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  Subjects -> TRANSPORTATION (Total: 170 journals)
    - AIR TRANSPORT (8 journals)
    - AUTOMOBILES (22 journals)
    - RAILROADS (5 journals)
    - ROADS AND TRAFFIC (6 journals)
    - SHIPS AND SHIPPING (34 journals)
    - TRANSPORTATION (95 journals)

TRANSPORTATION (95 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 84)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4)
Archives of Transport     Open Access   (Followers: 17)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 11)
Cities in the 21st Century     Open Access   (Followers: 14)
Economics of Transportation     Partially Free   (Followers: 13)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 10)
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: 7)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 8)
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 8)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 9)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 2)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 9)
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: 11)
International Journal of Services Technology and Management     Hybrid Journal  
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 11)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 15)
International Journal of Transportation Science and Technology     Open Access   (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: 7)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 210)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 11)
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: 8)
Journal of Transport and Land Use     Open Access   (Followers: 22)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 12)
Journal of Transport Geography     Hybrid Journal   (Followers: 21)
Journal of Transport History     Hybrid Journal   (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: 15)
Journal of Transportation Technologies     Open Access   (Followers: 14)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 9)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access   (Followers: 2)
Logistique & Management     Full-text available via subscription  
Mobility in History     Full-text available via subscription   (Followers: 2)
Modern Transportation     Open Access   (Followers: 10)
Nonlinear Dynamics     Hybrid Journal   (Followers: 16)
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: 8)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 13)
Public Transport     Hybrid Journal   (Followers: 18)
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: 2)
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: 14)
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: 26)
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: 32)
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: 34)
Transportation Science     Full-text available via subscription   (Followers: 19)
TRANSPORTES     Open Access   (Followers: 5)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 5)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 2)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 6)
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: 4)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 6)
Транспортні системи та технології перевезень     Open Access  
Journal Cover Transportation Research Part B: Methodological
  [SJR: 3.905]   [H-I: 87]   [29 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0191-2615
   Published by Elsevier Homepage  [3043 journals]
  • Effect of information availability on stability of traffic flow:
           Percolation theory approach
    • Authors: Alireza Talebpour; Hani S. Mahmassani; Samer H. Hamdar
      Pages: 81 - 100
      Abstract: Publication date: Available online 2 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Alireza Talebpour, Hani S. Mahmassani, Samer H. Hamdar
      Connectivity and automation are expected to enhance safety and efficiency in transportation systems. Connectivity will provide information to drivers/autonomous vehicles to enhance decision-making reliability at the operational and tactical levels. Consequently, drivers are more likely to execute safe and efficient maneuvers and autonomous vehicles will have a more accurate perception of the traffic condition and an “error-free” execution of the driving maneuvers. At the operational level, ensuring string stability is a key consideration since unstable traffic flow results in shockwave propagation and possibly crashes. While several studies have examined the effects of information availability on string stability in a connected environment, most of the approaches are focused on automated driving (e.g., Cooperative Adaptive Cruise Control systems) and do not consider a mixed environment with regular, connected, and autonomous vehicles. To ensure connectivity in such a mixed environment, the correlation between communication range and connected vehicles density should be considered. To capture the effects of this correlation, this study uses the Continuum Percolation theory to determine the effects of the vehicular density and communication range on the connectivity level in telecommunications network and consequently, on the string stability of traffic flow. Based on the Continuum Percolation theory, there is a critical density of connected vehicles above which the entire system is connected. This critical density also depends on the communication range. This study presents an analytical derivation of this critical density. Moreover, this study evaluates the string stability under different communication ranges and market penetration rates of connected and autonomous vehicles. Results revealed that as communication range increases, the system becomes more stable and at high communication ranges, the system performs similar to the system with full connectivity. Moreover, results indicated the existence of an optimal communication range to maximize stability and ensure information delivery.

      PubDate: 2017-10-10T02:43:17Z
      DOI: 10.1016/j.trpro.2017.05.006
      Issue No: Vol. 23 (2017)
       
  • On the uniqueness of equilibrated dynamic traffic flow patterns in
           unidirectional networks
    • Authors: Takamasa Iryo; Michael J. Smith
      Pages: 283 - 302
      Abstract: Publication date: Available online 9 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Takamasa Iryo, Michael J. Smith
      Uniqueness of the dynamic user-equilibrium assignment is still an important issue. This paper proves uniqueness with a milder condition compared to past studies and shows another counterexample to the uniqueness. A unidirectional network, in which any node on any shortest route has a unique node potential, is introduced. Orders of vehicles are determined by this node potential so that, given any two vehicles passing through the same node, the lower potential vehicle arrives at the node before the higher potential vehicle. It is shown that, for a unidirectional network in equilibrium, the link travel times and traffic volumes of congested links are uniquely determined. Moreover, a simple non-unidirectional network having multiple equilibria is introduced. This example exhibits importance of unidirectional-network structure to prove uniqueness.

      PubDate: 2017-10-10T02:43:17Z
      DOI: 10.1016/j.trpro.2017.05.017
      Issue No: Vol. 23 (2017)
       
  • Departure time and route choices in bottleneck equilibrium under risk and
           ambiguity
    • Authors: Yang Liu; Yuanyuan Li; Lu Hu
      Pages: 571 - 590
      Abstract: Publication date: Available online 13 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Yang Liu, Yuanyuan Li, Lu Hu
      This paper examines commuters’ departure time and route choices in the morning commute problem when a true distribution of travel time is unknown but belongs to a bounded distributional uncertainty set. The travel preferences towards risk and ambiguity are distinguished by adopting the criterion of ambiguity-aware Constant Absolute Risk Aversion (CARA) travel time. We first examine the dynamic user equilibrium for a single-route model with a homogeneous preference towards risk and ambiguity. Compared with risk-neutral commuters, we find that departure time window is shifted earlier for the risk-averse commuters and shifted later for the risk-seeking commuters. We also study the single bottleneck with a risk-averse class and a risk-seeking class. We show that with a larger gap between the two classes’ preferences, the congestion pattern will change from one peak to two peaks. It implies that preference heterogeneity may stagger the departure time choices and thereby relieve the average congestion. Last, we examine a two-route problem with homogeneous preference. Commuters choose between a fast and risky route (highway) and a slow and safe route (local arterial). We prove the monotonicity of the traffic flow distribution between the two routes with respect to the maximum variation in travel time. Furthermore, we find that reducing the uncertainty on the highway by providing information will reduce the total system cost and the total expected congestion simultaneously for risk-averse commuters. However, it will reduce the total expected congestion but increase the total system cost for risk-seeking commuters. In the numerical section, the price of anarchy is analyzed by varying the risk preference and the ambiguity preference.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trpro.2017.05.032
      Issue No: Vol. 23 (2017)
       
  • Adaptive offsets for signalized streets
    • Authors: Carlos F. Daganzo; Lewis J. Lehe; Juan Argote-Cabanero
      Pages: 612 - 623
      Abstract: Publication date: Available online 14 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Carlos F. Daganzo, Lewis J. Lehe, Juan Argote-Cabanero
      This paper shows that severe congestion on streets controlled by traffic signals can be reduced by dynamically adapting the signal offsets to the prevailing density with a simple rule that keeps the signals’ green-red ratios invariant. Invariant ratios reduce a control policy’s impact on the crossing streets, so a policy can be optimized and evaluated by focusing on the street itself without the confounding factors present in networks. Designed for heavy traffic with spillovers, the proposed policies are adaptive and need little data – they only require average traffic density readings and no demand forecasts. A battery of numerical experiments simulating the dynamics of rush hour traffic on a congested, homogeneous circular street reveals that the proposed form of adaptation reduces the duration of the rush and overall congestion compared with pre-timed control strategies. Eighteen different adaptation policies were considered. All inspect the street densities periodically and simultaneously, and retime the signals immediately thereafter. The period is a fixed multiple of the cycle. The street is evenly divided into sections that contain a set number of consecutive blocks and signals. The offset is the same for all blocks in a section. Three inspection intervals and six section sizes were tested. The latter ranged from a single block/signal to the whole street. It was found that adaptation worked best when sections were large and adaptation frequent. The effects were considerable across all scenarios. For a short street with a short rush and high input flows the probabilistic incidence of gridlock was reduced from 10 to 0%, and the average duration of a trip from 216 to 181 s. For a long street with a long rush and high input flows the gridlock probability was reduced from 23 to 0% and the average trip duration from 2037 to 1143s.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trpro.2017.05.034
      Issue No: Vol. 23 (2017)
       
  • The initial condition problem with complete history dependency in learning
           models for travel choices
    • Authors: C. Angelo Guevara; Yue Tang; Song Gao
      Pages: 758 - 771
      Abstract: Publication date: Available online 9 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): C. Angelo Guevara, Yue Tang, Song Gao
      Learning-based models that capture travelers’ day-to-day learning processes in repeated travel choices could benefit from ubiquitous sensors such as smartphones, which provide individual-level longitudinal data to help validate and improve such models. However, the common problem of missing initial observations in longitudinal data collection can lead to inconsistent estimates of perceived value of attributes in question, and thus inconsistent parameter estimates. In this paper, the stated problem is addressed by treating the missing observations as latent variables in an instance-based learning model that is estimated via maximum simulated likelihood (MSL). The MSL method is implemented in practice using random sampling and importance sampling. Monte Carlo experimentation based on synthetic data shows that both the MSL with random sampling (MSLrs) and MSL with importance sampling (MSLis) are effective in correcting for the endogeneity problem in that the percent error and empirical coverage of the estimators are greatly improved after the correction. Compared to the MSLrs method, the MSLis method is superior in both effectiveness and computational efficiency. Furthermore, MSLis passes a formal statistical test for the recovery of the population values up to a scale with a large number of missing observations, while MSLrs systematically fails due to the curse of dimensionality. The impacts of sampling size in MSLrs and number of high probability choice sequences in MSLis on the methods’ performances are investigated the methods are applied to an experimental route-choice dataset to demonstrate their empirical application. Hausman–McFadden tests show that the estimators after correction are statistically equal to the estimators of the full dataset without missing observations, confirming that the proposed methods are practical and effective for addressing the stated problem.

