Autonomous driving vehicle is the mainstream trend of the development of the automotive industry at home and abroad. In the process of its research and development, many safety problems are frequently exposed. Therefore, the safety test of autonomous driving vehicles is particularly important. Autonomous driving vehicle testing can be carried out in three aspects: virtual simulation test, proving ground test and real road test. Among them, proving ground test , as a kind of real vehicle test, mainly tests typical dangerous scenarios. Based on the simulation software Carmaker, a method of automatic generation of simulation test cases is proposed in this paper. The method defines different parameter variables and parameter boundary, realizes the automatic combination of parameters through the editing and running of the code, and improves the efficiency of simulation test and the coverage of test cases. Through the high-efficiency and high-coverage hardware-in-the-loop simulation test, the dangerous test cases of typical scenarios are screened out for the proving ground test, so as to make the proving ground test more targeted and improve the efficiency of the proving ground test. Meanwhile, combination of virtual simulation and proving ground in actual test is able to ensure simulation result effectiveness.


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    Title :

    Research on screening methods of autonomous driving dangerous test cases based on Carmaker


    Contributors:
    Zhang, Zhiqiang (author) / Liu, Shaohua (author) / Zhang, Cheng (author) / Li, HongFei (author)

    Conference:

    International Conference on Smart Transportation and City Engineering 2021 ; 2021 ; Chongqing,China


    Published in:

    Proc. SPIE ; 12050 ; 120500L


    Publication date :

    2021-11-10





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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