Ensuring safety for highly automated vehicles (AVs) using complex algorithms including artificial intelligence is still an open research question. A first step towards the goal of achieving safe operation is the Responsibility Sensitive Safety (RSS) model proposed by Intel/Mobileye, which addresses the decision making of an AV system. However, RSS requires a correct environment model. Hence, to have a comprehensive overall AV safety case, additional solutions and argumentation are required, to verify correctness of the environment model. For this purpose we propose in this paper a novel solution, that uses a Monitor-Recovery approach based on a dynamic occupancy grid. The grid is used to verify the object information (Monitor) provided to RSS, and if required to correct wrong information (Recovery). Our results show that with this approach we can detect common failures of a perception system and successfully recover from those errors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Towards Online Environment Model Verification


    Contributors:


    Publication date :

    2020-09-20


    Size :

    522356 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Towards Verification of Model Transformations Via Goal-Directed Certification

    Karsai, G. / Narayanan, A. | British Library Conference Proceedings | 2008


    ONLINE SENSOR CALIBRATION VERIFICATION SYSTEM

    DERENICK JASON C / DING XUCHU / ZHANG SHUO et al. | European Patent Office | 2017

    Free access

    Towards Verification of Model Transformations Via Goal-Directed Certification

    Karsai, Gabor / Narayanan, Anantha | Springer Verlag | 2008


    Online sensor calibration verification system

    DERENICK JASON C / DING XUCHU / ZHANG SHUO et al. | European Patent Office | 2018

    Free access