Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem

Operation of on-demand services like taxis, dynamic ridesharing services, or vehicle sharing depends significantly on the positioning of idle vehicles to anticipate future demand and operational states. A new queueing-based formulation is proposed for the problem of relocating idle vehicles in an on-demand mobility service. The approach serves as a decision support tool for future studies in urban transport informatics and design of new types of urban mobility systems like carsharing, ridesharing, and smart taxis. A Lagrangian Decomposition heuristic is developed and compared with a relaxed lower bound solution. Using New York taxicab data, the proposed algorithm reduces the cost by up to 27% compared to the myopic case.

• Record URL:
  https://doi.org/10.1016/j.tre.2017.08.003
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554517300121
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Sayarshad, Hamid R
  • Chow, Joseph Y J
• Publication Date: 2017-10

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 60-77
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 106
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Algorithms; Demand responsive transportation; Mobility; Queuing; Ridesharing
• Subject Areas: Passenger Transportation; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01646520
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 25 2017 2:10PM