Abstract Although Autonomous Vehicles (AVs) will enhance mobility and safety, their impact on congestion is not clear yet. AVs may increase roadway capacity due to their connectivity features. The capacity enhancement highly depends on the AV proportion in traffic. This study models user equilibrium traffic assignment when the link capacity is a function of AV proportion of traffic. The mixed traffic flow of AVs and human-driven vehicles is considered as a multiclass traffic assignment problem. This problem is formulated as a non-linear complementarity problem which is solved to find optimal traffic management policies. We show that simple policies such as AV exclusive links can improve network performance in mixed traffic of AVs and human-driven vehicles. We also show that if these policies are implemented the network performance would be very close to system optimal condition even when users choose their routes selfishly following a user equilibrium. Results of numerical examples for a real size network show that management policies can decrease the gap between user equilibrium and system optimal to less than 1%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Optimal traffic management policies for mixed human and automated traffic flows


    Contributors:


    Publication date :

    2020-03-06


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Comparing traffic state estimators for mixed human and automated traffic flows

    Wang, Ren / Li, Yanning / Work, Daniel B. | Elsevier | 2017


    Optimal Policies in Complex Large-scale UAS Traffic Management

    Sacharny, David / Henderson, Thomas C. | IEEE | 2019


    Automated Traffic Management Handling Traffic Congestions

    Roy, Reema Anne / Patil, Sunita R | IEEE | 2022


    Automated Vessel Traffic Management

    Meine, Jurgen | Online Contents | 1998


    Automated Vehicle Identification in Mixed Traffic

    Li, Qianwen / Li, Xiaopeng / Yao, Handong et al. | IEEE | 2021