Abstract The safety concerns for autonomous vehicles (AV) are shown to be a roadblock to their adoption. This paper addresses these concerns by studying a unified, game-theoretic framework (leader–follower game) of mixed traffic in which AVs and human-driven vehicles (HV) coexist, with endogenous vehicle demand and different types of accidents emerging in mixed traffic as crucial building blocks. We study the interaction between three types of players: (i) a policymaker, who decides on the liability regime and the level of V2I connectivity infrastructure, (ii) an AV producer, who decides on the AV price and safety level, and (iii) consumers, who differ in their preference for each vehicle type and choose the one they like best. Using both analytical and numerical tools, we analyze how the two policy variables, liability and V2I connectivity, affect behavior on the demand and supply side of the vehicle market and, in turn, AV market penetration and overall road safety. We also characterize optimal policies, thereby taking into account the market participants’ behavioral responses. Our findings provide guidance for a fast adoption of AVs and a smooth transition from existing traffic conditions to a mixed traffic environment, and assist in decision making for policymakers, legal agencies, traffic operation and transportation planning agencies, as well as car manufacturers.

    Highlights Game-theoretic framework of mixed traffic with autonomous and human-driven vehicles Endogenous AV demand and interaction between policymaker, AV producer and consumers Focus on (product) liability and V2I connectivity as key policy variables A higher level of AV safety might reduce the demand for AVs Stringent AV liability induces high safety investment but low AV market penetration


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    Title :

    Autonomous vehicles policy and safety investment: An equilibrium analysis with endogenous demand


    Contributors:


    Publication date :

    2024-02-20




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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