Adverse weather conditions and occlusions in urban environments result in impaired perception. The un-certainties are handled in different modules of an automated vehicle, ranging from sensor level over situation prediction until motion planning. This paper focuses on motion planning given an uncertain environment model with occlusions. We present a method to remain collision free for the worst-case evolution of the given scene. We define criteria that measure the available margins to a collision while considering visibility and interactions and consequently integrate conditions that apply these criteria into an optimization-based motion planner. We show the generality of our method by validating it in several distinct urban scenarios.


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    Titel :

    Limited Visibility and Uncertainty Aware Motion Planning for Automated Driving


    Beteiligte:


    Erscheinungsdatum :

    2018-06-01


    Format / Umfang :

    5373615 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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