Vehicular Ad-Hoc Network (VANET) is currently experiencing a critical technological transformation as more and more vehicles move to a higher level of automation. To cope with increasingly complex traffic conditions, automated vehicles need to maintain regular communication with each other. This highly dynamic topology structure poses significant challenges to routing protocols. This paper proposes a vehicle distribution prediction-based routing protocol called VDP. The protocol divides the map into grids, analyzes the role of different areas in a single grid by simulating the communication process between adjacent grids, and uses the neural network model to predict the distribution of vehicles in the grid. We combine the prediction results with the complexity of the urban environment to arrive at the optimal inter-grid path, which is then used for grid selection. Moreover, a grid-based routing method is proposed to select the optimal relay node according to real-time traffic information. All in all, VDP not only makes full use of the law of vehicle distribution but also can be flexibly adjusted according to the current actual situation. We have conducted extensive simulation evaluations to evaluate the performance of VDP under different prediction models. The experimental results on an accurate road map show that our method is superior to the existing position-based routing protocols.


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    Title :

    A Vehicle Distribution Prediction Based Routing Protocol in Large-Scale Urban VANET


    Contributors:
    Sheng, Yang (author) / Han, Weizhen (author) / Fang, Zhipeng (author) / Liu, Bingyi (author)


    Publication date :

    2022-05-04


    Size :

    1713422 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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