The control of an autonomous host vehicle at a crossroads intersection, in the presence of uncoordinated target vehicles, and without any crossing priority regulation is considered. The problem was spilt into two sub-problems, namely the priority and the path-planning problems. These problems are solved using a hierarchical controller. The lower control level is a linear controller to control the vehicle's speed and heading, to follow the reference signals provided by a middle-level algorithm. This middle-level controller is a Model Predictive Control (MPC) computed by modelling a unicycle model that is in a Linear Parameter-Varying (LPV) state-space model form. Different features are introduced for improving the prediction capability of the LPV-MPC. Prediction data computed by the MPC are used by the higher-level state-machine supervisor algorithm to determine when the host vehicle can safely cross the junction. The hierarchical controller was tested in simulation using a set of stressing scenarios. Reported results show the effectiveness of the proposed LPV-MPC in managing complex traffic scenarios with efficient compute.


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    Titel :

    LPV-MPC Path Planning for Autonomous Vehicles in Road Junction Scenarios


    Beteiligte:
    Cavanini, Luca (Autor:in) / Majecki, Pawel (Autor:in) / Grimble, Mike J. (Autor:in) / Ivanovic, Vladimir (Autor:in) / Tseng, H. Eric (Autor:in)


    Erscheinungsdatum :

    19.09.2021


    Format / Umfang :

    1752565 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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