This paper considers a coordination problem for Connected and Automated Vehicles (CAVs) in mixed traffic at unsignalized intersections. In such a setting, the behavior of the Human-Driven Vehicles (HDVs) is difficult to predict, thus challenging the formulation and the solution of the coordination problem. To solve this problem, we propose a coordination strategy, where CAVs are used as both sensors and actuators in mixed platoons. A timeslot-based approach is used to coordinate the occupancy of the intersection and to compensate for the HDVs behavior. The proposed approach has a bi-level optimization structure built upon the Model Predictive Control (MPC) framework that decides the crossing order and computes the vehicles’ commands. In simulations, we show that the choice of the HDV prediction model heavily affects the coordination by evaluating the performance of two different HDV models: car-following and constant velocity, where the latter demonstrates more consistent results in the presence of deviation of the HDVs’ behavior from a nominal model.


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    Title :

    Optimization-Based Coordination of Mixed Traffic at Unsignalized Intersections Based on Platooning Strategy


    Contributors:


    Publication date :

    2022-06-05


    Size :

    738725 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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