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  Subjects -> TRANSPORTATION (Total: 180 journals)
    - AIR TRANSPORT (9 journals)
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    - TRANSPORTATION (100 journals)

TRANSPORTATION (100 journals)

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Partially Free   (Followers: 88)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5)
Archives of Transport     Open Access   (Followers: 18)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 13)
Cities in the 21st Century     Open Access   (Followers: 13)
Economics of Transportation     Partially Free   (Followers: 12)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 12)
European Transport Research Review     Open Access   (Followers: 19)
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: 9)
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 7)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 10)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 3)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 9)
International Journal of Electronic Transport     Hybrid Journal   (Followers: 7)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 10)
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: 12)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 16)
International Journal of Transportation Science and Technology     Open Access   (Followers: 10)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 13)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 6)
Journal of Navigation     Hybrid Journal   (Followers: 216)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 11)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 2)
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: 21)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 11)
Journal of Transport Geography     Hybrid Journal   (Followers: 23)
Journal of Transport History     Hybrid Journal   (Followers: 11)
Journal of Transportation and Logistics     Open Access  
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 6)
Journal of Transportation Security     Hybrid Journal   (Followers: 1)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
Journal of Transportation Technologies     Open Access   (Followers: 14)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 8)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics     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: 18)
Open Journal of Safety Science and Technology     Open Access   (Followers: 9)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 1)
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: 15)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 17)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 5)
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: 10)
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: 1)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 5)
Transport     Open Access   (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: 8)
Transportation     Hybrid Journal   (Followers: 27)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 13)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 5)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 33)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 22)
Transportation Research Procedia     Open Access   (Followers: 4)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 31)
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: 1)
Transportrecht     Unknown  
Travel Behaviour and Society     Full-text available via subscription   (Followers: 8)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 1)
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
Journal Prestige (SJR): 3.109
Citation Impact (citeScore): 5
Number of Followers: 29  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0191-2615
Published by Elsevier Homepage  [3163 journals]
  • An exact convex relaxation of the freeway network control problem with
           controlled merging junctions
    • Authors: Marius Schmitt; John Lygeros
      Pages: 1 - 25
      Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Marius Schmitt, John Lygeros
      We consider the freeway network control problem where the aim is to optimize the operation of traffic networks modeled by the cell transmission model via ramp metering and partial mainline demand control. Optimal control problems using the cell transmission model are usually non-convex, due to the nonlinear fundamental diagram, but a convex relaxation in which demand and supply constraints are relaxed is often used. Previous works have established conditions under which solutions of the relaxation can be made feasible with respect to the original constraints. In this work, we generalize these conditions and show that the control of flows into merging junctions is sufficient to do so if the objective is to minimize the total time spent in traffic. We derive this result by introducing an alternative system representation. In the new representation, the system dynamics are concave and state-monotone. We show that exactness of the convex relaxation of finite horizon optimal control problems follows from these properties. Deriving the main result via a characterization of the system dynamics allows one to treat arbitrary monotone, concave fundamental diagrams and several types of control for merging junctions in a uniform manner. The derivation also suggests a straightforward method to verify if the results continue to hold for extensions or modifications of the models studied in this work.

      PubDate: 2018-06-03T17:29:25Z
      DOI: 10.1016/j.trb.2018.05.006
      Issue No: Vol. 114 (2018)
  • A generalized parallel constrained choice model for intra-household escort
           decision of high school students
    • Authors: Adam Weiss; Khandker Nurul Habib
      Pages: 26 - 38
      Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Adam Weiss, Khandker Nurul Habib
      This paper presents an expanded and generalized formulation of discrete group decision-making model. The empirical model is developed for modelling high school student escort and travel mode choices. The development of the model uncovered issues with an existing group decision model, the multi-linear logit, that has recently been applied to similar decision contexts. The paper proposes an expanded formulation of parallel constrained choices logit model as an alternative to the multi-linear logit. The proposed model explicitly considers both the choice of mode of the students and commuting adults within the household and how those decisions change in response to household escort decisions. This structure is powerful as it allows both individual and group level decisions to be jointly modelled. The application of the model in this paper is generalized such that any number of adults can be accommodated within the modelling structure whereas previous studies have been limited to either two adults or two workers. The key findings of the analysis include a certain degree of altruism (or dedication) from adults to household children. This altruism which is captured indirectly within the modelling framework based on a lower utility weight for the adults in the household relative to the utility weight for household children.

      PubDate: 2018-06-07T07:39:45Z
      DOI: 10.1016/j.trb.2018.05.008
      Issue No: Vol. 114 (2018)
  • Paths to the adoption of electric vehicles: An evolutionary game
           theoretical approach
    • Authors: Sara Encarnação; Fernando P. Santos; Francisco C. Santos; Vered Blass; Jorge M. Pacheco; Juval Portugali
      Pages: 24 - 33
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Sara Encarnação, Fernando P. Santos, Francisco C. Santos, Vered Blass, Jorge M. Pacheco, Juval Portugali
      Electric vehicles (EVs) are a viable alternative to internal combustion engine (ICE) vehicles, with the potential to alleviate the negative externalities stemming from the present ICE-based transportation sector. Notwithstanding, the current prevalence of ICE creates a lock-in state that averts the adoption of alternative and environmental friendly technologies, bringing forth a social dilemma. Here we investigate the feasibility of escaping the present lock-in state by studying possible incentive mechanisms involving, simultaneously, governments (public), companies (private) and consumers (civil). Resorting to evolutionary game theory (EGT), we develop a theoretical model grounded on the strategic interactions between players from the different sectors, whose co-evolving choices influence (and are influenced by) different policies and social incentives. Our findings suggest that i) public regulation is necessary but not sufficient for guaranteeing full EV adoption; ii) public-civil synergies are essential; iii) demand for EVs preceding supply is most efficient, providing companies with the needed incentives to counterweigh infrastructure investments; and iv) full adoption of EVs requires coordination between the three sectors to emerge, particularly when changes are initiated by the public sector.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.05.002
      Issue No: Vol. 113 (2018)
  • Travel time estimation by urgent-gentle class traffic flow model
    • Authors: Yongliang Zhang; M.N. Smirnova; A.I. Bogdanova; Zuojin Zhu; N.N. Smirnov
      Pages: 121 - 142
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Yongliang Zhang, M.N. Smirnova, A.I. Bogdanova, Zuojin Zhu, N.N. Smirnov
      To estimate travel time through a ring road, an urgent-gentle class traffic flow model (UGM) with viscoelastic and ramp effects is developed. Vehicles in traffic flow are divided into urgent and gentle categories, and the urgent class has the demand of arriving at destination in time, while the gentle class hasn’t. It is assumed that the urgent and gentle classes have the same instantaneous speed to simply the mathematical modeling. To validate the proposed traffic model, a Navier–Stokes like model (Zhang, 2003) is further extended just for validating the present model. Numerical simulations based on the present model are carried out to calculate the travel time on a ring road with total length of 80  km and four initially assumed jams. It was found that similar to the effect of initially assumed jams, the on/off ramp flows play significant roles in the formation and evolution of traffic flow patterns. Urgent density fraction propagates at local traffic speed, its temporal evolution and spatial distribution curves have different shapes as compared with that of traffic density and speed. The average travel time increases monotonically with the increase of ring road initial density. Rational management of road operation is necessary.

      PubDate: 2018-05-31T17:23:34Z
      DOI: 10.1016/j.trb.2018.05.010
      Issue No: Vol. 113 (2018)
  • Effects of maximum relaxation in viscoelastic traffic flow modeling
    • Authors: Jian Ma; C.K. Chan; Zhongbao Ye; Zuojin Zhu
      Pages: 143 - 163
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Jian Ma, C.K. Chan, Zhongbao Ye, Zuojin Zhu
      Viscoelastic modeling is used to describe traffic flows in analogous to non-Newtonian fluid flows, where first and second order linear viscoelastic approximations are employed. This paper presents the effects of maximum relaxation in traffic flow modeling by demonstrating numerical results of single lane ring road traffic flows. Numerical results show that there is a wide spectrum of spatial-temporal pattern formation phenomena in traffic system. Self-organization plays a crucial role in the determination of traffic flow patterns and a different initial density causes a completely distinct traffic flow pattern. Predicting traffic flow acceleration is useful for checking reliability of the simulation and maximum relaxation brings about some observable but non-significant effects on traffic flow patterns.

