Modern cars can detect unsafe driving by comparing the observed behavior of the subject vehicle (i.e., rear vehicles) with normal driving. However, normal driving does not have a standard definition. It changes depending on the situation. In this work, we address this problem and propose edge-assisted unsafe driving detection. In our proposal, instead of learning normal driving, the edge infers the most common unsafe driving patterns. It then shares this knowl-edge with cars. Cars look for such patterns to detect unsafe driving. Analysis of real-world traffic data shows that edge-assisted unsafe driving detection could detect unsafe behavior of subject vehicles with 90% accuracy.


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    Title :

    Poster: Edge-Assisted Unsafe Driving Detection


    Contributors:


    Publication date :

    2023-12-06


    Size :

    339456 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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