many metropolises. The parking problem becomes an integrated part of traffic planning and management. On the other hand, it is a fact that many private parking spots are available during daytime in nearby residential compound because those residents drive their cars out to work. These temporarily vacant parking lots can be efficiently utilized to meet the parking demand of other drivers who are working at nearby locations or drivers who come for shopping or other activities. This paper proposes a framework and a simple model for embracing shared use of residential parking spaces between residents and public users. The proposed shared use is a winning strategy because it maximizes the use of private resources to benefit the community as a whole. It also creates a new business model enabled by the fast-growing mobile apps in our daily lives.

      PubDate: 2016-08-26T14:56:06Z
      DOI: 10.1016/j.trc.2016.08.010
      Issue No: Vol. 71 (2016)
  • Adaptive scheduling for real-time and temporal information services in
           vehicular networks
    • Authors: Penglin Dai; Kai Liu; Liang Feng; Qingfeng Zhuge; Victor C.S. Lee; Sang H. Son
      Pages: 313 - 332
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Penglin Dai, Kai Liu, Liang Feng, Qingfeng Zhuge, Victor C.S. Lee, Sang H. Son
      Vehicular networks represent a research area of significant importance in improving the safety, efficiency and sustainability of transportation systems. One of the key research problems in vehicular networks is real-time data dissemination, which is crucial to the satisfactory performance of many emergent applications providing real-time information services in vehicular networks. Specifically, the two issues need to be addressed in this problem are maintenance of temporal data freshness and timely dissemination of data. Most existing works only considered periodical data update via backbone wired networks in maintaining temporal data freshness. However, many applications rely on passing vehicles to upload their collected information via wireless network, which imposes new challenges as the uplink data update will have to compete with the downlink data dissemination for the limited wireless bandwidth. With such observations, we propose a temporal information service system, in which vehicles are able to collect up-to-date temporal information and upload them to the roadside units (RSU) along their trajectories. Meanwhile, RSU can disseminate its available data items to vehicles based on their specific requests. Particularly, in this paper, we first quantitatively analyze the freshness of temporal data and propose a mathematical model to evaluate the usefulness of the temporal data. Next, we give the formulation of the proposed real-time and temporal information service (RTIS) problem, and prove the NP-hardness of this problem by constructing a polynomial-time reduction from 0–1 knapsack problem. Subsequently, we establish a probabilistic model to theoretically analyze the tradeoff between timely temporal data update and requested data dissemination sharing a common communication resource, which provides a deeper insight of the proposed RTIS. Further, a heuristic algorithm, namely adaptive update request scheduling (AURS), is designed to enhance the efficacy of RTIS by synthesizing the broadcast effect, the real-time service requirement and the service quality in making scheduling decisions. The computational complexity and scalability analysis of AURS is also discussed. Last but not least, a simulation model is implemented and a comprehensive performance evaluation has been carried out to demonstrate the superiority of ARUS against several state-of-the-art approaches in a variety of application scenarios.

      PubDate: 2016-08-26T14:56:06Z
      DOI: 10.1016/j.trc.2016.08.005
      Issue No: Vol. 71 (2016)
  • Heuristic search for the coupled runway sequencing and taxiway routing
    • Authors: Una Benlic; Alexander E.I. Brownlee; Edmund K. Burke
      Pages: 333 - 355
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Una Benlic, Alexander E.I. Brownlee, Edmund K. Burke
      This paper presents the first local search heuristic for the coupled runway sequencing (arrival & departure) and taxiway routing problems, based on the receding horizon (RH) scheme that takes into account the dynamic nature of the problem. As test case, we use Manchester Airport, the third busiest airport in the UK. From the ground movement perspective, the airport layout requires that departing aircraft taxi across the arrivals runway. This makes it impossible to separate arrival from departure sequencing in practice. Operationally, interactions between aircraft on the taxiways could prevent aircraft from taking off from, or landing on, runways during the slots assigned to them by an algorithm optimizing runway use alone. We thus consider the interactions between arrival and departure aircraft on the airport surface. Compared to sequentially optimized solutions, the results obtained with our approach indicate a significant decrease in the taxiway routing delay, with generally no loss in performance in terms of the sequencing delay for a regular day of operations. Another benefit of such a simultaneous optimization approach is the possibility of holding aircraft at the stands for longer, without the engines running. This significantly reduces the fuel burn, as well as bottlenecks and traffic congestion during peak hours that are often the cause of flight delays due to the limited amount of airport surface space available. Given that the maximum computing time per horizon is around 95s, real-time operation might be practical with increased computing power.