      PubDate: 2018-06-03T17:29:25Z
      DOI: 10.1016/j.trb.2018.05.013
      Issue No: Vol. 113 (2018)
  • Enhancing electric vehicle sustainability through battery life optimal
    • Authors: Jennifer Schoch; Johannes Gaerttner; Alexander Schuller; Thomas Setzer
      Pages: 1 - 18
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Jennifer Schoch, Johannes Gaerttner, Alexander Schuller, Thomas Setzer
      In this article, we investigate the potential for battery life prolongation through optimized charging under consideration of individual mobility requirements. Based on a comprehensive battery aging model we introduce a continuous quadratic programming model to derive battery life optimal charging (OPT). The strategy indicates when and how much to charge to maximize the potential range throughout the battery life. We find that OPT has the potential to more than double the expected battery life compared to simple and often abundant recharging activities as observable today. The degree of battery life prolongation strongly depends on the operating temperature. Since optimal charging would require deterministic knowledge of future trips and corresponding charging levels we investigate a more convenient charging heuristic derived from “As-Late-As-Possible” (ALAP) charging. ALAP charging considers range buffers between 5% and 60% over the range required until the next re-charging opportunity. We analyze the trade-off between (long-term) battery life and (short-term) range flexibility. We find that for decreasing temperatures the trade-off between battery life and flexibility is solved with increasing range buffers. From our results battery degradation aware charging heuristics can be easily derived and applied in real-world settings.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.03.016
      Issue No: Vol. 112 (2018)
  • How likely am I to find parking' – A practical model-based framework
           for predicting parking availability
    • Authors: Jun Xiao; Yingyan Lou; Joshua Frisby
      Pages: 19 - 39
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Jun Xiao, Yingyan Lou, Joshua Frisby
      Parking availability information (or occupancy of parking facility) is highly valued by travelers, and is one of the most important inputs to many parking models. This paper proposes a model-based practical framework to predict future occupancy from historical occupancy data alone. The framework consists of two modules: estimation of model parameters, and occupancy prediction. At the core of the predictive framework, a queuing model is employed to describe the stochastic occupancy change of a parking facility. While the underlying queuing model can be any reasonable model, we demonstrate the framework with the well-established continuous-time Markov M\M\C\C queue in this paper. The possibility of adopting a different queuing model that can potentially incorporate the parking-searching process is also discussed. The parameter estimation module and the occupancy prediction module are both built on the underlying queuing model. To apply the estimation and prediction methods in real world, a few practical considerations are accounted for in the framework with methods to handle variations of arrival and departure patterns from day to day and within a day, including special events. The proposed framework and models are validated using both simulated and real data. Our San Francisco case studies demonstrate that the parameters estimated offline can lead to accurate predictions of parking facility occupancy both with and without real-time update. We also performed extensive numerical experiments to compare the proposed framework and methods with several pure machine-learning methods in recent literature. It is found that our approach delivers equal or better performance, but requires a computation time that is orders of magnitude less to tune and train the model. Additionally, our approach can predict for any time in the future with one training process, while pure machine-learning methods have to train a specific model for a different prediction interval to achieve the same level of accuracy.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.001
      Issue No: Vol. 112 (2018)
  • Contracting and renegotiating with a loss-averse private firm in BOT road
    • Authors: Zhuo Feng; Yiwen Zhang; Shuibo Zhang; Jinbo Song
      Pages: 40 - 72
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Zhuo Feng, Yiwen Zhang, Shuibo Zhang, Jinbo Song
      In BOT road project, the government offers a firm an ex ante contract, which specifies toll price and concession period based on the forecasted demand. When the demand states are observed in the operation period, the government may request renegotiation to adapt the initial contract to the realized demand state. By considering the loss aversion behavior of the private firm, this paper shows that renegotiation takes place only if the private firm’s extent of loss aversion is sufficiently small. However, in what direction the government adjusts toll price and concession period depends on the combined effects of initial price, demand level, and demand uncertainty in each demand state. This paper has further investigated the optimal initial contract. We find that if one demand state realizes with a sufficiently large probability, then the optimal initial contract is renegotiation-proof in this demand state while inducing renegotiation in other demand states; if all demand states realize with almost equal probabilities, whether the optimal initial contract prevents or induces renegotiations in all demand states depends on the private firm’s extent of loss aversion. This paper makes two major contributions to the literature. First, we apply loss aversion to the context of renegotiation in BOT road projects and show that renegotiation is costly. Second, we consider the optimal initial contract in anticipation of ex post renegotiation and show that the government should trade off between ex ante social welfare and ex post psychological loss. To obtain more insights and to strengthen our model results, we have reexamined the optimal renegotiation and initial contracts under some relaxed assumptions.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.004
      Issue No: Vol. 112 (2018)
  • Detecting pattern changes in individual travel behavior: A Bayesian
    • Authors: Zhan Zhao; Haris N. Koutsopoulos; Jinhua Zhao
      Pages: 73 - 88
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Zhan Zhao, Haris N. Koutsopoulos, Jinhua Zhao
      Although stable in the short term, individual travel patterns are subject to changes in the long term. The ability to detect such changes is critical for developing behavior models that are adaptive over time. We define travel pattern changes as “abrupt, substantial, and persistent changes in the underlying patterns of travel behavior” and develop a methodology to detect such changes in individual travel patterns. We specify one distribution for each of the three dimensions of travel behavior (the frequency of travel, time of travel, and origins/destinations), and interpret the change of the parameters of the distributions as indicating the occurrence of a pattern change. A Bayesian method is developed to estimate the probability that a pattern change occurs at any given time for each behavior dimension. The proposed methodology is tested using pseudonymized smart card records of 3210 users from London, U.K. over two years. The results show that the method can successfully identify significant changepoints in travel patterns. Compared to the traditional generalized likelihood ratio (GLR) approach, the Bayesian method requires less predefined parameters and is more robust. The methodology presented in this paper is generalizable and can be applied to detect changes in other aspects of travel behavior and human behavior in general.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.03.017
      Issue No: Vol. 112 (2018)
  • Integrated optimization of traffic signals and vehicle trajectories at
           isolated urban intersections
    • Authors: Chunhui Yu; Yiheng Feng; Henry X. Liu; Wanjing Ma; Xiaoguang Yang
      Pages: 89 - 112
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Chunhui Yu, Yiheng Feng, Henry X. Liu, Wanjing Ma, Xiaoguang Yang
      Existing traffic signal control systems only allocate green time to different phases to avoid conflicting vehicle movements. With advances in connected and automated vehicle (CAV) technologies, CAV trajectories not only provide more information than existing infrastructure-based detection systems, but also can be controlled to further improve mobility and sustainability. This paper presents a mixed integer linear programming (MILP) model to optimize vehicle trajectories and traffic signals in a unified framework at isolated signalized intersections in a CAV environment. A new planning horizon strategy is applied to conduct the optimization. All vehicle movements such as left-turning, right-turning and through are considered. Phase sequences, green start and duration of each phase, and cycle lengths are optimized together with vehicle lane-changing behaviors and vehicle arrival times for delay minimization. Vehicles are split into platoons and are guaranteed to pass through the intersection at desired speeds and avoid stops at stop bars. Exact vehicle trajectories are determined based on optimized vehicle arrival times. For the trajectory planning of platoon leading vehicles, an optimal control model is implemented to minimize fuel consumption/emission. For following vehicles in a platoon, Newell's car-following model is applied. Simulation results validate the advantages of the proposed control method over vehicle-actuated control in terms of intersection capacity, vehicle delays, and CO2 emissions. A sensitivity analysis is conducted to show the potential benefits of a short minimum green duration as well as the impacts of no-changing zones on the optimality of the proposed model.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.007
      Issue No: Vol. 112 (2018)
  • Hybrid model predictive control based dynamic pricing of managed lanes
           with multiple accesses
    • Authors: Zhen Tan; H. Oliver Gao
      Pages: 113 - 131
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Zhen Tan, H. Oliver Gao
      We propose a hybrid model predictive control (MPC) based dynamic tolling strategy for high-occupancy toll (HOT) lanes with multiple accesses. This approach preplans and coordinates the prices for different OD pairs and enables adaptive utilization of HOT lanes by considering available demand information and boundary conditions. It also addresses such practical issues as prevention of recurrent congestion in HOT lanes, ensuring no higher toll for a closer toll exit and fairness among different OD groups at each toll entry, as well as the fact that high occupancy vehicles (HOVs) have free access to the HOT lanes. Taking the inflows at each toll entry as the control, traffic densities and vehicle queue length as observed system states, and boundary traffic as predicted exogenous input, we formulate a discrete-time piecewise affine traffic model. Optimal tolls are then derived from a one-to-one mapping based on the optimal toll entry flows. By properly formulating the constraints, we show that the MPC problem at each stage is a mixed-integer linear program and admits an explicit control law derived by multi-parametric programing techniques. A numerical experiment is presented for a representative freeway segment to validate the effectiveness of the proposed approach. The results show that our control model can react to demand and boundary condition changes by adjusting and coordinating tolls smoothly at adjacent toll entries and drive the system to a new equilibrium that minimizes the total person delay. Under the optimal prediction horizon, the on-line computational cost of the proposed control model is only about 4% and 8% of the modeling cycle of 30 s, respectively, for two typical traffic scenarios, which implies a potential of real-time implementation.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.03.008
      Issue No: Vol. 112 (2018)
  • An optimization approach for airport slot allocation under IATA guidelines
    • Authors: Nuno Antunes Ribeiro; Alexandre Jacquillat; António Pais Antunes; Amedeo R. Odoni; João P. Pita
      Pages: 132 - 156
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Nuno Antunes Ribeiro, Alexandre Jacquillat, António Pais Antunes, Amedeo R. Odoni, João P. Pita
      Air traffic demand has grown to exceed available capacity during extended parts of each day at many of the busiest airports worldwide. Absent opportunities for capacity expansion, this may require the use of demand management measures to restore the balance between scheduled traffic and available capacity. The main demand management mechanism in use today is the administrative schedule coordination process operated by the International Air Transport Association (IATA), which is in place at the great majority of busy airports outside the United States. This paper proposes a novel multi-objective Priority-based Slot Allocation Model (PSAM) that optimizes slot allocation, while complying with the complex set of priorities and requirements specified by the IATA guidelines, as well as with the declared capacity constraints at the airports. It presents an efficient computational approach that provides optimal slot allocation solutions at airports significantly larger than has been possible to date. The model is applied to two Portuguese airports, a small one (Madeira) and a mid-size one (Porto) using highly detailed data on airline slot requests and airport capacity constraints. Results suggest that PSAM can improve the efficiency of current practice by providing slot allocations that match better the slot requests of airlines. Equally important, PSAM can also quantify the sensitivity of slot allocation decisions to the various priorities and requirements specified in the IATA guidelines.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.005
      Issue No: Vol. 112 (2018)
  • Bottleneck model with heterogeneous information
    • Authors: Zaid Khan; Saurabh Amin
      Pages: 157 - 190
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Zaid Khan, Saurabh Amin
      This paper studies the effects of heterogeneous information on traffic equilibria and the resulting travel costs (both individual and social) when commuters make departure time choices to cross an unreliable bottleneck link. Increasing adoption and improved predictive abilities of Traveler Information Systems (TIS) enable commuters to plan their trips; however, there are inherent heterogeneities in information access and TIS accuracies. Our work addresses the open problem posed in Arnott et al. (1991) about the need to consider asymmetrically informed commuters in the bottleneck model of traffic congestion. We consider a Bayesian game with two heterogeneous commuter populations: one population is privately informed of the realized network state while the other only knows the public information about the distribution of states. We characterize the equilibrium of the game, in which each population chooses a departure rate function over time to minimize its expected cost based on its private belief about the state and the behavior of the other population. We provide a full equilibrium characterization for the complete range of values of link reliability, incident probability, and information penetration. The populations’ equilibrium strategies can broadly be categorized into two distinct regimes. Specifically, when information penetration is above a certain threshold, the populations’ equilibrium strategies are non-unique, and the relative Value of Information (VoI) is 0, i.e. the two populations face the same cost. On the other hand, when information penetration is below the threshold, equilibrium is unique, and VoI is positive and decreasing in information penetration. Importantly, we find that the lowest social cost is always achieved when a non-zero fraction of commuters are uninformed. The more unreliable the link, the higher the information penetration that achieves this minimum. We define the Value of Heterogeneity (VoH) as the difference between the minimum social cost and the cost under complete information penetration, and find that it can be significant under practically relevant conditions.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.003
      Issue No: Vol. 112 (2018)
  • Logit-based transit assignment: Approach-based formulation and paradox
    • Authors: S. Sun; W.Y. Szeto
      Pages: 191 - 215
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): S. Sun, W.Y. Szeto
      This paper proposes an approach-based transit assignment model under the assumption of logit-based stochastic user equilibrium (SUE) with fixed demand. This model is proven to have a unique solution. A cost-averaging version of the self-regulated averaging method (SRAM) is developed to solve the proposed approach-based SUE transit assignment problem. It is proven that the algorithm converges to the model solution. Numerical examples with discussions are presented to investigate the model properties, a paradoxical phenomenon due to the stochastic nature of the model, capacity paradox, and the performance of the proposed algorithm. The sensitivity analysis of different model and algorithm parameters are performed. A performance comparison between the cost-averaging SRAM, the flow-averaging SRAM, and the method of successive averages is made. The proposed methodology is demonstrated to be able to solve the Winnipeg transit network.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.03.018
      Issue No: Vol. 112 (2018)
  • Vehicle and Crew Scheduling for Flexible Bus Transportation Systems
    • Authors: Vincent Boyer; Omar J. Ibarra-Rojas; Yasmín Á. Ríos-Solís
      Pages: 216 - 229
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Vincent Boyer, Omar J. Ibarra-Rojas, Yasmín Á. Ríos-Solís
      This article deals with the Flexible Vehicle and Crew Scheduling Problem faced by urban bus transport agencies that have to assign their resources (vehicles and drivers) to cover timetables generated at the tactical level. We aim for high quality and fast to compute solutions for this problem, considering vehicle characteristics, driver qualifications requirements for each line, and labor regulations, that is, drivers have a limited duty length, mandatory rests, a restricted consecutive driving time, and a limited extra working hours. Moreover, the starting time of the drivers shift is not fixed a priori and the breaks can be allocated anywhere in the schedule as long as labor regulations are satisfied. Thus, flexibility is required to compute drivers duty but it is also needed in scenarios where the available number of drivers and vehicles changes almost everyday. We propose a mixed-integer linear programming model and a variable neighborhood search for this problem and show the efficiency of our approaches with a large set of instances.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.008
      Issue No: Vol. 112 (2018)
  • A link-node reformulation of ridesharing user equilibrium with network
    • Authors: Xuan Di; Rui Ma; Henry X. Liu; Xuegang (Jeff) Ban
      Pages: 230 - 255
      Abstract: Publication date: June 2018
      Source:Transportation Research Part B: Methodological, Volume 112
      Author(s): Xuan Di, Rui Ma, Henry X. Liu, Xuegang (Jeff) Ban
      Though the conventional network design is extensively studied, the network design problem for ridesharing, in particular, the deployment of high-occupancy toll (HOT) lanes, remains understudied. This paper focuses on one type of network design problem as to whether existing roads should be retrofit into HOT lanes. It is a continuous bi-level mathematical program with equilibrium constraints. The lower level problem is ridesharing user equilibrium (RUE). To reduce the problem size and facilitate computation, we reformulate RUE in the link-node representation. Then we extend the RUE framework to accommodate the presence of HOT lanes and tolls. Algorithms are briefly discussed and numerical examples are illustrated on the Braess network and the Sioux Falls network, respectively. Results show that carefully selecting the deployment of HOT lanes can improve the overall system travel time.

