We present solutions for autonomous vehicles in limited visibility scenarios, such as traversing T-intersections, as well as detail how these scenarios can be handled simultaneously. The approach models each problem separately as a partially observable Markov decision process (POMDP). We propose an approach for integrating limited visibility within a POMDPs and implementing them on a physical robot. In order to address scalability challenges, we use a framework for multiple online decision-components with interacting actions (MODIA). We present the novel necessary architectural details to deploy MODIA on an actual robot. The entire approach is demonstrated on a fully operational autonomous vehicle prototype acting in the real world at two different T-intersections.


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    Titel :

    POMDPs for Safe Visibility Reasoning in Autonomous Vehicles


    Beteiligte:


    Erscheinungsdatum :

    2021-03-04


    Format / Umfang :

    1823647 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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