With the rapid development of autonomous driving technologies, the proportion of autonomous vehicles (AVs) will increase and influence road capacity. In this study, the simulation of mixed traffic flow was studied using an improved cellular automata model. Safety inter-vehicle spacing, the length of vehicles and reaction time are introduced into the cellular automata model. We delete the acceleration, deceleration and randomization rule for ideal conditions. Numerical simulations are utilized to analyze road capacity with different proportions of AVs. Road capacity is about 2200 pcu/h/lane for pure manual vehicle (MV) traffic flow and about 3600 pcu/h/lane for pure AV traffic flow. The capacity increases by 19.2% when there are 50% AVs in the traffic flow. And the capacity increases by around 63.6% due to the pure AV traffic flow. The results indicate that the improved cellular automata model proposed in this paper simulates the mixed traffic flow under ideal conditions more accurately.


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    Title :

    Research on Road Capacity in the Scenarios of Autonomous Vehicles in China


    Additional title:

    Sae Technical Papers


    Contributors:
    Li, Jian (author) / Chen, Jing (author) / Zhang, Ning (author) / Zhuo, Xi (author) / Du, Yuchuan (author)

    Conference:

    3rd International Forum on Connected Automated Vehicle Highway System through the China Highway & Transportation Society ; 2020



    Publication date :

    2020-12-30




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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