Randomized routing strategies of fleets of CAVs may prove market efficient

2026-07-16

AI Summary

This study addresses the design of market mechanisms for connected and autonomous vehicle (CAV) fleets to balance corporate profits with social welfare in urban transportation systems. Recognizing the heterogeneous attitudes of human drivers toward CAVs, the work proposes a randomized CAV routing strategy incentivized by market share and innovatively incorporates system-wide average travel time into the market mechanism’s objective function. By integrating multi-agent simulation, game theory, and traffic flow modeling, the authors compare multiple routing algorithms and demonstrate that, under significant heterogeneity in human driving behavior, the proposed randomized strategy outperforms conventional system-optimal or user-equilibrium approaches. Furthermore, imposing travel time constraints effectively curbs anti-social competitive behaviors among fleet operators, thereby enhancing overall traffic efficiency.

Abstract

In future cities every driver may own a vehicle which could be either independently driven (HDV), or autonomously routed and piloted (CAV). The autonomous operations could be handled by a few competing companies. What is the market structure which would make this market aligned with city goals? In this paper we discuss a variant of the emerging market of collectively routed fleets of CAVs, where revenue for fleet operators is proportional to market share. We provide benchmark scenarios to compare the routing algorithms. We present several routing algorithms and demonstrate that, when the attitudes of human drivers towards CAVs exhibit significant diversity, randomised CAV routing, resulting in unpredictable travel times for HDVs, is more efficient than routing proportional to system optimum/user equilibrium. Based on this, we propose to improve the design of the market by augmenting the market-share objective with mean systemwide travel time in order to limit antisocial randomised strategies of fleet operators and drive the competition towards social welfare oriented cooperation.

Problem

• CAVs
• market structure
• randomized routing
• social welfare
• traffic efficiency

Innovation

• randomized routing
• CAV fleets
• market design
• system efficiency
• human-autonomy interaction