Reliability-Based User Equilibrium in Dynamic Stochastic Networks: A Scenario Approach Considering Travel Time Correlations and Heterogeneous Users

Travel time reliability is a major factor in travelers’ route choice, and a critical attribute of service quality, so needs to be considered in transportation network planning. Each traveler’s route choice decision, considering a reliability measure, affects the reliability of travel time for other travelers in the network, giving rise to the reliability-based user equilibrium (RBUE) problem in stochastic networks. Studies to date regarding formulations and solution algorithms for the RBUE problem have been limited to simplified assumptions or very small networks. Previous work by the authors presented an RBUE problem formulation framework, which considers travel time correlation patterns in addition to the heterogeneity of users’ behavior, though assumed congestion patterns to be related to link travel time distributions and correlations through a simplified analytical formulation. There is still the need to more realistically account for the probabilistic nature of time and flow-dependent travel times in RBUE models. This study proposes a methodology to solve the RBUE problem in stochastic time-varying networks considering travel time correlations and heterogeneous users, with actual applications in realistic large-scale networks. The presented methodology updates link travel time distributions and correlations based on flow-dependent relations. Multiple simulation runs are conducted considering scenarios based on real-world observations to obtain time-dependent travel time distributions and correlations, and update them in each iteration of the gap-based descent direction method. An iterative solution procedure that minimizes a defined gap function is presented. The approach is implemented and tested on an actual large-scale network of Chicago, where 86 distinct scenarios are simulated to generate the initial travel time distributions and correlations. The numerical results show the successful application of the algorithm and its sensitivity to both the valuation of reliability by users and the correlation structure.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01698272
  • Record Type: Publication
  • Report/Paper Numbers: 19-05738
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:50AM