This paper proposes an architecture for integrated decision-making, motion planning, and control in autonomous highway driving. The approach anticipates, to some degree, interactions between traffic participants and their reactive behavior to the actions of the autonomous vehicle (AV). To this end, we utilize an interaction-aware traffic prediction model to identify likely scenarios resulting from the current traffic scene, depending on the AV’s tactical decision options, which are evaluated by an ensemble of Scenario-based Model Predictive Controllers to decide on lane-changing maneuvers. We conduct a validation of two versions of the scenario generation using traffic data and demonstrate the combined architecture in a simulation study.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Scenario-Based Decision-Making, Planning and Control for Interaction-Aware Autonomous Driving on Highways


    Contributors:


    Publication date :

    2023-06-04


    Size :

    1076603 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Intention-aware Decision Making in Urban Lane Change Scenario for Autonomous Driving

    Song, Weilong / Su, Bo / Xiong, Guangming et al. | IEEE | 2018




    Interaction-Aware Decision-Making for Autonomous Vehicles

    Chen, Yongli / Li, Shen / Tang, Xiaolin et al. | IEEE | 2023


    PLANNING-AWARE PREDICTION FOR CONTROL-AWARE AUTONOMOUS DRIVING MODULES

    MCALLISTER ROWAN THOMAS / WULFE BLAKE WARREN / MERCAT JEAN et al. | European Patent Office | 2023

    Free access