      PubDate: 2018-05-28T21:13:47Z
      DOI: 10.1016/j.trb.2018.04.006
      Issue No: Vol. 112 (2018)
  • Bounded acceleration traffic flow models: A unified approach
    • Authors: Wen-Long Jin; Jorge Laval
      Pages: 1 - 18
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Wen-Long Jin, Jorge Laval
      Bounded acceleration plays a critical role in safety, fuel consumption, vehicle emissions, and capacity drop in traffic flow. We present here equivalent second-order continuum and car-following models with bounded accelerations that encompass existing models, including the LWR model with bounded acceleration, Lebacque’s two-phase model, and the bounded acceleration version of Newell’s car-following model. Analytical solutions are presented for (i) an accelerating rarefaction wave on a homogeneous road, where traffic is still in equilibrium in the acceleration zone, and (ii) an inhomogeneous road with varying speed limits, where an accelerating standing wave is continuous over an acceleration zone and traffic states are non-equilibrium but stationary. We find that traffic states with bounded acceleration can be equilibrium or not and stationary or not, and bounded acceleration does not lead to capacity drop with variable speed limits. These theoretical results are verified with numerical solutions of corresponding lead-vehicle problems. This study provides a theoretical foundation of applying variable speed limits to eliminate capacity drop at lane-drop, sag, tunnel, and other bottlenecks. In the future we are interested in extending such bounded acceleration models for other bottlenecks with inhomogeneous jam densities and time gaps.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.006
      Issue No: Vol. 111 (2018)
  • Train timetable design under elastic passenger demand
    • Authors: Tomáš Robenek; Shadi Sharif Azadeh; Yousef Maknoon; Matthieu de Lapparent; Michel Bierlaire
      Pages: 19 - 38
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Tomáš Robenek, Shadi Sharif Azadeh, Yousef Maknoon, Matthieu de Lapparent, Michel Bierlaire
      A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the passenger centric train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15% when taking into account the passengers’ behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.002
      Issue No: Vol. 111 (2018)
  • Considering a dynamic impact zone for real-time railway traffic management
    • Authors: Sofie Van Thielen; Francesco Corman; Pieter Vansteenwegen
      Pages: 39 - 59
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Sofie Van Thielen, Francesco Corman, Pieter Vansteenwegen
      In a railway system, a conflict occurs when two trains require the same part of the infrastructure at the same time. Currently, such conflicts are typically resolved manually by experienced dispatchers. However, it is impossible for them to fully anticipate the impact of their actions on the entire network. This paper proposes a conflict prevention strategy which focuses only on the relevant part of the network and traffic and, consequently, proposes a solution for that part only. The proposed strategy first looks for possible rerouting options by using an optimization model. If no solution is found, a solution based on delaying one of the trains is required. This retiming/reordering heuristic uses information from an offline calculation, for determining related conflicts that frequently occur. In this way, a so-called dynamic impact zone is created online for each conflict. When deciding which train to delay, the potential conflicts and the incurred delays of all trains in this dynamic impact zone are taken into account. The performance of this new Conflict Prevention Strategy is compared to a common dispatching strategy, other heuristics, and an exact method. Extensive experiments on a large part of the Belgian railway network show that by considering this dynamic impact zone the total delay can be decreased by at least 67% compared to the basic First Come, First Served decision rule. Moreover, the dynamic impact zone has a reasonable size and scales well to large networks as only the relevant conflicts and their expected consequences are considered. This makes our Dynamic Impact Zone heuristic very fast. The computation time for returning a resolution to a conflict with the proposed conflict prevention strategy is, for 95% of the conflicts, less than two seconds, and at most 26 s, including the creation of the dynamic impact zone of the conflict.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.003
      Issue No: Vol. 111 (2018)
  • Electric vehicle fleet size and trip pricing for one-way carsharing
           services considering vehicle relocation and personnel assignment
    • Authors: Min Xu; Qiang Meng; Zhiyuan Liu
      Pages: 60 - 82
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Min Xu, Qiang Meng, Zhiyuan Liu
      This study proposes an interesting electric vehicle fleet size and trip pricing (EVFS&TP) problem for one-way carsharing services by taking into account the necessary practical requirements of vehicle relocation and personnel assignment. The EVFS&TP problem aims to maximize the profit of one-way carsharing operators by determining the electric vehicle fleet size, trip pricing, and strategies of vehicle relocation and personnel assignment subject to the elastic demand for the one-way carsharing services. A mixed-integer nonlinear and nonconvex programming model is first built for the EVFS&TP problem. By exploiting the unique structure of the original built model, a mixed-integer convex programming model is subsequently developed. An effective global optimization method with several outer-approximation schemes is put up to find the global optimal or ε-optimal solution to the EVFS&TP problem. A case study based on a one-way carsharing operator in Singapore is conducted to demonstrate the efficiency of the proposed model and solution method and further analyse the impact of demand, the degree of demand variation, the fixed operational cost of the vehicles as well as payment for personnel on the performance of the one-way carsharing services.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.001
      Issue No: Vol. 111 (2018)
  • Strategic investment in enhancing port–hinterland container
           transportation network resilience: A network game theory approach
    • Authors: Hong Chen; Jasmine Siu Lee Lam; Nan Liu
      Pages: 83 - 112
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Hong Chen, Jasmine Siu Lee Lam, Nan Liu
      China's “Belt and Road” strategy emphasizes the significance of maritime logistics. To ensure the efficiency and safety of landside maritime logistics, this study aims to investigate the strategic investment of players in a port–hinterland container transportation network to enhance network resilience to man-made unconventional emergency events by reducing vulnerability. Given the complexity of the involvement of multiple players and their interacting complementary and competitive business relationships, network game theory is adopted. Results show that the complementary influence Bonacich centrality of players plays a critical role in determining their investment decisions and serves as basis from which useful managerial insights can be derived.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.004
      Issue No: Vol. 111 (2018)
  • Flexible ship loading problem with transfer vehicle assignment and
    • Authors: Çağatay Iris; Jonas Christensen; Dario Pacino; Stefan Ropke
      Pages: 113 - 134
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Çağatay Iris, Jonas Christensen, Dario Pacino, Stefan Ropke
      This paper presents the flexible containership loading problem for seaport container terminals. The integrated management of loading operations, planning of the transport vehicles to use and their scheduling is what we define as the Flexible Ship Loading Problem (FSLP). The flexibility comes from a cooperative agreement between the terminal operator and the liner shipping company, specifying that the terminal has the right to decide which specific container to load for each slot obeying the class-based stowage plan received from the liner. We formulate a mathematical model for the problem. Then we present various modelling enhancements and a mathematical model to obtain strong lower bounds. We also propose a heuristic algorithm to solve the problem. It is shown that enhancements improve the performance of formulation significantly, and the heuristic efficiently generates high-quality solutions. Results also point out that substantial cost savings can be achieved by integrating the ship loading operations.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.009
      Issue No: Vol. 111 (2018)
  • The two-train separation problem on non-level track—driving strategies
           that minimize total required tractive energy subject to prescribed section
           clearance times
    • Authors: Amie Albrecht; Phil Howlett; Peter Pudney; Xuan Vu; Peng Zhou
      Pages: 135 - 167
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Amie Albrecht, Phil Howlett, Peter Pudney, Xuan Vu, Peng Zhou
      When two trains travel along the same track in the same direction it is a common safety requirement with three-aspect signalling that the trains must be separated by at least two signals if they wish to continue following the planned schedule. Under these separation conditions there will always be at least one clear section of track between the two trains. When these conditions are violated the following train must adopt a revised strategy that will enable it to stop at the next signal if required. In this paper we find necessary conditions on non-level track to minimize the total tractive energy required for both trains to complete their respective journeys within the allowed time subject to safety-compatible separation constraints in the form of a prescribed set of latest allowed section exit times for the leading train and a corresponding prescribed set of earliest allowed section entry times for the following train. We use classical methods of constrained optimzation to show that the optimal driving strategy for each train is defined by a unique optimal driving speed on each section and that the sequence of optimal driving speeds is a decreasing sequence for the leading train and an increasing sequence for the following train. We illustrate our results by finding optimal strategies and associated speed profiles for both the leading train and the following train in some elementary but realistic examples.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.012
      Issue No: Vol. 111 (2018)
  • Estimating panel effects in probabilistic representations of dynamic
           decision trees using bayesian generalized linear mixture models
    • Authors: Seheon Kim; Soora Rasouli; Harry Timmermans; Dujuan Yang
      Pages: 168 - 184
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Seheon Kim, Soora Rasouli, Harry Timmermans, Dujuan Yang
