Connected automated vehicles (CAVs) offer unparalleled opportunities to revolutionize existing transportation systems. Despite various prototype systems based on CAVs have been constructed, a simple yet realistic approximation of mixed traffic delay over signalized intersections is largely missing. This paper develops a stochastic analytical framework that integrates Markov chain analysis, car-following model, and queuing theory. Given the highly intricate nature of the mixed-traffic environment, to make the framework realistic while tractable, multiple factors' impact including free-flow speed, control gains boundaries, as well as CAVs market penetration rate is systematically incorporated in the proposed approximation framework via mathematical derivations. Finally, numerical simulations have been conducted to systematically evaluate the impact of multiple factors mentioned to gain a comprehensive understanding of mixed traffic delay on signalized intersections.


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    Titel :

    Markov-Based Analytical Approximation for Mixed Traffic Delay of Signalized Intersections


    Beteiligte:
    Yue, Ximin (Autor:in) / Li, Zihao (Autor:in) / Zhou, Yang (Autor:in) / Zhang, Yunlong (Autor:in)


    Erscheinungsdatum :

    24.09.2023


    Format / Umfang :

    632819 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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