      PubDate: 2017-10-10T02:43:17Z
      DOI: 10.1016/j.trpro.2017.05.042
      Issue No: Vol. 23 (2017)
       
  • Optimal hyperpaths with non-additive link costs
    • Authors: Saeed Maadi; Jan-Dirk Schmöcker
      Pages: 790 - 808
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Saeed Maadi, Jan-Dirk Schmöcker
      Non-additive fares are common in public transport as well as important for a range of other assignment problems. We discuss the problem of finding optimal hyperpaths under such conditions assuming a cost vector with a limited number of marginal decreasing costs depending on the number of links already traversed. We illustrate that these non-additive costs lead to violation of Bellman's optimality principle which in turn means that standard procedures to obtain optimal destination specific hyperpath trees are not feasible. To overcome the problem we introduce the concepts of a “travel history vector” and critical vs fixed nodes. The former records the expected number of traversed links until a node, and the latter distinguishes nodes for which the fare cost can be determined deterministically. With this we develop a 2-stage solution approach. In the first stage we test whether the optimal hyperpath can be obtained by backward search. If this is not the case, we propose a selective hyperpath generation to a (small) number of critical nodes and combine this with standard hyperpath search. We illustrate our approach by applying it to the Sioux Falls network showing that even for link cost functions (fare stages) with large step changes we are able to obtain all optimal hyperpaths in a reasonable computational time.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trpro.2017.05.044
      Issue No: Vol. 23 (2017)
       
  • Dynamic clustering and propagation of congestion in heterogeneously
           congested urban traffic networks
    • Authors: Mohammadreza Saeedmanesh; Nikolas Geroliminis
      Pages: 962 - 979
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Mohammadreza Saeedmanesh, Nikolas Geroliminis
      The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be studied in the spatiotemporal dimension. Investigating the clustering problem over time in the dynamic domain is critical to better understand and reveal the hidden information during the process of congestion formation and dissolution. The primary motivation of the paper is to study the spatiotemporal relation of congested links, observing congestion propagation from a macroscopic perspective, and finally identifying critical pockets of congestion that can aid the design of peripheral control strategies. To achieve this, we first introduce a static clustering method to partition the heterogeneous network into homogeneous connected sub-regions. The proposed framework guarantees connectivity of the cluster in different steps, which eases the development of a dynamic framework. The proposed clustering approach has 3 steps; firstly, it obtains a set of homogeneous connected components in the network. Each component has a form of sequence which is built by sequentially adding neighboring links with similar level of congestion. Secondly, the major skeleton of clusters is obtained out of this feasible set by minimizing a heterogeneity index. Thirdly, a fine-tuning step is designed to complete the clustering task by assigning the unclustered links of the network to proper clusters while keeping the connectivity. The optimization problem in both second and third step is formulated as a mixed integer linear programming. The approach is also extended to capture spatiotemporal growth and formation of congestion. The dynamic clustering is based on an iterative and fast procedure that considers the spatiotemporal characteristics of congestion propagation and identifies the links with the highest degree of heterogeneity due to time dependent conditions and finally re-cluster them to guarantee connectivity and minimize heterogeneity. An implementation of the developed methodologies in a megacity based on more than 20,000 taxis with GPS highlights the quality of the method due to its fast computation and proper integration of physical properties of congestion.

      PubDate: 2017-09-19T06:24:03Z
      DOI: 10.1016/j.trpro.2017.05.053
      Issue No: Vol. 23 (2017)
       
  • Exogenous priority rules for the capacitated passenger assignment problem
    • Authors: Stefan Binder; Yousef Maknoon; Michel Bierlaire
      Pages: 19 - 42
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Stefan Binder, Yousef Maknoon, Michel Bierlaire
      We propose a novel algorithm for the capacitated passenger assignment problem in public transportation where exogenous priority lists define the order in which passengers are assigned. Separating explicitly theses rules from the assignment procedure allows for a great deal of flexibility to model various priority rules. When the actual rules are endogenous, the framework can easily be embedded in a fixed-point specification. Computational experiments are performed on a realistic case study based on the morning rush hours of the timetable of Canton Vaud, Switzerland. The algorithm is able to assign the demand in very low computational times. The results provide evidences that the ordering of the passengers does not have a significant impact on aggregate performance indicators (such as average delay and level of unsatisfied demand), but that the variability at the individual passenger level is substantial. Thanks to its flexibility, our framework can easily be implemented by a railway operator who wishes to evaluate the effects of different policies in terms of passenger priorities.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.022
      Issue No: Vol. 105 (2017)
       
  • A subjective capacity evaluation model for single-track railway system
           with δ-balanced traffic and λ-tolerance level
    • Authors: Feng Li; Ziyou Gao; David Z.W. Wang; Ronghui Liu; Tao Tang; Jianjun Wu; Lixing Yang
      Pages: 43 - 66
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Feng Li, Ziyou Gao, David Z.W. Wang, Ronghui Liu, Tao Tang, Jianjun Wu, Lixing Yang
      In this paper, we propose a method to measure the capacity of single-track railway corridors subject to a given degree of balance between the two directional traffic loads and a permitted overall delay level. We introduce the concepts of δ-balance degree and λ-tolerance level to reflect the subjective measures of the railway administrator for capacity evaluation. A train balance scheduling problem with initial departure time choice of trains is embedded into the measure of railway capacity. The combined scheduling and capacity evaluation method is formulated as a 0-1 mixed integer programming model, and solved using a simple dichotomization-based heuristic method. A highly efficient heuristic procedure based on the concept of compaction pattern is developed to solve the train balance scheduling problem, and the numerical results demonstrate that the method yields high-quality solutions close to the optimal ones using the CPLEX solver. The two-way traffic loading capacity of a single-track railway corridor is analyzed in detail under different tolerance levels and balance degrees. The transition regions of traffic loading capacity are identified, and provide a useful decision support tool for the railway administrators in dealing with train rescheduling requests under disturbance or disruption scenarios.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.020
      Issue No: Vol. 105 (2017)
       
  • A new solution framework for the limited-stop bus service design problem
    • Authors: Guillermo Soto; Homero Larrain; Juan Carlos Muñoz
      Pages: 67 - 85
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Guillermo Soto, Homero Larrain, Juan Carlos Muñoz
      Limited-stop services are a key element to the successful operation of bus rapid transit corridors. In this study, we present a framework for addressing the limited-stop service design problem over a corridor, and formally introduce a family of subproblems involved in its solution. Using a bi-level optimization approach, we introduce a method of designing these services while considering bus capacity, transfers, and two behavioral models for passengers: deterministic and stochastic. The algorithm and its variants were tested on nine scenarios with up to 80 stops. Working with deterministic passenger assignment, our model solved the problem in a small fraction of the time required by a benchmark algorithm. We use this algorithm to show that neglecting transfers can lead to suboptimal solutions. We finally show that although it makes the problem much harder, working with stochastic assignment leads to more realistic and robust solutions.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.026
      Issue No: Vol. 105 (2017)
       
  • Exact and approximate route set generation for resilient partial
           observability in sensor location problems
    • Authors: Marco Rinaldi; Francesco Viti
      Pages: 86 - 119
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Marco Rinaldi, Francesco Viti
      Sensor positioning is a fundamental problem in transportation networks, as the location of sensors strongly determines how traffic flows are observable and hence manageable. This paper aims to develop a methodology to determine sensor locations on a network such that an optimal trade-off solution is found between the amount of sensors installed and the resilience of the sensor set. In particular, we propose exact and heuristic solutions for identifying the optimal route sets such that no other route would include any additional information for finding optimal full and partial observability solutions. This is an important contribution to sensor location problems, as route-based link flow inference problems have non-unique solutions, strongly depending on the used link-route information. The properties of the new methodology are analyzed and illustrated through different case studies, and the advantages of the algorithms are quantified both for full and for partial observability solutions. Due to the route sets found by our approach, we are able to find full observability solutions characterized by a small number of sensors, while yet being efficient also in terms of partial observability. We perform validation tests on both small and real-life sized network instances.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.007
      Issue No: Vol. 105 (2017)
       
