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Shared low-speed autonomous vehicles for short-distance trips: agent-based modeling with mode choice analysis

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  • Zihe Zhang
  • Jun Liu
  • Qifan Nie
  • Steven Jones

Abstract

Previous research has envisioned behavior changes with the availability of shared autonomous vehicle (SAV) services. It is expected that SAVs will compete with conventional human-driven vehicles and lead to a shift in mode share. If designed as single-occupancy, low-speed, and lightweight, SAVs can also be considered a micro-mobility mode targeting short-distance trips in geofencing areas, which has been lacking in discussion in the state-of-the-art literature. To address this gap, this study envisions changes in mode choice with the implementation of a single-occupancy Shared Low-speed Light-weight Autonomous Mobility (SLLAM) system deployed, serving trips at speeds below 25 mph. Agent-based simulations are conducted to evaluate the mode share of the SLLAM system. The findings demonstrate that the SLLAM system has the potential to serve 36.98% of the trip demand in the study area. Increased operating speeds enhance the SLLAM mode share, making it a more attractive option for existing private vehicle trips.

Suggested Citation

  • Zihe Zhang & Jun Liu & Qifan Nie & Steven Jones, 2025. "Shared low-speed autonomous vehicles for short-distance trips: agent-based modeling with mode choice analysis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 48(2), pages 313-341, February.
    • Handle: RePEc:taf:transp:v:48:y:2025:i:2:p:313-341
    DOI: 10.1080/03081060.2024.2373322
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