      When collecting panel data, we need to acknowledge that responses do not represent independent measurements. The known apparatus in transportation research offers several opportunities to estimate panel effects for well-known and widely applied models such as hazard and dynamic logit models. However, the transportation research community is not endowed with a rich set of methods to account for panel effects in dynamic probabilistic decision trees, which have been used as a formalism for the representation of decision heuristics. Building on scarce prior work in statistics, we elaborate an approach to estimate panel effects in dynamic probabilistic decision trees with multinomial action states. Given that panel data naturally have a hierarchical structure with repeated measures nested within individuals, we implement a mixed-effects model that simultaneously accounts for population-level effects (fixed effects), between-individual variances (random effects), and within-individual variances (autocorrelations). The approach uses an iterative estimation procedure between CHAID-based probabilistic tree induction and Bayesian generalized linear mixture modeling (GLMM). When extracting the dynamic probabilistic decision trees, it is assumed that the random effects are known, while it is assumed that the fixed effects are known when estimating the Bayesian GLMM. This iterative process continues until convergence is reached. A Monte Carlo technique is used to navigate between aggregate choice probabilities and individual level multinomial choices. We also test the significance of temporal autocorrelation within individuals. The suggested approach is illustrated using charging station choice of users of Plug-in Electric Vehicles (PEV). Results support the potential value of the suggested approach.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.010
      Issue No: Vol. 111 (2018)
  • A two-stage robust approach for the reliable logistics network design
    • Authors: Chun Cheng; Mingyao Qi; Ying Zhang; Louis-Martin Rousseau
      Pages: 185 - 202
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Chun Cheng, Mingyao Qi, Ying Zhang, Louis-Martin Rousseau
      This paper examines a three-echelon logistics network in which all supply and transshipment nodes are subject to disruption. We use uncertainty sets to describe the possible scenarios without depending on probabilistic information. We adopt a two-stage robust optimization approach where location decisions are made before and recourse decisions are made after the disruptions are known. We construct three two-stage robust models, which are solved exactly by a column-and-constraint-generation algorithm. Numerical tests demonstrate that the proposed algorithm outperforms the Benders decomposition method in both solution quality and computational time, and that the system’s reliability can be improved with only a slight increase in the normal cost.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.015
      Issue No: Vol. 111 (2018)
  • Optimal design of intersecting bimodal transit networks in a grid city
    • Authors: Wenbo Fan; Yu Mei; Weihua Gu
      Pages: 203 - 226
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Wenbo Fan, Yu Mei, Weihua Gu
      The urban transit system in a real city usually has two major components: a sparse express (e.g. rail) network and a dense local (e.g. bus) network. The two networks intersect and interweave with each other throughout the city to furnish various route options for serving transit patrons with distinct ODs. The optimal design problem of this bimodal transit system, however, has not been well explored in the literature, partly due to the difficulty of modeling the patrons’ complex route choice behavior in the bimodal networks. In light of this, we formulate parsimonious continuum models for minimizing the total cost of the patrons and the transit agency for an intersecting bimodal transit network in a grid city, where the perpendicular local and express lines intersect at transfer stops. Seven distinct route types are identified in this network, which represent realistic intra- and inter-modal route options. A lower-level assignment problem between these routes is embedded in the upper-level network design optimization problem. We develop an efficient method to find near-optimal designs of the intersecting network. Numerical results unveil a number of insightful findings, e.g., that sizable cost savings are observed for the intersecting bimodal design as compared to the single-mode designs for moderate to high demand levels, and that only moderate benefits are observed as compared to the trunk-feeder designs under certain operating conditions. We also show that the conventional practice of designing the local and express networks separately would greatly undermine the benefit of the bimodal system.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.007
      Issue No: Vol. 111 (2018)
  • The integration of item-sharing and crowdshipping: Can collaborative
           consumption be pushed by delivering through the crowd'
    • Authors: Moritz Behrend; Frank Meisel
      Pages: 227 - 243
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Moritz Behrend, Frank Meisel
      Item-sharing and crowdshipping are two concepts of the sharing economy. In item-sharing, members of a sharing community can temporarily rent items such as tools or leisure equipment from one another. In crowdshipping, private drivers offer to execute delivery jobs for other people on trips they would make anyway. Since the peer-to-peer exchange in item-sharing involves repeated, inefficient ‘last-mile’ transports of small shipments, we investigate here whether the integration of item-sharing and crowdshipping has the potential to facilitate collaborative consumption. To this end, the decision making for an integrated item-sharing and crowdshipping platform is modeled. This platform matches supplies, requests, and planned trips of the community members. We develop mathematical models and heuristics for maximizing the platform’s profit and the number of fulfilled requests. Our results quantify and confirm the substantial benefit of integrating item-sharing and crowdshipping.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.02.017
      Issue No: Vol. 111 (2018)
  • Analysis of multimodal two-dimensional urban system equilibrium for cordon
           toll pricing and bus service design
    • Authors: Zhi-Chun Li; Ya-Dong Wang
      Pages: 244 - 265
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Zhi-Chun Li, Ya-Dong Wang
      This paper presents a multimodal urban system equilibrium model to address cordon toll pricing and bus service design issues in a two-dimensional monocentric city. Commuters are assumed to travel by auto or bus from their home locations to their workplace located in the city center through a ring-radial routing system. Auto users must pay tolls when passing through the cordons installed on the radial major roads. The multimodal two-dimensional urban system equilibrium is first formulated and its properties are analytically explored. A social welfare maximization model that simultaneously determines the optimal cordon toll location, toll level, bus service frequency and fare on each radial major road is then proposed. The effects of different tolling schemes (uniform and differential cordon-based, first-best, and no toll) on the multimodal urban system are also examined and compared.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.005
      Issue No: Vol. 111 (2018)
  • Analytical evaluation of the use of left-turn phasing for single left-turn
           lane only
    • Authors: Qiaoli Yang; Zhongke Shi; Shaowei Yu; Jie Zhou
      Pages: 266 - 303
      Abstract: Publication date: May 2018
      Source:Transportation Research Part B: Methodological, Volume 111
      Author(s): Qiaoli Yang, Zhongke Shi, Shaowei Yu, Jie Zhou
      At most traditional signalized intersections, three types of phasing can be provided to left turns: protected only phasing, permitted only phasing, and a combination of protected and permitted phasing (protected/permitted phasing). While numerous guidelines for the selection of left-turn phasing have been developed, there is no widely recognized guideline or criterion for the use of left-turn phasing under specific traffic conditions especially for a single left-turn lane. Focusing on the inherent mechanism of the dynamic nature and uncertainty of left-turn queues under different left-turn phasing, this paper develops a left-turn queueing model with uncertain second vacation to analytically evaluate the performance of left turns for different left-turn phasing, which considers various factors including the type of left-turn phasing, signal timing, left-turn volume, opposing through volume, type of left-turn lane, number of opposing through lanes, and number of sneakers, etc. For different left-turn phasing, the left-turn queues formation and dissipation with different characteristics of vacations (i.e., server absences during the red time and uncertain blocked time caused by the opposing through flow during the permitted green time) are formulated, and the queue length distributions of left turns along with the time within one cycle and at an arbitrary time are derived. Furthermore, three sets of left-turn performance measures are obtained: primary queueing measures, fuel-consumption (or emissions) related measures, and safety related measure. On the basis of these performance measures, an analytical evaluation framework for left-turn queues is established, which can provide a more accurate and detailed basis for evaluating and improving the use of left-turn phasing. Model validation indicates that the proposed model can be an effective tool to evaluate the use of left-turn phasing under different traffic conditions. In addition, numerical experiments are also performed to theoretically identify the factors that could affect the performance of left turns and thus help to determine the left-turn phasing selection under different conditions.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.03.013
      Issue No: Vol. 111 (2018)
  • Bicycle sharing system design with capacity allocations
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Dilay Çelebi, Aslı Yörüsün, Hanife Işık
      This study presents an integrated approach for the design of a Bicycle Sharing System (BSS) by jointly considering location decisions and capacity allocation. An important distinction of this approach is the definition of service levels, measured by the amount of unsatisfied demand both for bicycle pick-ups and returns. The method combines a set-covering model to assign location demands to stations with a queuing model to measure the related service levels. The key quality of this approach is its capacity in addressing the issues related to uncertainties in bicycle pick-up and return demand in BSS network design decisions. Results of the implementation of a BSS design for Istanbul Technical Universityâ;;s Ayazağa Campus show that our approach provides a balanced BSS network by equalizing the mean demand and return rates, which will decrease the need for relocation efforts once the system is put to use.

