Randomized routing strategies of fleets of CAVs may prove market efficient

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

eets of CAVs, where revenue for eet 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 signi cant diversity, randomised CAV routing, resulting in unpredictable travel times for HDVs, is more e cient 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 eet operators and drive the competition towards social welfare oriented cooperation.