As driving scenarios and autonomous vehicles (AVs) become increasingly intricating, there is an increasing need for innovative frameworks that can enhance and test AV capabilities across diverse scenarios. At present, the design and validation for AVs predominantly rely on simulation software or real-road testing methodologies. However, these approaches possess inherent limitations, leading to inaccuracy, reduced efficiency, and potential hazards during the development process. This letter reports our first DHW (decentralized and hybrid workshop) on Scenarios Engineering (SE), that aims to calibrate and validate AV modules through advanced scenarios. Specifically, the DHW discusses combining SE with existing simulation software and real-road testing strategies, enabling developers to maximize the advantages of each approach while ensuring the safety and efficacy in the development of autonomous vehicles. Our findings demonstrate the benefits of enhancing realism of simulation scenarios in the aspects of both content and appearance. Furthermore, the use of scenarios engineering is explored in order to enhance the diversity and safety of real-road testing by means of integrating virtual and physical components.


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    Titel :

    Advanced Scenario Generation for Calibration and Verification of Autonomous Vehicles


    Beteiligte:
    Li, Xuan (Autor:in) / Teng, Siyu (Autor:in) / Liu, Bingzi (Autor:in) / Dai, Xingyuan (Autor:in) / Na, Xiaoxiang (Autor:in) / Wang, Fei-Yue (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.05.2023


    Format / Umfang :

    2146565 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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