A novel generic sensor model is introduced for testing and validation of ADAS/AD (Advanced Driver Assistance Systems/Autonomous Drive) functions. The model converts an incoming object list into a sensor specific object list and is suitable for all ADAS/AD perception sensors operating on object level. The field of view of the sensor is represented by a two dimensional polygon, that can be defined by a set of points. A simple ray-tracing method is applied to simulate coverage by objects. The model allows multiple range specifications for a single sensor depending on object type and classification capabilities. A look-up table is used to convert the object class definitions of the virtual environment into the class definitions of the considered sensor. Additional object parameters that are detected by the sensor may be included. False negative and false positive detections are generated by probabilistic functions. The parametrisation procedure of the sensor model is explained and depicted in an example using the data sheet of the Radar Continental ARS404. The model's capability to simulate a complete sensor set is demonstrated with the sensor set of the Renault Zoe that was used to collect the nuScenes data set. The sensor model is integrated into a virtual test-bed using Vires VTD and Open Simulation Interface.


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    Titel :

    Object-based sensor model for virtual testing of ADAS/AD functions


    Beteiligte:


    Erscheinungsdatum :

    01.11.2019


    Format / Umfang :

    1462818 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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