Vehicular safety technologies play a vital role in preventing or minimizing the impact of vehicle collisions to reduce life-threatening injuries and keep down vehicle collision-related casualties. One such application is connected vehicles, powered by vehicle-to-infrastructure (V2I) technology to enhance safety on road. It enables all the vehicles on a road within its range to communicate their speed, position, and heading direction to roadside unit (RSU) through cooperative awareness messages (CAM). This process needs three major operations. The first one is receiving the data from the vehicles, the second one detects the collision, and the third one communicates it with the vehicle in case of an impending collision. In this study, we developed a sophisticated algorithm to detect collisions. On detection of the impending collision, RSU sends a warning message to the concerned vehicle. This alerts the driver to take control measures like brake and speed limiting. Here, we implemented the intersection and rear-end collision scenarios using simulation of urban mobility (SUMO) traffic simulator and developed vehicular network (VANET) on network simulator OMNET++ . Veins framework combines both traffic and network simulator. Now using this computerized testbed, we can simulate the collision scenarios on the connected network and evaluate the timeline and data delivery rate with which the latter received the signal in order to take control actions like brake or halt the vehicle.


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    Titel :

    Virtual Testbed of Vehicular Network for Collision Simulation and Detection on SUMO and OMNeT++ Simulators


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Zhang, Yu-Dong (Herausgeber:in) / Senjyu, Tomonobu (Herausgeber:in) / So-In, Chakchai (Herausgeber:in) / Joshi, Amit (Herausgeber:in) / Ratnam, Tatini Shanmuki Krishna (Autor:in) / Lakshmikanthan, C. (Autor:in)


    Erscheinungsdatum :

    06.07.2022


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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