      PubDate: 2018-06-19T03:17:37Z
  • A unified framework for rich routing problems with stochastic demands
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Iliya Markov, Michel Bierlaire, Jean-François Cordeau, Yousef Maknoon, Sacha Varone
      We introduce a unified framework for rich vehicle and inventory routing problems with complex physical and temporal constraints. Demands are stochastic, can be non-stationary, and are forecast using any model that provides the expected demands and their error term distribution, which can be any theoretical or empirical distribution. We offer a detailed discussion on the modeling of demand stochasticity, focusing on the probabilities and cost effects of undesirable events, such as stock-outs, breakdowns and route failures, and their associated recourse actions. Tractability is achieved through the ability to pre-compute or at least partially pre-process the stochastic information, which is possible under mild assumptions for a general inventory policy. We integrate the stochastic aspect into a mixed integer non-linear program, illustrate applications to various problem classes, and show how to model specific problems through the lens of inventory routing. The case study is based on two sets of realistic instances, representing a waste collection inventory routing problem and a facility maintenance problem, respectively. We analyze the effects of our assumptions on modeling realism and tractability, and demonstrate that our framework significantly outperforms deterministic policies in its ability to limit the number of undesirable events for the same routing cost.

      PubDate: 2018-06-19T03:17:37Z
  • Effects of train speed on airline demand and price: Theory and empirical
           evidence from a natural experiment
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Kun Wang, Wenyi Xia, Anming Zhang, Qiong Zhang
      This study investigates, both theoretically and empirically, the effects of high-speed rail (HSR) speed on airline traffic and price, taking into account the degree of substitutability between the two services. Our model incorporates two countervailing effects of HSR speed, namely the “travel time” effect and the “safety” effect: while increasing HSR speed reduces HSR travel time, it may bring about a safety concern especially in emerging HSR markets such as China. Our theoretical analysis suggests that HSR speed impact on airline traffic and price depends on the relative dominance of the travel-time and safety effects, and air-HSR substitutability may reinforce the HSR speed effect. Furthermore, HSR speed has a larger impact on airline traffic than on airline price. Our empirical results from a rare natural experiment of HSR speed reduction in China show that HSR speed reduction raises both airline traffic and price, suggesting the dominance of travel-time effect. More importantly, consistent with the theoretical prediction, the HSR speed effect is empirically stronger on short-haul routes where the airline and HSR services are more substitutable.

