Vehicle repositioning for a ride-sourcing network system providing differentiated services

The increasing trend on adopting ride-sourcing services has brought obvious benefits to short-haul transportation systems. In this paper, the authors investigate a dynamic ride-sourcing system, where, in each period, a constant number of vehicles (fixed system capacity) is used to satisfy random customer demands or is reallocated within an under-investigation network. To save resources, the authors' objective is to deploy the smallest number of vehicles to satisfy the network system with differentiated service levels. Unlike the common approaches that achieve an equilibrium solution to match supply and demand by implementing a proper pricing and waging policies, based on the fixed vehicle capacity, the authors need to explicitly confront the region-to-region imbalance in the system by using appropriate reallocation strategies. The authors first formulate a framework for this type of ride-sourcing system and investigate the lower and upper bounds for the optimal vehicle capacity. Then, the authors discuss the conditions of obtaining the lower bound and the optimality of the upper bound. Based on the proposed model, the authors further design some heuristics to appropriately reallocate the vehicles. In particular, the authors introduce a benchmark heuristic that robustly performs between the lower and upper bounds. A variety of experiments are conducted to validate this benchmark for a wide choice of potential settings. Finally, besides satisfying the differentiated service levels, the authors generalize the model by incorporating the operation costs of maintaining the vehicle fleet, route dependent costs, and unequal travel times to adapt some common real-world situations.

• Record URL:
  https://doi.org/10.1016/j.trb.2023.02.002
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261523000152
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhong, Yuanguang
  • Zillmann, Stefan
  • Zhang, Ruijie
  • 0000-0001-8644-6190
  • Zhou, Yong-Wu
  • Xie, Wei
  • 0000-0002-5079-3315
• Publication Date: 2023-4

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 221-243
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 170
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Dispatching; Level of service; Ridesourcing; Short haul; Vehicle capacity; Vehicle fleets
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01878893
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 10 2023 11:58AM