Dynamic Resource Management for Ridesharing Systems in Urban Transportation Networks

Rapid advancement of self-driving vehicle technologies holds the promise to revolutionize on-demand ridesharing service as an exciting way of delivering shared mobility. Yet, significant imbalance between spatiotemporal distributions of vehicle supply and travel demand poses a pressing challenge. This paper proposes a multi-period game-theoretic model that addresses dynamic pricing and idling vehicle dispatching problems in the context of driverless on-demand ridesharing services. A dynamic mathematical program with equilibrium constraints (MPEC) is formulated to capture the interdependent decision-making processes of the mobility service provider (e.g., regarding vehicle allocation) and travelers (e.g., regarding ride-sharing and travel path options). An algorithm based on approximate dynamic programming (ADP), with customized subroutines for solving the MPEC, is developed to solve the overall problem. It is shown with numerical experiments that the proposed dynamic pricing and vehicle dispatching strategy can help ridesharing service providers achieve better system performance (as compared with myopic policies) while facing spatial and temporal variations in ridesharing demand.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB00 Section - Travel Analysis Methods.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Lei, Chao
    • Jiang, Zhoutong
    • Ouyang, Yanfeng
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01697786
  • Record Type: Publication
  • Report/Paper Numbers: 19-04927
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:37AM