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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    Titel :

    A predictive collision detection protocol using vehicular networks


    Beteiligte:


    Erscheinungsdatum :

    01.10.2017


    Format / Umfang :

    535141 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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