  • An approach to transportation network analysis via transferable utility
           games
    • Authors: Yuval Hadas; Giorgio Gnecco; Marcello Sanguineti
      Pages: 120 - 143
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Yuval Hadas, Giorgio Gnecco, Marcello Sanguineti
      Network connectivity is an important aspect of any transportation network, as the role of the network is to provide a society with the ability to easily travel from point to point using various modes. A basic question in network analysis concerns how “important” each node is. An important node might, for example, greatly contribute to short connections between many pairs of nodes, handle a large amount of the traffic, generate relevant information, represent a bridge between two areas, etc. In order to quantify the relative importance of nodes, one possible approach uses the concept of centrality. A limitation of classical centrality measures is the fact that they evaluate nodes based on their individual contributions to the functioning of the network. The present paper introduces a game theory approach, based on cooperative games with transferable utility. Given a transportation network, a game is defined taking into account the network topology, the weights associated with the arcs, and the demand based on an origin-destination matrix (weights associated with nodes). The network nodes represent the players in such a game. The Shapley value, which measures the relative importance of the players in transferable utility games, is used to identify the nodes that have a major role. For several network topologies, a comparison is made with well-known centrality measures. The results show that the suggested centrality measures outperform the classical ones, and provide an innovative approach for transportation network analysis.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.029
      Issue No: Vol. 105 (2017)
       
  • Multi-periodic train timetabling using a period-type-based Lagrangian
           relaxation decomposition
    • Authors: Wenliang Zhou; Junli Tian; Lijuan Xue; Min Jiang; Lianbo Deng; Jin Qin
      Pages: 144 - 173
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Wenliang Zhou, Junli Tian, Lijuan Xue, Min Jiang, Lianbo Deng, Jin Qin
      To provide passengers with strict regularity of train operation, this research is devoted to modeling and solving the multi-periodic train timetabling problem to simultaneously optimize operation periods, arrival times, and departure times of all period types of trains on a double-track rail network. Based on the construction of a weighted directed graph, a multi-path searching model, namely, a 0-1 linear programming model, is built to minimize the total travel time of all period-types of trains subject to many operational constraints, including station parking capacity and train minimum load factors. After decomposing this model by introducing some Lagrangian multipliers to relax its complicated constraints, a solution algorithm, including a multi-path simultaneous searching sub-algorithm for each period-type of train, is designed to optimize both the feasible and dual solutions, which correspond to the upper and lower bounds, respectively. Finally, the performance, convergence, sensitivity, and practicability of our method are analyzed using many instances on both a small rail network and the high-speed railway between Beijing and Shanghai in China.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.08.005
      Issue No: Vol. 105 (2017)
       
  • Dynamic equilibrium at a congestible facility under market power
    • Authors: Erik T. Verhoef; Hugo E. Silva
      Pages: 174 - 192
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Erik T. Verhoef, Hugo E. Silva
      This paper studies equilibrium and optimum at a congested facility when firms have market power; e.g., when a few airlines jointly use a congested airport. Unlike most of the previous literature, we characterize the equilibrium in terms of timing of arrivals in a continuous-time congestion model when firms simultaneously schedule services. Using the Henderson-Chu dynamic model of flow congestion in a multiple-firm setting, we find that a stable and unique Nash equilibrium in pure strategies always exists. Importantly, it also exists in cases where it fails to exist under bottleneck congestion (notably when the value of schedule late exceeds the value of travel delays). We find that symmetric firms schedule arrivals inefficiently, and strongly concentrated around the desired arrival time so that the peak is shorter and delays are higher than socially optimal. We show that when firms are asymmetric in terms of output, all firms schedule vehicles in the peak center, around the desired arrival time, with arrival windows increasing with firm size such that a smaller firm's window is always fully contained in a larger firm's window and only the largest firm operates in the early and late shoulders. Furthermore, for any pair of asymmetric firms, the larger firm has a higher instantaneous arrival rate at any moment where both firms schedule arrivals. Our results also show that even though self-internalization can be substantial, there is scope for decentralizing the first-best outcome through time-varying tolls.

      PubDate: 2017-09-06T23:31:02Z
      DOI: 10.1016/j.trb.2017.08.028
      Issue No: Vol. 105 (2017)
       
  • On node models for high-dimensional road networks
    • Authors: Matthew A. Wright; Gabriel Gomes; Roberto Horowitz; Alex A. Kurzhanskiy
      Pages: 212 - 234
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Matthew A. Wright, Gabriel Gomes, Roberto Horowitz, Alex A. Kurzhanskiy
      Macroscopic traffic models are necessary for simulation and study of traffic’s complex macro-scale dynamics, and are often used by practitioners for road network planning, integrated corridor management, and other applications. These models have two parts: a link model, which describes traffic flow behavior on individual roads, and a node model, which describes behavior at road junctions. As the road networks under study become larger and more complex — nowadays often including arterial networks — the node model becomes more important. Despite their great importance to macroscopic models, however, only recently have node models had similar levels of attention as link models in the literature. This paper focuses on the first order node model and has two main contributions. First, we formalize the multi-commodity flow distribution at a junction as an optimization problem with all the necessary constraints. Most interesting here is the formalization of input flow priorities. Then, we discuss a very common “conservation of turning fractions” or “first-in-first-out” (FIFO) constraint, and how it often produces unrealistic spillback. This spillback occurs when, at a diverge, a queue develops for a movement that only a few lanes service, but FIFO requires that all lanes experience spillback from this queue. As we show, avoiding this unrealistic spillback while retaining FIFO in the node model requires complicated network topologies. Our second contribution is a “partial FIFO” mechanism that avoids this unrealistic spillback, and a (first-order) node model and solution algorithm that incorporates this mechanism. The partial FIFO mechanism is parameterized through intervals that describe how individual movements influence each other, can be intuitively described from physical lane geometry and turning movement rules, and allows tuning to describe a link as having anything between full FIFO and no FIFO. Excepting the FIFO constraint, the present node model also fits within the well-established “general class of first-order node models” for multi-commodity flows. Several illustrative examples are presented.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.09.001
      Issue No: Vol. 105 (2017)
       
  • Managing disruptions in the multi-depot vehicle scheduling problem
    • Authors: Ezgi Uçar; Ş. İlker Birbil; İbrahim Muter
      Pages: 249 - 269
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Ezgi Uçar, Ş. İlker Birbil, İbrahim Muter
      We consider two types of disruptions arising in the multi-depot vehicle scheduling; the delays and the extra trips. These disruptions may or may not occur during operations, and hence they need to be indirectly incorporated into the planned schedule by anticipating their likely occurrence times. We present a unique recovery method to handle these potential disruptions. Our method is based on partially swapping two planned routes in such a way that the effect on the planned schedule is minimal, if these disruptions are actually realized. The mathematical programming model for the multi-depot vehicle scheduling problem, which incorporates these robustness considerations, possesses a special structure. This special structure causes the conventional column generation method fall short as the resulting problem grows also row-wise when columns are generated. We design an exact simultaneous column-and-row generation algorithm to find a valid lower-bound. The novel aspect of this algorithm is the pricing subproblem, which generates pairs of routes that form recovery solutions. Compromising on exactness, we modify this algorithm in order to enable it to solve practical-sized instances efficiently. This heuristic algorithm is shown to provide very tight bounds on the randomly generated instances in a short computation time.

      PubDate: 2017-09-25T06:31:00Z
      DOI: 10.1016/j.trb.2017.09.002
      Issue No: Vol. 105 (2017)
       
  • A decomposition approach to the static traffic assignment problem
    • Authors: Ehsan Jafari; Venktesh Pandey; Stephen D. Boyles
      Pages: 270 - 296
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Ehsan Jafari, Venktesh Pandey, Stephen D. Boyles
      This paper describes a spatial parallelization scheme for the static traffic assignment problem. In this scheme, which we term a decomposition approach to the static traffic assignment problem (DSTAP), the network is divided into smaller networks, and the algorithm alternates between equilibrating these networks as subproblems, and master iterations using a simplified version of the full network. The simplified network used for the master iterations is based on linearizations to the equilibrium solution for each subnetwork obtained using sensitivity analysis techniques. We prove that the DSTAP method converges to the equilibrium solution on the full network, and demonstrate computational savings of 35–70% on the Austin network. Natural applications of this method are statewide or national assignment problems, or cities with rivers or other geographic features where subnetworks can be easily defined.

