With self-driving vehicles being pushed towards the main-stream, there is an increasing motivation towards development of systems that autonomously perform manoeuvres involving combined lateral-longitudinal motion (e.g., lane-change, merge, overtake, etc.). This paper presents a situational awareness and trajectory planning framework for performing autonomous overtaking manoeuvres. 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 model predictive controller as reference to generate feasible trajectories for a vehicle. The strengths of the proposed framework are: (i) it is free from non-convex collision avoidance constraints, (ii) it ensures feasibility of trajectory, and (iii) it is real-time implementable. A proof of concept simulation is shown to demonstrate the ability to plan trajectories for high-speed overtaking manoeuvres.


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    Titel :

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


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


    Erscheinungsdatum :

    01.11.2018


    Format / Umfang :

    671090 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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