Vehicular traffic accidents are a crucial problem in big urban centers. Nearly one million people die in road crashes each year. In this paper, we propose a predictive vehicular collision detection protocol for VANETs. The proposed protocol takes advantage of the vehicle-to-vehicle communication in VANETs to predict potential collisions with vehicles in the proximity. Simulation results show that our proposed protocol achieves 92% accuracy in detecting collisions using real case Ottawa urban scenarios and several accidents scenarios. Also, applying a prediction model to estimate future trajectories of nearby vehicles, has significantly reduced the overhead of transmitted packets.


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    Title :

    A predictive collision detection protocol using vehicular networks


    Contributors:


    Publication date :

    2017-10-01


    Size :

    535141 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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