Despite numerous investments toward autonomous vehicle technology this past decade the ensured safe operation of these systems is still an unresolved issue for both commercial and defense systems due to decision uncertainty. In complex dynamic domains (e.g. intersections or congested terrain) the expected mode of operation for ensured safety of these unmanned systems is still direct human control (whether through direct vehicle input or through teleoperation). This paper presents research toward an autonomous vehicle safety reasoning system that provides a novel approach to temporally address scene uncertainty to increase the safety envelope for commercial and defense systems.


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    Titel :

    An anticipatory dynamic bayesian network approach towards an autonomous vehicle safety reasoning system


    Beteiligte:
    Frederick, Philip A. (Autor:in) / Cheok, Kac (Autor:in) / Del Rose, Mike (Autor:in) / Kania, Robert (Autor:in)

    Kongress:

    Unmanned Systems Technology XXIV ; 2022 ; Orlando,Florida,United States


    Erschienen in:

    Proc. SPIE ; 12124


    Erscheinungsdatum :

    31.05.2022





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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