      PubDate: 2017-10-02T01:03:08Z
      DOI: 10.1016/j.trb.2017.09.011
      Issue No: Vol. 105 (2017)
       
  • Multi-train trajectory optimization for energy efficiency and delay
           recovery on single-track railway lines
    • Authors: Pengling Wang; Rob M.P. Goverde
      Pages: 340 - 361
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Pengling Wang, Rob M.P. Goverde
      This paper proposes a novel multi-train trajectory optimization for single-track lines. We restrict our attention to delay cases aiming at finding optimal speed profiles, which reduce delays and save energy consumption. A multi-train trajectory optimization method is proposed to find optimal meeting locations, arrival/departure times, and speed trajectories of multiple trains within the time and speed windows. The proposed method first finds timetable constraint sets for trains under delayed situations. The timetable constraint sets provide drivable, feasible, and energy-efficient time and speed windows along the trains’ routes. The multi-train trajectory optimization method uses minimizing energy consumption and reducing delays as the objective functions, and takes into account each train’s operational constraints as well as constraints to avoid conflicts between adjacent trains. Three driving strategies of delay-recovery, energy-efficient and on-time driving, are proposed and combined in the optimization objective selection for different delay scenarios. The multi-train trajectory optimization is formulated as a multiple-phase optimal control problem and solved by a pseudospectral method. The proposed method is applied in case studies of opposite trains running on a Dutch single-track railway corridor with different initial delay scenarios. The results show that our method is able to produce a feasible schedule with energy-efficient speed trajectories for all interacting trains.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trb.2017.09.012
      Issue No: Vol. 105 (2017)
       
  • A microscopic model for optimal train short-turnings during complete
           blockages
    • Authors: Nadjla Ghaemi; Oded Cats; Rob M.P. Goverde
      Pages: 423 - 437
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Nadjla Ghaemi, Oded Cats, Rob M.P. Goverde
      Currently railway traffic controllers use predefined solutions (contingency plans) to deal with a disruption. These plans are manually designed by expert traffic controllers and are specific to a certain location and timetable. With a slight change in the timetable or infrastructure, these plans might not be feasible and have to be updated. Instead traffic controllers can benefit from algorithms that can quickly compute an optimal solution given a disruption specification. This paper presents a Mixed Integer Linear Programming model to compute a disruption timetable when there is a complete blockage and no train can use part of the track for several hours. The model computes the optimal short-turning stations, routes and platform tracks. In this approach short-turning as a common practice in case of complete blockages is modelled at a microscopic level of operational and infrastructural detail to guarantee feasibility of the solution. To demonstrate the functionality and applicability of the model two case studies are performed on two Dutch railway corridors. In the first case, four experiments are presented to show how different priorities can change the optimal solution including the order of services and the choice of short-turning station. In the second case the performance of the model on a big station is investigated. It is shown that the model can compute the optimal solution in a short time.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trb.2017.10.002
      Issue No: Vol. 105 (2017)
       
  • Recasting and optimizing intersection automation as a
           connected-and-automated-vehicle (CAV) scheduling problem: A sequential
           branch-and-bound search approach in phase-time-traffic hypernetwork
    • Authors: Pengfei (Taylor) Li; Xuesong Zhou
      Pages: 479 - 506
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Pengfei (Taylor) Li, Xuesong Zhou
      It is a common vision that connected and automated vehicles (CAVs) will increasingly appear on the road in the near future and share roads with traditional vehicles. Through sharing real-time locations and receiving guidance from infrastructure, a CAV's arrival and request for green light at intersections can be approximately predicted along their routes. When many CAVs from multiple approaches at intersections place such requests, a central challenge is how to develop an intersection automation policy (IAP) to capture complex traffic dynamics and schedule resources (green lights) to serve both CAV requests (interpreted as request for green lights on a particular signal phase at time t) and traditional vehicles. To represent heterogeneous vehicle movements and dynamic signal timing plans, we first formulate the IAP optimization as a special case of machine scheduling problem using a mixed integer linear programming formulation. Then we develop a novel phase-time-traffic (PTR) hypernetwork model to represent heterogeneous traffic propagation under traffic signal operations. Since the IAP optimization, by nature, is a special sequential decision process, we also develop sequential branch-and-bound search algorithms over time to IAP optimization considering both CAVs and traditional vehicles in the PTR hypernetwork. As the critical part of the branch-and-bound search, special dominance and bounding rules are also developed to reduce the search space and find the exact optimum efficiently. Multiple numerical experiments are conducted to examine the performance of the proposed IAP optimization approach.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trb.2017.09.020
      Issue No: Vol. 105 (2017)
       
  • Kinematic wave models of lane-drop bottlenecks
    • Authors: Wen-Long Jin
      Pages: 507 - 522
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Wen-Long Jin
      Lane-drop bottlenecks lead to both capacity reduction and capacity drop, but there are no systematic studies on traffic dynamics, especially the stationary traffic patterns when the upstream link is congested, at such critical bottlenecks within the framework of kinematic wave theory. In this paper, we study three kinematic wave models for both discontinuous and continuous lane-drop bottlenecks, where the number of lanes drops either suddenly or gradually. In the first two models, we apply the multilane LWR model (Lighthill and Whitham, 1955; Richards, 1956) for a discontinuous and continuous lane-drop bottleneck, respectively; in the third model, we assume that the standing wave is instantaneous inside a continuous lane-drop bottleneck. For the first model, we apply the kinematic wave theory developed in Jin et al. (2009) to solve the Riemann problem. In particular, we present an optimization formulation for the entropy condition, solve the stationary states and kinematic waves on both upstream and downstream links, and define instantaneous discontinuous standing waves connecting the upstream and downstream links’ stationary states. For the second model, we define a generalized Riemann problem and show that the asymptotic stationary states and kinematic waves on both links are the same as those in the first model, but the asymptotic standing wave is continuous, comprising of stationary states inside the whole lane-drop zone. Assuming standing waves to be instantaneous as in the first model but continuous as in the second model, we present a new model of a continuous lane-drop bottleneck and a new theoretical framework to solve the generalized Riemann problem. Finally we develop three corresponding Cell Transmission Models and verify theoretical results, especially the presence and structure of continuous standing waves inside a continuous lane-drop zone, with numerical examples. We find that vehicles’ acceleration rates across the standing waves can be infinite in the first model and unrealistically large in the other two and that there is no capacity drop in all of the models. The theoretical framework of the third model forms a basis for a follow-up study, (Jin, 2017), in which we introduce bounded acceleration as an additional constraint on the instantaneous standing waves and present a behavioral model of capacity drop.

      PubDate: 2017-10-17T14:59:19Z
      DOI: 10.1016/j.trb.2017.09.015
      Issue No: Vol. 105 (2017)
       
  • Discrete-time day-to-day dynamic congestion pricing scheme considering
           multiple equilibria
    • Authors: Linghui Han; David Z.W. Wang; Hong K. Lo; Chengjuan Zhu; Xingju Cai
      Pages: 1 - 16
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Linghui Han, David Z.W. Wang, Hong K. Lo, Chengjuan Zhu, Xingju Cai
      In this study, we focus on the discrete-time day-to-day dynamic congestion pricing scheme which varies the toll on a day-to-day basis and aims to drive the traffic system to a given objective traffic equilibrium state. As is well known, due to the asymmetric nature of the travel cost functions, multiple equilibria exist. In this case, without external force, the traffic system cannot converge to the traffic equilibrium state as desired by traffic management through a day-to-day adjustment process if the initial traffic state does not fall into its attraction domain (Bie and Lo, 2010). Therefore, it is imperative for traffic management to propose a traffic control measure to ensure the desired traffic state can be achieved regardless of the initial traffic state. Previous studies on the day-to-day dynamic congestion pricing, either worked on continues-time day-to-day pricing scheme, or took the form of discrete-time day-to-day pricing scheme but did not guarantee the convergence to the desired objective traffic state for the cases when multiple traffic equilibria exist. Both are undesirable. This study aims to develop a discrete-time day-to-day pricing scheme so as to direct the traffic evolution to reach the desired equilibrium from any initial traffic state when multiple traffic equilibria exist. Based on the very general formulation of day-to-day traffic dynamics model, we present a general formulation of such day-to-day pricing schemes and propose a method to obtain one specific road pricing scheme. Moreover, we present rigorous proofs and numerical tests to verify the proposed pricing scheme.

