Automated vehicles are increasingly getting main-streamed and this has pushed development of systems for autonomous manoeuvring (e.g., lane-change, merge, and overtake) to the forefront. A novel framework for situational awareness and trajectory planning to perform autonomous overtaking in high-speed structured environments (e.g., highway and motorway) is presented in this paper. A combination of a potential field like function and reachability sets of a vehicle are used to identify safe zones on a road that the vehicle can navigate towards. These safe zones are provided to a tube-based robust model predictive controller as reference to generate feasible trajectories for combined lateral and longitudinal motion of a vehicle. The strengths of the proposed framework are: 1) it is free from non-convex collision avoidance constraints; 2) it ensures feasibility of trajectory even if decelerating or accelerating while performing lateral motion; and 3) it is real-time implementable. The ability of the proposed framework to plan feasible trajectories for high-speed overtaking is validated in a high-fidelity IPG CarMaker and Simulink co-simulation environment.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Trajectory Planning for Autonomous High-Speed Overtaking in Structured Environments Using Robust MPC


    Beteiligte:
    Dixit, Shilp (Autor:in) / Montanaro, Umberto (Autor:in) / Dianati, Mehrdad (Autor:in) / Oxtoby, David (Autor:in) / Mizutani, Tom (Autor:in) / Mouzakitis, Alexandros (Autor:in) / Fallah, Saber (Autor:in)


    Erscheinungsdatum :

    01.06.2020


    Format / Umfang :

    2286268 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Trajectory Planning for Autonomous High-Speed Overtaking using MPC with Terminal Set Constraints

    Dixit, Shilp / Montanaro, Umberto / Fallah, Saber et al. | IEEE | 2018


    A Trajectory Planning Algorithm for Autonomous Overtaking Maneuvers

    Zhang, Su Min ;Sun, Hao ;Wang, Yu | Trans Tech Publications | 2013


    Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios

    Ögretmen, Levent / Chen, Mo / Pitschi, Phillip et al. | ArXiv | 2024

    Freier Zugriff


    Trajectory optimization for autonomous overtaking with visibility maximization

    Andersen, Hans / Schwarting, Wilko / Naser, Felix et al. | IEEE | 2017