Order matching optimization of the ridesplitting service: A scenario with midway stops

Ridesplitting travel can provide numerous social and environmental benefits, including reducing vehicle usage and traffic congestion, and decreasing energy consumption and greenhouse gas emissions. This study examines the practicability of integrating the function of midway stops into ridesplitting services. Considering two coexisting matching forms: pre-pool-matching and en-route matching, the ridesplitting order dispatch problem with midway stops is formulated as an integer programming model with multiple objectives. Two methods are developed to address the proposed problem, i.e., an exact algorithm based on bipartite graph and a two-stage method based on Kuhn-Munkres algorithm. Based on the ride-hailing trip data, numerical experiments are conducted to examine the performance of the proposed methods. The authors also quantify the benefits of the ridesplitting matching with midway stops compared with the solo matching with midway stops and the traditional ridesplitting matching without midway stops. The impacts of the characteristics of midway stops on the order dispatching results are also discussed. The results indicate that compared with the solo ride-hailing matching with midway stops, the ridesplitting matching with midway stops could greatly improve distance savings of trips and the matching success rate of passengers. The research results can enrich the landing scene of ridesplitting service and promote the innovation and upgrading of this product.

• Record URL:
  • https://doi.org/10.1016/j.tre.2024.103936
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1366554524005271
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Abstract reprinted with permission of Elsevier.
• Authors:
  • Du, Mingyang
  • Li, Xuefeng
  • Cheng, Lin
  • Lu, Weike
  • Li, Wenxiang
• Publication Date: 2025-2

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: 103936
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 194
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Algorithms; Optimization; Ridesharing; Ridesourcing; Stopping
• Subject Areas: Data and Information Technology; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01943655
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 27 2025 11:34AM