      PubDate: 2018-06-19T03:17:37Z
  • The joy of flying: Efficient airport PPP contracts
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Eduardo Engel, Ronald Fischer, Alexander Galetovic
      We derive the optimal concession contract for an airport where the concessionaire’s effort impacts either non-aeronautical revenue (shops, restaurants, parking lots and hotels) or aeronautical revenues (passenger and airline fees). Our first model assumes that demand for the infrastructure is exogenous whereas demand for non-aeronautical services depends both on passenger flow and on the concessionaire’s effort and diligence. We show that the optimal principal-agent contract separates exogenous and endogenous risks. First, the term of the concession varies inversely with passenger flow, so that the concessionaire bears no exogenous demand risk. Second, the concessionaire bears part or all of non-aeronautical risk, which fosters effort. We also study a model where the concessionaire’s effort affects demand for aeronautical services and focus on the case where the contract includes a demand trigger for investment as an incentive. Both optimal contracts can be implemented with a Present-Value-of-Revenue (PVR) auction in which firms bid on the present value of aeronautical revenue and the concession ends when the bid is collected. PVR auctions have been used to auction airport PPP contracts in Chile, and demand triggers for investment have been used both in Brazil and Chile.

      PubDate: 2018-06-19T03:17:37Z
  • A mobility network approach to identify and anticipate large crowd
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Zhiren Huang, Pu Wang, Fan Zhang, Jianxi Gao, Maximilian Schich
      The study of large crowd gatherings combines aspects of longer-range human mobility with site-specific pedestrian dynamics. Recently, substantial progress has been made in understanding the collective behaviors of crowds on the site-specific scale. Yet, the human mobility aspect remains vague in terms of how large crowds come together in the first place. Using high-resolution human mobility data in form of millions, potentially real-time, subway and taxi records, our approach uncovers the mobility patterns involved in large crowd gatherings. In addition, we discriminate anomalous mobility fluxes from ordinary mobility fluxes by introducing the concept of anomalous mobility networks, within which nodes are traffic zones and links are defined via the Jensen-Shannon divergence. Our approach allows for easy identification of occurrence, location and developing stages of crowd formation. Strikingly, within the anomalous mobility networks, we find high-stress crowd density to be preceded by a node in-degree k in surpassing the critical threshold kc , typically preceding the maximum crowd density by a couple of hours, enabling us to anticipate large crowd gatherings via a surprisingly simple approach based on the simple network index k in.

      PubDate: 2018-06-19T03:17:37Z
  • A consistent reliability-based user-equilibrium problem with risk-averse
           users and endogenous travel time correlations: Formulation and solution
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): A. Arun Prakash, Ravi Seshadri, Karthik K. Srinivasan
      The traditional traffic assignment model has been extended in the literature to incorporate uncertainty and travelers who are sensitive to it. However, the proposed formulations that model risk-averse users lack (i) a consistent representation of the various stochastic quantities involved and (ii) a general solution approach. In this context, this study formulates a consistent, reliability-based user-equilibrium problem with risk-averse travelers. In the proposed formulation, various stochastic quantities are consistent with each other: the stochastic origin–destination demands result in stochastic path-flows and in turn stochastic link-flows, which result in stochastic link travel times, and travelers make decisions based on the stochasticity of travel times. The formulation also incorporates (i) endogenous link-flow variances and covariances and (ii) flow-dependent and endogenous link travel time correlations. At equilibrium – which is defined over the distributions of travel times and flows – no user can improve her travel time reliability by unilaterally changing route. The conditions for existence of a solution to the formulated problem are presented. A gradient projection based algorithm is proposed to solve the formulated problem, which is demonstrated to be correct and efficient through computational experiments. We also show that ignoring consistency in the formulation can lead to potentially erroneous conclusions. Experiments also demonstrate that the solution can be sensitive to the demand levels, stochasticity in demand, and users’ degree of risk-aversion. This work has the potential to make existing reliability-based user-equilibrium formulations more general and operational. It also has important applications in reliability-based traffic planning and management.

