With the advancement and reform of the automotive industry, intelligent driving vehicles have gradually penetrated the automobile market and entered a phase of peak development. Concurrently, the significant progress has been made in testing technology for intelligent driving vehicles. However, designing extreme testing scenarios remains a crucial and challenging problem in the field of vehicle testing. Therefore, this paper proposes an optimal method based on time window to create extreme scenarios for intelligent driving vehicle testing. By analyzing vehicle movement trajectories and incorporating the information such as size and volume of vehicles, more rational and realistic test scenarios are optimized. And simulation results demonstrate that the proposed method is reliable and effective.


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    Titel :

    Optimal method of extreme scenarios for intelligent driving vehicle testing based on time window


    Beteiligte:
    Ghanizadeh, Ali Reza (Herausgeber:in) / Jia, Hongfei (Herausgeber:in) / Qu, Ge (Autor:in) / Shi, Juan (Autor:in) / Zhang, Zhiqiang (Autor:in) / Guo, Kuiyuan (Autor:in)

    Kongress:

    Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023) ; 2023 ; Dalian, China


    Erschienen in:

    Proc. SPIE ; 13064


    Erscheinungsdatum :

    20.02.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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