With the widespread development of automated driving systems (ADS), it is imperative that standardized testing methodologies be developed to assure safety and functionality. Scenario testing evaluates the behavior of an ADS-equipped subject vehicle (SV) in predefined driving scenarios. This paper compares four modes of performing such tests: closed-course testing with real actors, closed-course testing with surrogate actors, simulation testing, and closed-course testing with mixed reality. In a collaboration between the Waterloo Intelligent Systems Engineering (WISE) Lab and AAA, six automated driving scenario tests were executed on a closed course, in simulation, and in mixed reality. These tests involved the University of Waterloo’s automated vehicle, dubbed the “UW Moose”, as the SV, as well as pedestrians, other vehicles, and road debris. Drawing on both data and the experience gained from executing these test scenarios, the paper reports on the advantages and disadvantages of the four scenario testing modes, and compares them using eight criteria. It also identifies several possible implementations of mixed-reality scenario testing, including different strategies for data mixing. The paper closes with twelve recommendations for choosing among the four modes.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations


    Additional title:

    Sae Int. J. Adv. and Curr. Prac. in Mobility


    Contributors:

    Conference:

    WCX SAE World Congress Experience ; 2020



    Publication date :

    2020-04-14


    Size :

    19 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations

    Antkiewicz, Michał / Kahn, Maximilian / Ala, Michael et al. | British Library Conference Proceedings | 2020


    FUNDAMENTAL CONSIDERATIONS AROUND SCENARIO-BASED TESTING FOR AUTOMATED DRIVING

    Neurohr, Christian / Westhofen, Lukas / Henning, Tabea et al. | British Library Conference Proceedings | 2020


    Fundamental Considerations around Scenario-Based Testing for Automated Driving

    Neurohr, Christian / Westhofen, Lukas / Henning, Tabea et al. | IEEE | 2020


    Highly immersive driving simulator for scenario based testing of automated driving functions

    Prokop, Günther / Tüschen, Thomas / Eisenköck, Norman et al. | Springer Verlag | 2022


    Highly immersive driving simulator for scenario based testing of automated driving functions

    Prokop, G. / Tüschen, T. / Eisenköck, N. et al. | British Library Conference Proceedings | 2022