      PubDate: 2018-06-19T03:17:37Z
  • A hierarchical mixture modeling framework for population synthesis
    • Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Lijun Sun, Alexander Erath, Ming Cai
      Synthetic population is a key input to agent-based urban/transportation microsimulation models. The objective of population synthesis is to reproduce the underlying statistical properties of real population based on available microsamples and marginal distributions. However, characterizing the joint associations among a large set of attributes is challenging because of the curse of dimensionality, in particular when attributes are organized in a hierarchical household-individual structure. In this paper, we use a hierarchical mixture model to characterize the joint distribution of both household and individual attributes. Based on this model, we propose a framework of generating representative household structures in population synthesis. The framework integrates three models: (1) probabilistic tensor factorization, (2) multilevel latent class model, and (3) rejection sampling. With this framework, one can generalize not only the associations of within- and cross-level attributes, but also reproduce structural relationships among household members (e.g., husband-wife). As a case study, we implement this framework based on the household interview travel survey (HITS) data of Singapore, and then use the inferred model to generate a synthetic population pool. This model demonstrates great potential in reproducing the underlying statistical distribution of real population. The generated synthetic population can serve as a replacement for census in developing agent-based models, with privacy and confidentiality being protected and preserved.

      PubDate: 2018-06-19T03:17:37Z
  • Multi-stage airline scheduling problem with stochastic passenger demand
           and non-cruise times
    • Authors: Selim
      Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Özge Şafak, Özlem Çavuş, M. Selim Aktürk
      We propose a three-stage stochastic programming model which determines flight timing, fleeting and routing decisions while considering the randomness of demand and non-cruise times. Our model differs from the existing two-stage stochastic models by considering not only flight timing and potential passenger demand, but also expected operational expenses, such as fuel burn and carbon emission costs. We include aircraft cruise speed decisions to compensate for non-cruise time variability so as to satisfy the time requirements of the passenger connections. We handle nonlinear functions of fuel and emission costs associated with cruise speed adjustments by utilizing mixed integer second order cone programming. Because the three-stage stochastic model leads to a large decision tree and can be very time-consuming to solve optimally, we suggest a scenario group-wise decomposition algorithm to obtain lower and upper bounds for the optimal value of the proposed model. The lower and upper bounds are obtained by solving a number of group subproblems, which are similar to proposed multi-stage stochastic model defined over a reduced number of scenarios. We suggest a cutting plane algorithm, along with improvements, to efficiently solve each group subproblem. In the numerical experiments, we provide a significant cost savings over two-stage stochastic programming and deterministic approaches.

      PubDate: 2018-06-07T07:39:45Z
  • Transportation network redundancy: Complementary measures and
           computational methods
    • Authors: Xiangdong Anthony; Chen Sarawut Jansuwan Chao Yang Seungkyu Ryu
      Abstract: Publication date: August 2018
      Source:Transportation Research Part B: Methodological, Volume 114
      Author(s): Xiangdong Xu, Anthony Chen, Sarawut Jansuwan, Chao Yang, Seungkyu Ryu
      Redundancy is vital for transportation networks to provide utility to users during disastrous events. In this paper, we develop two network-based measures for systematically characterizing the redundancy of transportation networks: travel alternative diversity and network spare capacity. Specifically, the travel alternative diversity dimension is to evaluate the existence of multiple modes and effective routes available for travelers or the number of effective connections between a specific origin-destination pair. The network spare capacity dimension is to quantify the network-wide residual capacity with an explicit consideration of travelers’ mode and route choice behaviors as well as congestion effect. They can address two fundamental questions in the pre-disaster transportation system evaluation and planning, i.e., "how many effective redundant alternatives are there for travelers in the normal or disruptive event'" and "how much redundant capacity does the network have'" To implement the two measures in practice, computational methods are provided to evaluate the network redundancy. Numerical examples are also presented to demonstrate the features of the two redundancy measures as well as the applicability of the computational methods. The analysis results reveal that the two measures have different characterizations on network redundancy from different perspectives, and they can complement each other by providing meaningful information to both travelers and planners.

      PubDate: 2018-06-07T07:39:45Z
  • The generalized rollon-rolloff vehicle routing problem and savings-based
    • Authors: Hongqi Xiaorong; Jian Xinyu Chang Yingrong
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Hongqi Li, Xiaorong Jian, Xinyu Chang, Yingrong Lu
      Taking the waste collection management as the practical background, the rollon-rolloff vehicle routing problem (RRVRP) involves tractors pulling large containers between customer locations and the disposal facility. Each used-tractor begins and ends its route at the depot. Customer demand includes emptying a full container, ordering an empty container or changing a container. The objective is to find tractor routes that feature the minimum amount of total nonproductive time. In the literature the RRVRP is formulated as the node routing problem, and the “trip” definition that is the complete transport service of a container is used. To relax some assumptions of the RRVRP to cater to practical desires, we present a variant called the generalized RRVRP (G-RRVRP). The G-RRVRP generalizes the practical background, the objective function and the demand flow, and considers specially container loading and unloading time constraints. The G-RRVRP classifies demand into loaded-container demand and cargo demand with time windows. On condition of respecting container loading/unloading time and customer time windows, the G-RRVRP can design tractor routes for the synchronous scheduling of loaded and empty containers so as to ensure the timeliness of transport service. The G-RRVRP aims to minimize the total running cost of used tractors, instead of the total nonproductive time of tractors adopted by the RRVRP. A mixed integer linear programming model for the G-RRVRP is proposed. The Benders decomposition algorithm involving Pareto-optimal cuts and Benders decomposition-callback implementation, and a two-stage heuristic involving the savings algorithm followed by a local search phase are provided. The mathematical formulation and the two-stage heuristic are tested by solving 40 small-scale instances and 20 benchmark instances. Small-scale instances can be solved directly by CPLEX through the Benders decomposition strategies to find exact solutions. The case study indicates the applicability of the G-RRVRP model and the two-stage heuristic to realistic-size problems abstracted from intercity linehaul systems. The computational experiments and case study indicate that the heuristic can solve various instances of the G-RRVRP such that the solution quality and the computation time are acceptable.

      PubDate: 2018-05-28T21:13:47Z
  • Multiple depot vehicle scheduling with controlled trip shifting
    • Authors: Lucie Desfontaines; Guy Desaulniers
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Lucie Desfontaines, Guy Desaulniers
      The multiple depot vehicle scheduling problem (MDVSP) has been widely studied in the context of public transit systems. Given a timetable of bus trips, it consists of finding a set of bus schedules that covers every trip exactly once while satisfying vehicle availability at each depot and minimizing the operating costs. This work considers a generalization of the MDVSP that allows slight modifications of the trip scheduled start times. By shifting some trips, one can indeed expect to cover all trips with fewer vehicles or less expensive deadheads (vehicle moves without passengers). However, reducing the operational costs in this way should not be too detrimental to the overall quality of the timetable and, therefore, the following criteria should be controlled: the number of shifted trips, the headways between the consecutive trips of a line, and the quality of some passenger connections. To solve this generalized problem, we develop a two-phase matheuristic: the first phase computes vehicle schedules with a column-generation heuristic; the second relies on a mixed integer program to find the best possible timetable considering the computed vehicle schedules. Penalties are introduced in the first phase to increase the chances of finding a better-quality timetable in the second phase. Computational tests on real-life datasets from a bus company show that the proposed matheuristic can solve the problem efficiently, yielding solutions with a significant reduction in the number of vehicles used compared to the solutions of the classical MDVSP and a limited alteration of the timetable.

