Simulation can be an important tool in evaluating autonomous vehicle performance. In a virtual proving ground, challenging and highly unlikely scenarios can be created and novel control algorithms can be tested with no safety concerns and relatively little cost. A critical component of any virtual proving ground is sensor simulation; i.e., the ability to produce realistic sensor information inside the simulated environment. This paper overviews several models and methods for generating, through simulation, GPS, IMU, and lidar data. While the current models can account for some sensor noise, significant work remains to be done in order to produce simulated data that is realistic and can be used to confidently test and evaluate autonomous agents in virtual proving grounds.


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    Titel :

    Methods and Models for Simulating Autonomous Vehicle Sensors


    Beteiligte:
    Elmquist, Asher (Autor:in) / Negrut, Dan (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2020-12-01


    Format / Umfang :

    3600285 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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