Autonomous driving requires decision making in dynamic and uncertain environments. The uncertainty from the prediction originates from the noisy sensor data and from the fact that the intention of human drivers cannot be directly measured. This problem is formulated as a partially observable Markov decision process (POMDP) with the intention of the other vehicles as hidden variables. The solution of the POMDP is a policy determining the optimal acceleration of the ego vehicle along a preplanned path. Therefore, the policy is optimized for the most likely future scenarios resulting from an interactive, probabilistic motion model for the other vehicles. Considering possible future measurements of the surroundings allows the autonomous car to incorporate the estimated change in future prediction accuracy in the optimal policy. A compact representation allows a low-dimensional state-space so that the problem can be solved online for varying road layouts and number of other vehicles. This is done with a point-based solver in an anytime fashion on a continuous state-space. We show the results with simulations for the crossing of complex (unsignalized) intersections. Our approach performs nearly as good as with full prior information about the intentions of the other vehicles and clearly outperforms reactive approaches.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Decision making for autonomous driving considering interaction and uncertain prediction of surrounding vehicles


    Beteiligte:
    Hubmann, Constantin (Autor:in) / Becker, Marvin (Autor:in) / Althoff, Daniel (Autor:in) / Lenz, David (Autor:in) / Stiller, Christoph (Autor:in)


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    847514 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Decision Making for Autonomous Driving Considering Interaction and Uncertain Prediction of Surrounding Vehicles

    Hubmann, Constantin / Becker, Marvin / Althoff, Daniel et al. | British Library Conference Proceedings | 2017




    Automatic driving behavior decision-making system considering social preferences of surrounding vehicles

    JIN LISHENG / HAN GUANGDE / XIE XIANYI et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Expressway lane changing decision-making method and system considering driving styles of surrounding vehicles

    XIE XIANYI / FU HAOYAN / JIN LISHENG et al. | Europäisches Patentamt | 2024

    Freier Zugriff