      PubDate: 2017-06-27T03:32:32Z
      DOI: 10.1016/j.trb.2017.06.006
      Issue No: Vol. 104 (2017)
       
  • Determining optimal locations for charging stations of electric
           car-sharing systems under stochastic demand
    • Authors: Georg Brandstätter; Michael Kahr; Markus Leitner
      Pages: 17 - 35
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Georg Brandstätter, Michael Kahr, Markus Leitner
      In this article, we introduce and study a two-stage stochastic optimization problem suitable to solve strategic optimization problems of car-sharing systems that utilize electric cars. By combining the individual advantages of car-sharing and electric vehicles, such electric car-sharing systems may help to overcome future challenges related to pollution, congestion, or shortage of fossil fuels. A time-dependent integer linear program and a heuristic algorithm for solving the considered optimization problem are developed and tested on real world instances from the city of Vienna, as well as on grid-graph-based instances. An analysis of the influence of different parameters on the overall performance and managerial insights are given. Results show that the developed exact approach is suitable for medium sized instances such as the ones obtained from the inner districts of Vienna. They also show that the heuristic can be used to tackle very-large-scale instances that cannot be approached successfully by the integer-programming-based method.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.009
      Issue No: Vol. 104 (2017)
       
  • An agent-based day-to-day adjustment process for modeling ‘Mobility as a
           Service’ with a two-sided flexible transport market
    • Authors: Shadi Djavadian; Joseph Y.J. Chow
      Pages: 36 - 57
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Shadi Djavadian, Joseph Y.J. Chow
      Due to advances in communications technologies and social networks, flexible mobility systems such as taxi, carpool and demand responsive transit have gained interest among practitioners and researchers as a solution to address such problems as the ``first/last mile problem". While recent research has modeled these systems using agent-based stochastic day-to-day processes, they assume only traveler adjustment under a one-sided market setting. What if such systems are naturally ``two-sided markets" like Uber or AirBnB?In this study, we explore flexible transport services in the framework of two-sided markets, and extend an earlier day-to-day adjustment process to include day-to-day adjustment of the service operator(s) as the seller and the built environment as the platform of a two-sided market. We use the Ramsey pricing criterion for social optimum to show that a perfectly matched state from a day-to-day process is equivalent to a social optimum. A case study using real data from Oakville, Ontario, as a first/last mile problem example demonstrates the sensitivity of the day-to-day model to operating policies. Computational experiments confirm the existence of locally stable states. More importantly, the experiments show the existence of thresholds from which network externalities cause two-sided and one-sided market equilibria to diverge.
      Graphical abstract image

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.015
      Issue No: Vol. 104 (2017)
       
  • Investigation of the traffic congestion during public holiday and the
           impact of the toll-exemption policy
    • Authors: Yue Bao; Feng Xiao; Zaihan Gao; Ziyou Gao
      Pages: 58 - 81
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Yue Bao, Feng Xiao, Zaihan Gao, Ziyou Gao
      Traffic congestion has long been a noticeable issue worldwide. Besides congestion caused by the daily commuters, congestion during public holidays is also very typical. The traffic volume often has a sharp increase during public holidays, which puts a heavy burden on the road capacity and results in severe congestion. This is especially true for the beginning and ending of the holidays. The situation is even worse under some government policies designed initially to benefit people, e.g. the highway toll-exemption during public holidays in China. The focus of this paper is to model the evolution of traffic congestion caused by the demand from residential place to the famous resorts during public holidays. The research questions include: (1) how do tourists tradeoff between schedule delay, queuing time and the overcrowding of the resort' and (2) the impact of the toll-exemption policy during public holidays on tourists’ departure time choices and the social welfare. By adopting the bottleneck model, we obtain the cumulative departure curves of tourists during public holidays. Closed-form results of tourists’ departure time variation with the toll-exemption policy are obtained, as well as the resulting social efficiency loss, which is significant for the management of the traffic mobility during public holidays.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.05.011
      Issue No: Vol. 104 (2017)
       
  • Resilient facility location against the risk of disruptions
    • Authors: Guodong Yu; William B. Haskell; Yang Liu
      Pages: 82 - 105
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Guodong Yu, William B. Haskell, Yang Liu
      In this paper, we consider an uncapacitated facility location problem (RUFL) with random facility disruptions. We develop risk-averse optimization formulations to compute resilient location and customer assignment solutions for two cases (i.e., under either independent or correlated disruptions), where the risks are expressed through a family of risk measures including conditional value-at-risk (CVaR) and absolute-semideviation (ASD). The risk-averse RUFL with independent facility disruptions is to control the risks at each individual customer and modeled as a mixed-integer nonlinear programming, which is challenging to be solved. In response, we develop a branch-and-cut algorithm combined with augmented Lagrangian decomposition for globally optimizing the problem. As for the risk-averse RUFL with correlated facility disruptions, we propose a scenario-based model to minimize the total fixed costs and risks across the entire customer set. The resulting formulation is a pure MILP and a Lagrangian decomposition scheme is proposed for computational aspects in large-scale cases. Our numerical results show that the risk-averse models outperform the classic risk-neutral models in improving the reliability. Experiments demonstrate that our proposed algorithms perform well. To conclude, we extract managerial insights that suggest important guidelines for controlling risk in the face of disruption.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.014
      Issue No: Vol. 104 (2017)
       
  • Simultaneous estimation of states and parameters in Newell’s simplified
           kinematic wave model with Eulerian and Lagrangian traffic data
    • Authors: Zhe Sun; Wen-Long Jin; Stephen G. Ritchie
      Pages: 106 - 122
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Zhe Sun, Wen-Long Jin, Stephen G. Ritchie
      The traffic state estimation process estimates various traffic states from available data in a road network and provides valuable information for travelers and decision makers to improve both travel experience and system performance. In many existing methods, model parameters and initial states have to be given in order to estimate traffic states, which limits the accuracy of the results as well as their transferability to different locations and times. In this paper, we propose a new framework to simultaneously estimate model parameters and traffic states for a congested road segment based on Newell’s simplified kinematic wave model (Newell, 1993). Given both Eulerian traffic count data and Lagrangian vehicle reidentification data, we formulate a single optimization problem in terms of the initial number of vehicles and model parameters. Then we decouple the optimization problem such that the initial number of vehicles can be analytically solved with a closed-form formula, and the model parameters, including the jam density and the shock wave speed in congested traffic, can be computed with the Gauss-Newton method. Based on Newell’s model, we can calculate individual vehicles’ trajectories as well as the average densities, speeds, and flow-rates inside the road segment. We also theoretically show that the optimization problem can have multiple solutions under absolutely steady traffic conditions. We apply the proposed method to the NGSIM datasets, verifying the validity of the method and showing that this method yields better results in the estimation of average densities than existing methods.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.012
      Issue No: Vol. 104 (2017)
       
  • A predictive-control framework to address bus bunching
    • Authors: Matthias Andres; Rahul Nair
      Pages: 123 - 148
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Matthias Andres, Rahul Nair
      Busy bus routes often suffer from buses not arriving at regular intervals but in bunches at bus stops. In this paper we study this bus bunching phenomenon and address it by a combination of data-driven headway prediction and dynamic holding strategies, which allow to modulate buses’ dwell times at stops to reduce the headway deviation. We formulate time headways as time series and compare several prediction methods by testing on data from a busy bus route in Dublin. Furthermore we review and extend an analytical model of an artificial bus route and discuss stability properties and dynamic holding strategies using both data available at the time and predicted headway data. In a numerical simulation we illustrate how the combination of two simple concepts lead to a promising strategy to reduce bus bunching.

      PubDate: 2017-07-08T08:56:27Z
      DOI: 10.1016/j.trb.2017.06.013
      Issue No: Vol. 104 (2017)
       
  • Train timetabling by skip-stop planning in highly congested lines
    • Authors: Feng Jiang; Valentina Cacchiani; Paolo Toth
      Pages: 149 - 174
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Feng Jiang, Valentina Cacchiani, Paolo Toth
      We study the problem of scheduling passenger trains in a highly congested railway double-track line with the aim of increasing the number of scheduled trains. A feasible timetable of the trains currently scheduled in the network is given. Additional trains should be scheduled to meet the increasing passenger demand. To achieve this goal, we are allowed to increase the dwelling time of some trains at some stations, to let them stop at some additional stations and even to skip a few stops. Thereby, we need to take explicitly into account the deceleration and acceleration times that are needed by the train when it stops at a station. This problem integrates the choice of the train schedule with the choice of the train stops, the latter being usually made in the Line Planning process. To solve this problem, we propose a heuristic algorithm, extended from a previous method to include the new features of the studied application, and show its performance on real-world instances of the Chinese high-speed JingHu corridor (between Beijing and Shanghai) involving up to 387 trains.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.06.018
      Issue No: Vol. 104 (2017)
       
