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Evaluating shared autonomous vehicles through agent-based discrete event simulation
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AI
DOI：10.1080/17477778.2026.2655766.png)
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Abstract
En 中文
Shared autonomous vehicles (SAVs) are increasingly integrated into urban transport, yet effective evaluation tools for fleet sizing and charging infrastructure are lacking. This study develops an agent-based discrete event simulation model to evaluate SAV service levels and costs. Tested on the Manhattan road network, the model simulates interactions between vehicles and infrastructure agents. Key results show: (1) a heuristic charging deployment algorithm improves passenger waiting times compared to even distribution; (2) for small fleets, more charging stations significantly boost performance, though this effect diminishes once fleet size exceeds 6,600; and (3) while increasing charging stations reduces unsatisfied demand for smaller fleets, larger fleets eventually saturate demand regardless of station density. These findings offer insights for optimizing SAV fleet management and infrastructure deployment.
Keywords:
Agent-based simulation
discrete event simulation
shared autonomous vehicles
Journal
J
IF:
1.7
Papers:
43
Citations:
839