Modeling and Managing Mixed On-Demand Ride Services of Human-Driven Vehicles and Autonomous Vehicles

The authors model a monopoly ride-sourcing market where the platform adopts the service types of human-driven vehicles (HVs) and autonomous vehicles (AVs). Both congestion externality under mixed traffic flow and heterogeneity on riders' perceived utility of the ride-sourcing service are considered when formulating the mode choice behavior of riders. The authors analyze the impact of the platform's fleet size and its price for riders on demand rates and riders' waiting time in the market equilibrium state. The analytical results show that the demand rates of mixed on-demand ride service types are not necessarily monotonous to the price for riders or the fleet size, due to the congestion externality and existence of a wild goose chase regime. Under either profit maximization or welfare maximization strategies, numerical results demonstrate that a higher pure AV traffic flow capacity benefits human ride-sourcing drivers and both types of riders. The platform should arrange more AVs than HVs even under the high AV depreciation cost. In a surging demand scenario, the platform should encourage riders to switch from the HV service to the AV service through price regulation. Moreover, an extended scenario considering the integrated service is discussed. The economic analysis and gained managerial insights benefit the on-demand ride services platform's decision making on operational strategies of HVs and investment in AVs with mixed traffic congestion effects.

• Record URL:
  https://doi.org/10.1016/j.trb.2022.01.003
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261522000091
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Mo, Dong
  • Chen, Xiqun (Michael)
  • Zhang, Junlin
• Publication Date: 2022-3

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 80-119
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 157
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Demand responsive transportation; Externalities; Fleet management; Human beings; Markets; Mode choice; Motor vehicles; Pricing; Ridesourcing; Vehicle mix
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01835943
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 15 2022 9:49AM