  • Modelling bus bunching and holding control with vehicle overtaking and
           distributed passenger boarding behaviour
    • Authors: Weitiao Wu; Ronghui Liu; Wenzhou Jin
      Pages: 175 - 197
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Weitiao Wu, Ronghui Liu, Wenzhou Jin
      Headway fluctuation and bus bunching are commonly observed in transit operations, while holding control is a proven strategy to reduce bus bunching and improve service reliability. A transit operator would benefit from an accurate forecast of bus propagation in order to effectively control the system. To this end, we propose an ‘ad-hoc’ bus propagation model taking into account vehicle overtaking and distributed passenger boarding (DPB) behaviour. The latter represents the dynamic passenger queue swapping among buses when bunching at bus stops occurs and where bus capacity constraints are explicitly considered. The enhanced bus propagation model is used to build the simulation environment where different holding control strategies are tested. A quasi first-depart-first-hold (FDFH) rule is applied to the design of schedule- and headway-based holding control allowing for overtaking, with the objective to minimise the deviation from the targeted headway. The effects of control strategies are tested in an idealised bus route under different operational setting and in a real bus route in Guangzhou. We show that when the combined overtaking and queue-swapping behaviour are considered, the control strategies can achieve better headway regularity, less waiting time and less on-board travel time than their respective versions without overtaking and DPB. The benefit is even greater when travel time variability is higher and headway is smaller, suggesting that the control strategies are preferably deployed in high-frequency service.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.06.019
      Issue No: Vol. 104 (2017)
       
  • Speed optimization over a path with heterogeneous arc costs
    • Authors: Qie He; Xiaochen Zhang; Kameng Nip
      Pages: 198 - 214
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Qie He, Xiaochen Zhang, Kameng Nip
      The speed optimization problem over a path aims to find a set of speeds over each arc of the given path to minimize the total cost, while respecting the time-window constraint at each node and speed limits over each arc. In maritime transportation, the cost represents fuel cost or air pollutant emissions, so study of this problem has significant economic and environmental impacts. To accommodate different fuel and emission models, we allow the dependence of the cost on the speed to be a general continuously differentiable and strictly convex function, and different across the arcs. We develop an efficient algorithm that is able to solve instances of 1000 nodes in less than a second. The algorithm is 20 to 100 times faster than a general convex optimization solver on test instances and requires much less memory. The solutions found at intermediate steps of our algorithm also provide some insights to ship planners on how to balance the operating cost and service quality.

      PubDate: 2017-07-21T10:44:54Z
      DOI: 10.1016/j.trb.2017.07.004
      Issue No: Vol. 104 (2017)
       
  • Modeling the dynamics of congestion in large urban networks using the
           macroscopic fundamental diagram: User equilibrium, system optimum, and
           pricing strategies
    • Authors: Mahyar Amirgholy; H. Oliver Gao
      Pages: 215 - 237
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Mahyar Amirgholy, H. Oliver Gao
      The macroscopic fundamental diagram (MFD) is introduced in recent studies to present the relationship between the flow and the density of the network in large urban regions (neighborhoods). The MFD can be also rescaled to approximate network outflow as a function of the vehicular accumulation of the system in the morning commute problem. In this research, we develop a bathtub model (macro-scale traffic congestion model) by combining Vickrey's (1969) model of dynamic congestion with the MFD to formulate the user equilibrium over the peak as an ordinary differential equation (ODE). This problem can be solved numerically to estimate the exact solution of the morning commute problem. Alternatively, the morning commute problem can be solved analytically by approximating the solution of the ODE using a well-behaved function. Here, we present a quadratic and also a linear approximation of the equilibrium solution for a semi-quadratic MFD, considering that the declining part of the MFD is shown to be well estimated by a quadratic function. To optimize the system, we present pricing strategies for network users (dynamic tolling) and employers inside the region (dynamic taxing) that can minimize the generalized cost of the system by keeping the outflow maximized over the peak. Finally, we compare the exact and the approximate solutions of the problem, and also the proposed pricing strategies of the region in a numerical example.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.07.006
      Issue No: Vol. 104 (2017)
       
  • A fast simulation algorithm for multiple moving bottlenecks and
           applications in urban freight traffic management
    • Authors: Michele D. Simoni; Christian G. Claudel
      Pages: 238 - 255
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Michele D. Simoni, Christian G. Claudel
      Moving bottlenecks are moving capacity restrictions that affect traffic flows, and they can be used to describe the effects of buses and trucks in transportation networks. The computation of solutions associated with the presence of moving bottlenecks is complex, since they both influence and are influenced by surrounding traffic. In this study, we propose a fast numerical scheme that can efficiently compute the solutions to an arbitrary number of moving (and fixed) bottlenecks, for a stretch of road modeled by the Lighthill–Whitham–Richards (LWR) model. Several different moving bottlenecks can be simulated endogenously all together by means of an algorithm based on a semi-analytic Lax–Hopf formula. Since the numerical scheme is semi-analytic and requires a very low number of operations, it can be employed for traffic estimation problems where fast and accurate solutions are required. We demonstrate the capabilities of the method by implementing two alternative traffic management strategies designed to minimize the negative impacts of trucks and buses in urban environments.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.06.010
      Issue No: Vol. 104 (2017)
       
  • On the stochastic fundamental diagram for freeway traffic: Model
           development, analytical properties, validation, and extensive applications
           
    • Authors: Xiaobo Qu; Jin Zhang; Shuaian Wang
      Pages: 256 - 271
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Xiaobo Qu, Jin Zhang, Shuaian Wang
      In this research, we apply a new calibration approach to generate stochastic traffic flow fundamental diagrams. We first prove that the percentile based fundamental diagrams are obtainable based on the proposed model. We further prove the proposed model has continuity, differentiability and convexity properties so that it can be easily solved by Gauss–Newton method. By selecting different percentile values from 0 to 1, the speed distributions at any given densities can be derived. The model has been validated based on the GA400 data and the calibrated speed distributions perfectly fit the speed-density data. This proposed methodology has wide applications. First, new approaches can be proposed to evaluate the performance of calibrated fundamental diagrams by taking into account not only the residual but also ability to reflect the stochasticity of samples. Secondly, stochastic fundamental diagrams can be used to develop and evaluate traffic control strategies. In particular, the proposed stochastic fundamental diagram is applicable to model and optimize the connected and automated vehicles at the macroscopic level with an objective to reduce the stochasticity of traffic flow. Last but not the least, this proposed methodology can be applied to generate the stochastic models for most regression models with scattered samples.

      PubDate: 2017-07-27T06:31:09Z
      DOI: 10.1016/j.trb.2017.07.003
      Issue No: Vol. 104 (2017)
       
  • Efficient and fair system states in dynamic transportation networks
    • Authors: Feng Zhu; Satish V. Ukkusuri
      Pages: 272 - 289
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Feng Zhu, Satish V. Ukkusuri
      This paper sets out to model an efficient and fair transportation system accounting for both departure time choice and route choice of a general multi-OD network within a dynamic traffic assignment environment. Firstly, a bi-level optimization formulation is introduced based on the link-based traffic flow model. The upper level of the formulation minimizes the total system travel time, whereas the lower level captures traffic flow propagation and the user equilibrium constraints. Then the bi-level formulation is relaxed to a linear programming formulation that produces a lower bound of an efficient and fair system state. An efficient iterative algorithm is proposed to obtain the exact solution. It only requires solving one linear program in one iteration. Further, it is shown that the number of iterations is bounded, and the output traffic flow pattern is efficient and fair. Finally, two numerical cases (including a single OD network and a multi-OD network) are conducted to demonstrate the performance of the algorithm. The results consistently show that the departure rate pattern generated from the algorithm leads to an efficient and fair system state, and the algorithm converges within two iterations across all test scenarios.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.07.010
      Issue No: Vol. 104 (2017)
       
  • The decentralized field service routing problem
    • Authors: Edison Avraham; Tal Raviv; Eugene Khmelnitsky
      Pages: 290 - 316
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Edison Avraham, Tal Raviv, Eugene Khmelnitsky
      Companies that provide service at geographically dispersed locations face the problem of determining the technician that will serve each location as well as setting the best route for each technician. Such a scenario is known as the field service routing problem. Large companies often outsource their field service tasks to several contractors. Each contractor may serve several companies. Since the contractors cannot share the information about the tasks of their other clients, the most common practice involves allocating the tasks to the contractors heuristically based on geographical considerations. In this approach, the tasks for which the contractors have already been committed to other companies are not considered. As a result, the allocation of new tasks can be inefficient. This study develops 2-stage task allocation mechanisms that cope with the problem and result in nearly optimal allocations. In the first stage, a feasible allocation of tasks to contractors is generated. We consider two possible allocation procedures: sequential combinatorial auctions and sequential negotiations. The sequential combinatorial auctions procedure implements the Generalized Vickrey auction, which is a strategy-proof mechanism for the allocation of multiple goods among several competing agents. A sequential negotiation method is suggested as an alternative task allocation mechanism. The method automates a multi-lateral negotiation process in which the company is the leader, and the contractors are followers. In the second stage, the contractors are allowed to exchange the tasks among themselves so as to decrease their operational costs. The exchanges may or may not include money transfers. We found that the first-stage procedures yield fairly efficient allocations and the second stage further improves them. The obtained allocations are considerably more efficient than the solutions generated by a reasonable benchmark heuristic. Moreover, the allocations' costs are close to a lower bound established by the optimal allocation of a central planner. That is, the price of decentralization is shown to be small.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.07.005
      Issue No: Vol. 104 (2017)
       