      PubDate: 2016-08-26T14:56:06Z
      DOI: 10.1016/j.trc.2016.08.004
      Issue No: Vol. 71 (2016)
  • Second order macroscopic traffic flow model validation using automatic
           differentiation with resilient backpropagation and particle swarm
           optimisation algorithms
    • Authors: Adam Poole; Apostolos Kotsialos
      Pages: 356 - 381
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Adam Poole, Apostolos Kotsialos
      The problem of validating the Modéle d’Écoulement de Trafic sur Autoroute NETworks (METANET) model of a motorway section is considered. Model calibration is formulated as a least squares error minimisation problem with explicit penalisation of fundamental diagram parameter variation. The Automatic Differentiation by Overloading in C++ (ADOL-C) library is incorporated into the METANET source code and is coupled with the Resilient Back Propagation (RPROP) heuristic for solving the minimisation problem. The result is a very efficient system which is able to be calibrate METANET by determining the density and speed equation parameters as well as the fundamental diagrams used. Information obtained from the system’s Jacobian provides extra insight into the dynamics showing how sensitivities propagate into the network. A 22km site near Sheffield, UK, using data from three different days is considered. In addition to the ADOL-C/RPROP system, three particle swarm optimisation algorithms are used for solving the calibration problem. In all cases, the optimal parameter sets found are verified on data not used during calibration. Although, all three sets of data display a similar congestion pattern, the verification process showed that only one of them is capable of leading to parameter sets that capture the underlying dynamics of the traffic flow process.

      PubDate: 2016-08-26T14:56:06Z
      DOI: 10.1016/j.trc.2016.07.008
      Issue No: Vol. 71 (2016)
  • A new rail optimisation model by integration of traffic management and
           train automation
    • Authors: Xiaolu Rao; Markus Montigel; Ulrich Weidmann
      Pages: 382 - 405
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Xiaolu Rao, Markus Montigel, Ulrich Weidmann
      This paper reviews and classifies the traffic optimisation schemes of current mainline railway into two groups. One is to improve the efficiency of traffic management by providing resolutions for traffic conflicts, while the other is to improve trains’ driving behaviour by providing driver assistance or introducing train automation. Based on a comparison of these two groups, this paper proposes to combine the functions of traffic management and train automation into an integrated optimisation model. This model includes the following contributions. First, in the function of traffic management, this paper explores the flexibility in generating different train running trajectories to prevent potential traffic conflicts. The trajectory can improve traffic flow by avoiding unplanned train stops. This is regarded as a supplementary conflict resolution to train reordering or rerouting or retiming. Second, this paper defines a series of train control commands to determine different intensities of the train’s tractive force and braking force. These commands are seen as the key to train automation. Moreover, a decision-making procedure is introduced to select the most attractive train running trajectory or train control command according to different optimisation objectives. Lastly, this paper proves the importance of bidirectional communication between traffic management and train automation based on a case study.

      PubDate: 2016-08-31T07:35:35Z
      DOI: 10.1016/j.trc.2016.08.011
      Issue No: Vol. 71 (2016)
  • Real-time estimation of secondary crash likelihood on freeways using
           high-resolution loop detector data
    • Authors: Chengcheng Xu; Pan Liu; Bo Yang; Wei Wang
      Pages: 406 - 418
      Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71
      Author(s): Chengcheng Xu, Pan Liu, Bo Yang, Wei Wang
      This study aimed to develop a secondary crash risk prediction model on freeways using real-time traffic flow data. The crash and traffic data were collected on the I-880 freeway for five years in California, United States. The secondary crashes were identified by a method based on speed contour plot. The random effect logit model was used to link the probability of secondary crashes with the real-time traffic flow conditions, primary crash characteristics, environmental conditions, and geometric characteristics. The results showed that real-time traffic variables significantly affect the likelihood of secondary crashes. These traffic variables include the traffic volume, average speed, standard deviation of detector occupancy, and volume difference between adjacent lanes. In addition, the primary crash characteristics, environmental conditions and geometric characteristics also significantly affect the risks of secondary crashes. The model evaluation results showed that the predictive performance of the developed model was deemed satisfactory. The inclusion of traffic flow variables and random effect increases prediction accuracy by 16.6% and 7.7%, respectively. These results have the potential to be used in advanced traffic management systems to develop proactive traffic control strategies to prevent the occurrences of secondary crashes on freeways.

      PubDate: 2016-08-31T07:35:35Z
      DOI: 10.1016/j.trc.2016.08.015
      Issue No: Vol. 71 (2016)
  • Editorial Board/Copyright Information
    • Abstract: Publication date: October 2016
      Source:Transportation Research Part C: Emerging Technologies, Volume 71

      PubDate: 2016-09-30T14:34:26Z
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