This paper proposes an algorithm for resolution of traffic conflicts occurring on an intersection, intended for Connected Autonomous Vehicle (CAV). The algorithm is based on the trade-off between energy consumption and user-defined value of time. The consequent cooperation opportunities originating from agent heterogeneity are captured by a game-theoretic cooperative-competitive solution approach to develop a computationally feasible, self-enforced, cooperative intersection de-conflicting algorithm. It is intended as a component of a robust framework for strategic control of the vehicle’s powertrain. Monte Carlo simulation is used to showcase the decision-making algorithm’s behaviour, to estimate its efficiency as a function of traffic heterogeneity. The results confirm that the proposed algorithm may offer threefold improvement in energy and time efficiency in relation to a First Come First Served scheme.


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    Titel :

    A Framework for Self-Enforced Interaction Between Connected Vehicles: Intersection Negotiation


    Beteiligte:


    Erscheinungsdatum :

    2021-11-01


    Format / Umfang :

    2670493 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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