  • Strategic entry to regional air cargo market under joint competition of
           demand and promised delivery time
    • Authors: Fan Wang; Xiaopo Zhuo; Baozhuang Niu
      Pages: 317 - 336
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Fan Wang, Xiaopo Zhuo, Baozhuang Niu
      In air cargo industry, mainline carrying and regional carrying are complementary services that form an air cargo service supply chain. Recently, many mainline carriers (MCs) have strategically entered upstream regional carrying service market to offer “one-stop-delivery” service and hence, competed with incumbent regional carriers (RCs). Note that promised delivery time (PDT) competition is essential and common in this industry. We study a MC's entry decision using a joint demand and PDT competition model. We investigate the entry mode issue (fully-controlled or joint-venture), which influences the equilibrium profits and channel structure, and characterize the value of upstream competition and vertical cooperation between the MC and incumbent RC. Interestingly, we find that the MC's upstream entry can result in a win-win situation, or a lose-lose situation for the MC and the incumbent RC. Comparing parties’ profits with and without PDT competition, we find that multi-dimensional competition may weaken the negative effect of upstream entry on the incumbent RC, resulting in a price advantage and PDT disadvantage for the MC. We also find that a fully-controlled entry mode is always a dominant strategy with or without PDT competition. Moreover, by assuming power distribution of the PDT, we find that the increase in service rate can result in a lower price and shorter PDT quotation for the MC. A(n) decrease (increase) of service rate strengthens (weakens) the PDT disadvantage, and this effect is strengthened with fully-controlled entry mode. We also examine Bertrand models and characterize the entry effects and the MC's entry decisions under joint price and PDT competition.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.002
      Issue No: Vol. 104 (2017)
       
  • Effects of risk-aversion on competing shipping lines’ pricing strategies
           with uncertain demands
    • Authors: Wei Zheng; Bo Li; Dong-Ping Song
      Pages: 337 - 356
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Wei Zheng, Bo Li, Dong-Ping Song
      Container shipping is facing severe overcapacity, fierce price-based competition and high demand uncertainty. It is natural that some shipping lines may adopt a risk-aversion attitude in their pricing strategies. This paper considers the pricing strategies of two competing ocean carriers facing uncertain demand. The first carrier is risk-neutral with sufficient capacity, whereas the second carrier is risk-averse with limited capacity. The conditional value at risk (CVaR) is used to measure the risk-averse attitude of the second carrier. A Nash game model is formulated to model the pricing decisions and the equilibrium solution is obtained. We find that the pricing solution takes two forms, which can be determined by a threshold value of carrier 2’s capacity. Under uniformly distributed demand, we show that as the second carrier becomes more risk-averse, both carriers’ optimal prices are decreasing, and the threshold value that determines the pricing strategy is also decreasing. We also analyze the impact of price sensitivity and competition intensity parameters on two carriers’ price decisions under more specific conditions. A necessary and sufficient condition is established to determine whether two carriers’ optimal prices would be positively or negatively affected by the competition intensity parameter. A range of numerical experiments are provided to illustrate the analytical results and explore their validity in more general cases. Moreover, it is shown that the main analytical results in this paper can carry over to the cases when both carriers are risk-averse.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.004
      Issue No: Vol. 104 (2017)
       
  • Cruising for parking around a circle
    • Authors: Richard Arnott; Parker Williams
      Pages: 357 - 375
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Richard Arnott, Parker Williams
      Several recent papers have used the approximation that the number of curbside parking spaces searched before finding a vacant space equals the reciprocal of the expected curbside vacancy rate. The implied expected cruising-for-parking times are significantly lower than those that have been obtained through observation and simulation. Through computer simulation of cars cruising for parking around a circle in stochastic steady state, this paper shows that the approximation leads to underestimation of expected cruising-for-parking time and, at high occupancy rates, considerable underestimation. The paper also identifies several “effects” that contribute to the approximation being an increasingly poor one as the occupancy rate increases.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.07.009
      Issue No: Vol. 104 (2017)
       
  • Group-based hierarchical adaptive traffic-signal control part I:
           Formulation
    • Authors: Seunghyeon Lee; S.C. Wong; Pravin Varaiya
      Pages: 376 - 397
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Seunghyeon Lee, S.C. Wong, Pravin Varaiya
      A group-based adaptive traffic-control method for isolated signalized junctions is developed that includes a hierarchical structure comprising tactical and local levels of signal timing optimization. The control method optimizes the signal timings in adaptive traffic-control systems, and takes full advantage of flexible new technologies to incorporate the most up-to-date traffic information, as collected in real time. The definitions, combinations, and sequencing of the cycle structure stages are generated automatically using a procedure for optimizing the signal-timing plans in response to online data from traffic detectors. This new method provides a wider search space and improves the efficiency of the signal-control systems, thus improving the junction performance, minimizing delays, and maximizing capacity in real time. A multi-resolution strategy is proposed for updating the elements of the signal plans cycle-by-cycle and adjusting the current green signal timing second-by-second. The group-based variables and parameters for the proactive global-optimization method utilize lane-based predictive traffic-flow information, such as arrival and discharge rates, expressed as the slopes of polygonal delay formulas. Therefore, there is a high degree of flexibility in the tactical identification of the optimal signal plan in response to the real-time predicted traffic information, the objective function of the polygonal delay formula, and the direct differential equations for the adaptive group-based variables. The reactive local signal-control policy, which is formed based on the max-pressure strategy, is developed to locally adjust the current green signal time and to accommodate delicate demand fluctuations second-by-second at the fine-resolution level. The most appropriate cycle-structure for the tactical level of control is identified using a group-based global-optimization procedure that takes advantage of the latest available information. In part II of this study (Lee et al. 2017), the effectiveness of the proposed methods is validated based on the actualized mathematical frameworks, computer simulations, and a case study, using the appropriate computer programs.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.009
      Issue No: Vol. 104 (2017)
       
  • Group-based hierarchical adaptive traffic-signal control Part II:
           Implementation
    • Authors: Seunghyeon Lee; S.C. Wong; Pravin Varaiya
      Pages: 376 - 397
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Seunghyeon Lee, S.C. Wong, Pravin Varaiya
      In part I of this study (Lee et al., 2017), the formulation of a theoretical framework for a group-based adaptive traffic-control method for isolated signalized junctions is presented, which includes tactical and local levels of signal timing optimization. The global level control aims to determine the time-varying cycle structure, with a resolution of cycles, and the real-time adjustment of the green phase, with a resolution of seconds, based on longer-term traffic information observed by traffic detectors. Overall, the purpose of the study is to actualize a multi-resolution strategy for a group-based adaptive signal-control method and establish a microscopic simulation platform to implement the proposed methodology and test its effectiveness. To actualize the global proactive-optimization scheme, in this paper, a rolling-horizon approach to the temporal and spatial variables, signal structures for four-arm intersections, and discrete directional search methods is applied using the developed mathematical framework. The formulation of the group-based max-pressure policy is realized using the logical form of the local reactive-control policy at a typical directional three-lane, four-arm approach to an isolated intersection. The integrated group-based adaptive traffic-signal control is actualized using VISSIM, Fortran, and VBA based on the developed tactical and local levels of signal timing optimization. The results of the computer simulations and the case study presented in this paper show that the integrated group-based adaptive traffic-signal-control logic outperforms the other methods over a wide range of traffic conditions, from free-flowing traffic to extreme congestion. Moreover, the proposed models perform much better than the existing fixed-signal plan and the actuated signal-control in asymmetric traffic conditions.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.009
      Issue No: Vol. 104 (2017)
       
  • ℓ1-minimization method for link flow correction
    • Authors: Penghang Yin; Zhe Sun; Wen-Long Jin; Jack Xin
      Pages: 398 - 408
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Penghang Yin, Zhe Sun, Wen-Long Jin, Jack Xin
      A computational method, based on ℓ1-minimization, is proposed for the problem of link flow correction, when the available traffic flow data on many links in a road network are inconsistent with respect to the flow conservation law. Without extra information, the problem is generally ill-posed when a large portion of the link sensors are unhealthy. It is possible, however, to correct the corrupted link flows accurately with the proposed method under a recoverability condition if there are only a few bad sensors which are located at certain links. We analytically identify the links that are robust to miscounts and relate them to the geometric structure of the traffic network by introducing the recoverability concept and an algorithm for computing it. The recoverability condition for corrupted links is simply the associated recoverability being greater than 1. In a more realistic setting, besides the unhealthy link sensors, small measurement noises may be present at the other sensors. Under the same recoverability condition, our method guarantees to give an estimated traffic flow fairly close to the ground-truth data and leads to a bound for the correction error. Both synthetic and real-world examples are provided to demonstrate the effectiveness of the proposed method.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.006
      Issue No: Vol. 104 (2017)
       
  • Testing the slope model of scheduling preferences on stated preference
           data
    • Authors: Dereje Abegaz; Katrine Hjorth; Jeppe Rich
      Pages: 409 - 436
      Abstract: Publication date: October 2017
      Source:Transportation Research Part B: Methodological, Volume 104
      Author(s): Dereje Abegaz, Katrine Hjorth, Jeppe Rich
      The valuation of travel time variability is derived either from a structural model, given information on departure time, or directly from a reduced-form model where departure time is assumed to be optimally chosen. The two models are theoretically equivalent under certain assumptions, hence are expected to yield similar results. We use stated preference data to compare the valuation of travel time variability under a structural model where trip-timing preferences are defined in terms of time-dependent utility rates, the “slope model”, against its reduced-form model. Two choice experiments are used that are identical except one has a fixed departure time while the other allows respondents to choose departure time freely. The empirical results in this paper do not support the theoretical equivalence of the two models as the implied value of travel time variability under the reduced-form model is an order of magnitude larger. This finding, which is robust to various specification tests, is in line with a recent Swedish study by Börjesson, Eliasson and Franklin [Transportation Research Part B: Methodological, 46(7), 855–873 (2012)]. Since our data allows a direct comparison of the two approaches, we are able to rule out some potential explanations lined up by past research for the observed discrepancy between the two models.

