The evolution towards autonomous driving involves operating safely in open-world environments. For this, autonomous vehicles and their Autonomous Driving System (ADS) are designed and tested for specific, so-called Operational Design Domains (ODDs). When moving from prototypes to real-world mobility solutions, autonomous vehicles, however, will face changing scenarios and operational conditions that they must handle safely. Within this work, we propose a fuzzy-based approach to consider changing operational conditions of autonomous driving based on smaller ODD fragments, called $\mu$ ODDs. By this, an ADS is enabled to smoothly adapt its driving behavior for meeting safety during shifting operational conditions. We evaluate our solution in simulated vehicle following scenarios passing through different $\mu$ ODDs, modeled by weather changes. The results show that our approach is capable of considering operational domain changes without endangering safety and allowing improved utility optimization.


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    Title :

    Fuzzy Interpretation of Operational Design Domains in Autonomous Driving


    Contributors:


    Publication date :

    2022-06-05


    Size :

    743013 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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