      PubDate: 2018-05-28T21:13:47Z
  • Compensation and profit distribution for cooperative green pickup and
           delivery problem
    • Authors: Junwei Wang; Yang Jiafu Tang
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Junwei Wang, Yang Yu, Jiafu Tang
      Cooperation is a powerful strategy to achieve the objective of the green pickup and delivery problem (GPDP) that minimizes carbon emissions of pickup and delivery service. However, the cooperative GPDP may not be accepted by all the partners, as the cost of cooperative GPDP may be higher than that of the non-cooperative minimum cost PDP. Therefore, a reasonable compensation mechanism is desired to form an acceptable cooperative GPDP, and a fair method of profit distribution, based on the mechanism, is needed to stabilize the cooperation. In this paper, we analyze the situations in which a compensation is needed and develop the lower bound of the compensation. Further, we propose an exact method to calculate the actual compensation and the profit distribution based on cooperative game theory. The proposed exact method can efficiently solve the largest scale instance in Li & Lim benchmarks, i.e., pdptw1000-LR1_10_1 with 1,054 customers and 19,306 products. The proposed compensation and profit distribution mechanism based on cooperative game theory is also applied to a real-world GPDP and achieve satisfactory performance. Some interesting and important managerial insights are found and discussed.
      Graphical abstract image

      PubDate: 2018-05-28T21:13:47Z
  • A column generation-based heuristic for aircraft recovery problem with
           airport capacity constraints and maintenance flexibility
    • Authors: Zhe Liang; Fan Xiao Xiongwen Qian Lei Zhou Xianfei Jin
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Zhe Liang, Fan Xiao, Xiongwen Qian, Lei Zhou, Xianfei Jin, Xuehua Lu, Sureshan Karichery
      We consider the aircraft recovery problem (ARP) with airport capacity constraints and maintenance flexibility. The problem is to re-schedule flights and re-assign aircraft in real time with minimized recovery cost for airlines after disruptions occur. In most published studies, airport capacity and flexible maintenance are not considered simultaneously via an optimization approach. To bridge this gap, we propose a column generation heuristic to solve the problem. The framework consists of a master problem for selecting routes for aircraft and subproblems for generating routes. Airport capacity is explicitly considered in the master problem and swappable planned maintenances can be incorporated in the subproblem. Instead of discrete delay models which are widely adopted in much of the existing literature, in this work flight delays are continuous and optimized accurately in the subproblems. The continuous-delay model can improve the accuracy of the optimized recovery cost by up to 37.74%. The computational study based on real-world problems shows that the master problem gives very tight linear relaxation with small, often zero, optimality gaps. Large-scale problems can be solved within 6 min and the run time can be further shortened by parallelizing subproblems on more powerful hardware. In addition, from a managerial point of view, computational experiments reveal that swapping planned maintenances may bring a considerable reduction in recovery cost by about 20% and 60%, depending on specific problem instances. Furthermore, the decreasing marginal value of airport slot quota is found by computational experiments.

      PubDate: 2018-05-28T21:13:47Z
  • Data-driven distributionally robust optimization approach for reliable
           travel-time-information-gain-oriented traffic sensor location model
    • Authors: Ning Zhu; Chenyi Shoufeng
      Abstract: Publication date: July 2018
      Source:Transportation Research Part B: Methodological, Volume 113
      Author(s): Ning Zhu, Chenyi Fu, Shoufeng Ma
      Travel time is one of the most intuitive pieces of traffic information to help decision makers to control real-time traffic conditions and to guide travelers to choose a reasonable route. An optimal sensor location scheme can obtain reliable route travel time information. Most current travel-time-oriented sensor location models are deterministic and assume a given and correct travel time probability density function. Nevertheless, due to widespread observational and systematic errors, prior travel time information is not accurate or reliable. In our study, a novel data-driven link-based network sensor location method is proposed to maximize travel time information gain. The effect of route differentiation is considered, and the sensors are located at links rather than at nodes. In addition, to account for the uncertainty in the prior travel time distribution, the distributionally robust travel time information gain sensor location (DRTTIGSL) model is presented. The prior distribution information is taken into account based on a statistical measure called ϕ-divergence. The ϕ-divergence is used to construct the uncertainty set. The reformulation of DRTTIGSL is dependent on the choice of ϕ-divergence and is tractable. Extensive numerical experiments are conducted to verify the effectiveness of the DRTTIGSL model. Compared with the optimal solutions for the deterministic model, the optimal solutions for the DRTTIGSL model can reduce the worst-case situation with a small price of the average objective value, especially when the total budget is not large.

      PubDate: 2018-05-28T21:13:47Z
  • Boundary conditions and behavior of the macroscopic fundamental diagram
           based network traffic dynamics: A control systems perspective
    • Authors: R.X. Zhong; Y.P. Huang; C. Chen; W.H.K. Lam; D.B. Xu; A. Sumalee
      Abstract: Publication date: Available online 9 March 2018
      Source:Transportation Research Part B: Methodological
      Author(s): R.X. Zhong, Y.P. Huang, C. Chen, W.H.K. Lam, D.B. Xu, A. Sumalee
      Macroscopic fundamental diagram (MFD), establishing a mapping from the network flow accumulation to the trip completion rate, has been widely used for aggregate modeling of urban traffic network dynamics. Based on the MFD framework, extensive research has been dedicated to devising perimeter control strategies to protect the network from gridlock. Recent research has revealed that the stochasticity and time-varying nature of travel demand can introduce significant scattering in the MFD, thus reducing the definition of the MFD dynamics. However, this type of demand effect on the behavior of the MFD dynamics has not been well studied. In this article, we investigate such effect and propose some appropriate boundary conditions to ensure that the MFD dynamics are well-defined. These boundary conditions can be regarded as travel demand adjustment in traffic rationing. For perimeter control design, a set of sufficient conditions that guarantee the controllability, an important but yet untouched issue, are derived for general multi-region MFD systems. The stability of the network equilibrium and convergence of the network dynamics are then analyzed in the sense of Lyapunov. Both theoretical and numerical results indicate that the network traffic converges to the desired uncongested equilibrium under proper boundary conditions in conjunction with proper control measures. The results are consistent with some existing studies and offer a control systems perspective regarding the demand-oriented behavior analysis of MFD-based network traffic dynamics. A surprising finding is that if the control purpose is to regulate the traffic to a desired level of service, the perimeter control gain can be simply chosen as its desired steady state, that is, the control gain is a constant and can be implemented as proportional control. This property sheds light on the road pricing design based on the MFD framework by minimizing the gap between the actual traffic state and the desired traffic state.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.02.016
  • Estimating the spatiotemporal impact of traffic incidents: An integer
           programming approach consistent with the propagation of shockwaves
    • Authors: Zhengli Wang; Xin Qi; Hai Jiang
      Abstract: Publication date: Available online 8 March 2018
      Source:Transportation Research Part B: Methodological
      Author(s): Zhengli Wang, Xin Qi, Hai Jiang
      A fundamental issue in estimating the spatiotemporal impact of an incident is to ensure that the shape of the affected region in the speed map is consistent with the propagation of shockwaves. In this research, we develop an integer programming model with a set of novel constraints to guarantee such consistency, which is new to the literature. The input to our model includes the historical speed on a given road as well as the location and starting time of a known incident. The model then outputs the spatiotemporal region impacted by this incident. We prove that our model produces results that are consistent with the propagation of shockwaves. We then show that our model is computationally more efficient than the current state-of-the-art model because ours requires substantially fewer constraints. Numerical experiments using both simulation and real data demonstrate that the reduction in computational time can be as large as 95–98% on average.

      PubDate: 2018-04-15T13:53:50Z
      DOI: 10.1016/j.trb.2018.02.014
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