      PubDate: 2017-09-01T01:25:08Z
      DOI: 10.1016/j.trb.2017.08.001
      Issue No: Vol. 104 (2017)
       
  • Optimal environmental road pricing and daily commuting patterns
    • Authors: Jessica Coria; Xiao-Bing Zhang
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Jessica Coria, Xiao-Bing Zhang
      Road pricing can improve air quality by reducing and spreading traffic flows. Nevertheless, air quality does not depend only on traffic flows, but also on pollution dispersion. In this paper we investigate the effects of the temporal variation in pollution dispersion on optimal road pricing, and show that time-varying road pricing is needed to make drivers internalize the social costs of both time-varying congestion and time-varying pollution. To this end, we develop an ecological economics model that takes into account the effects of road pricing on daily commuting patterns. We characterize the optimal road pricing when pollution dispersion varies over the day and analyze its effects on traffic flows, arrival times, and the number of commuters by car.

      PubDate: 2017-10-10T02:43:17Z
       
  • A unified follow-the-leader model for vehicle, bicycle and pedestrian
           traffic
    • Authors: Yongxiang Zhao; H.M. Zhang
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Yongxiang Zhao, H.M. Zhang
      In this research we performed new bicycle and pedestrian experiments to supplement data extracted from existing follow-the-leader experiments in vehicles, bicycles and pedestrians, and studied their spacetime trajectories and flow-density (or spacing-velocity) phase diagrams. The strong similarities in the spacetime trajectories and the bi-variate phase plots as well as the relative consistence of the estimated proportionality parameter across all three types of traffic, suggest that a unified behavioral mechanism is at play in human-driven traffic. It is suggested that this mechanism is essentially a safety-driven behavior that vehicles, bicycles or pedestrians adopt a safe speed for a given spacing between them. This behavior is well described by a well-known model in vehicular traffic and it is shown in this paper that a scaled version of this model applies to all three types of traffic. A unified relaxation-driven social force traffic model is then proposed to incorporate this behavior mechanism. Simulations with the same setup as the real-life experiments were carried out for vehicle, bicycle, and pedestrian traffic using the unified traffic model and the simulated spacetime trajectories and fundamental diagrams show remarkable consistence with the experimental results.

      PubDate: 2017-10-10T02:43:17Z
       
  • Dynamical capacity drop in a nonlinear stochastic traffic model
    • Authors: Wei-Liang Qian; Adriano Siqueira Romuel Machado Kai Lin Ted Grant
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Wei-Liang Qian, Adriano F. Siqueira, Romuel F. Machado, Kai Lin, Ted W. Grant
      In this work, we show that the inverse-λ shape in the fundamental diagram of traffic flow can be produced dynamically by a simple nonlinear mesoscopic model with stochastic noises. The proposed model is based on the gas-kinetic theory of the traffic system. In our approach, the nonlinearity leads to the coexistence of different traffic states. The scattering of the data is thus attributed to the noise terms introduced in the stochastic differential equations and the transition among the various traffic states. Most importantly, the observed inverse-λ shape and the associated sudden jump of physical quantities arise due to the effect of stochastic noises on the stability of the system. The model parameters are calibrated, and a qualitative agreement is obtained between the data and the numerical simulations.

      PubDate: 2017-10-10T02:43:17Z
       
  • A critical evaluation of the Next Generation Simulation (NGSIM) vehicle
           trajectory dataset
    • Authors: Benjamin Coifman; Lizhe
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Benjamin Coifman, Lizhe Li
      A clear understanding of car following behavior and microscopic relationships is critical for advancing traffic flow theory. Without empirical microscopic data, plausible but incorrect hypotheses perpetuate in the vacuum. The Next Generation Simulation (NGSIM) project was undertaken to collect such data and the NGSIM data set has become the de facto standard, underlying the vast majority of empirically based advances of the past decade. But there has been a growing minority of researchers who have found unrealistic relationships in the NGSIM data. To date, the critical findings have almost exclusively come from the existing NGSIM database itself. Unfortunately, as this paper shows, the NGSIM errors are beyond anything that could be corrected strictly through cleaning or interpolation of the reported NGSIM data. This paper takes the deepest evaluation yet of the NGSIM data. This research manually re-extracts the vehicle trajectories from a portion of the original NGSIM video to explicitly quantify NGSIM errors, e.g., piecewise constant speeds punctuated by brief periods of large acceleration exhibited by the NGSIM data were not evident in the newly extracted trajectories. This point is particularly troublesome for applications that rely on acceleration, e.g., most car following models. The magnitude of errors exhibit a dependency on speed, location and vehicle length. Examples are shown where a real vehicle stopped but the NGSIM trajectory does not and then overruns the location of the real leader. Needless to say, the re-extracted trajectories showed much cleaner speed-spacing relationships than the corresponding raw NGSIM trajectories. Finally, this work tracked the original NGSIM vehicles seen in one camera and added another 236 vehicles (11%) visible before/after the period of NGSIM tracking. As of publication, the manually re-extracted data from this paper will be released to the research community.

      PubDate: 2017-10-10T02:43:17Z
       
  • Sufficient optimality conditions for distributed, non-predictive ramp
           metering in the monotonic cell transmission model
    • Authors: Marius Schmitt; Chithrupa Ramesh John Lygeros
      Abstract: Publication date: November 2017
      Source:Transportation Research Part B: Methodological, Volume 105
      Author(s): Marius Schmitt, Chithrupa Ramesh, John Lygeros
      We consider the ramp metering problem for a freeway stretch modeled by the Cell Transmission Model. Assuming perfect model knowledge and perfect traffic demand prediction, the ramp metering problem can be cast as a finite horizon optimal control problem with the objective of minimizing the Total Time Spent, i.e., the sum of the travel times of all drivers. For this reason, the application of Model Predictive Control (MPC) to the ramp metering problem has been proposed. However, practical tests on freeways show that MPC may not outperform simple, distributed feedback policies. Until now, a theoretical justification for this empirical observation was lacking. This work compares the performance of distributed, non-predictive policies to the optimal solution in an idealised setting, specifically, for monotonic traffic dynamics and assuming perfect model knowledge. To do so, we suggest a distributed, non-predictive policy and derive sufficient optimality conditions for the minimization of the Total Time Spent via monotonicity arguments. In a case study based on real-world traffic data, we demonstrate that these optimality conditions are only rarely violated. Moreover, we observe that the suboptimality resulting from such infrequent violations appears to be negligible. We complement this analysis with simulations in non-ideal settings, in particular allowing for model mismatch, and argue that Alinea, a successful, distributed ramp metering policy, comes close to the ideal controller both in terms of control behavior and in performance.

      PubDate: 2017-10-10T02:43:17Z
       
  • Advancements in continuous approximation models for logistics and
           transportation systems: 1996–2016
    • Authors: Sina Ansari; Mehmet Xiaopeng Yanfeng Ouyang Karen Smilowitz
      Abstract: Publication date: Available online 9 October 2017
      Source:Transportation Research Part B: Methodological
      Author(s): Sina Ansari, Mehmet Başdere, Xiaopeng Li, Yanfeng Ouyang, Karen Smilowitz
      Continuous approximation (CA) is an efficient and parsimonious technique for modeling complex logistics problems. In this paper, we review recent studies that develop CA models for transportation, distribution and logistics problems with the aim of synthesizing recent advancements and identifying current research gaps. This survey focuses on important principles and key results from CA models. In particular, we consider how these studies fill the gaps identified by the most recent literature reviews in this field. We observe that CA models are used in a wider range of applications, especially in the areas of facility location and integrated supply chain management. Most studies use CA as an alternative and a complement to discrete solution approaches; however, CA can also be used in combination with discrete approaches. We conclude with promising areas of future work.

      PubDate: 2017-10-10T02:43:17Z
       
 
 
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