Modeling Evolution of Mode and Departure Choices in a Bi-Modal Network with User Inertia and Information Provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices and the resulting traffic dynamics in a bi-modal transportation system. Specifically, the authors consider that travelers can learn from their past travel experiences as well as the traffic forecasts offered by the transport information provider/agency in adjusting their departure time and mode choices, while the information agency learns from historical data in updating traffic forecast from day to day at the same time. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia has been taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, the authors find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling. Alternate title: Modeling Evolution of Mode and Departure Choices in a Bimodal Network with User Inertia and Information Provision.
  • Authors:
    • Liu, Wei
    • Li, Xinwei
    • Zhang, Fangni
    • Yang, Hai
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 18p

Subject/Index Terms

Filing Info

  • Accession Number: 01660259
  • Record Type: Publication
  • Report/Paper Numbers: 18-02879
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 8 2018 10:41AM