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Traffic big data assisted V2X communications toward smart transportation

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Abstract

In order to enable smart transportation, an efficient vehicle-to-everything (V2X) communication scheme is required. However, due to the mobility of vehicles and temporal varying features of vehicular environment, it is challenging to design an efficient communication scheme for vehicular networks. In this paper, we first give a review on the recent research efforts for solving communication challenges in vehicular networks, and then propose a traffic Big Data Assisted Communication scheme, BDAC, for vehicular networks. The proposed scheme uses past traffic big data to estimate the vehicle density and velocity, and then uses the prediction results to improve the V2X communications. We implement the proposed scheme in a multi-hop broadcast protocol to show the advantage of the proposed scheme by comparing with other baselines.

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Acknowledgements

This research was supported in part by JSPS KAKENHI Grant Nos. 18KK0279, 19H04093, JST-Mirai Program Grant No. JPMJMI17B3, and the Telecommunications Advanced Foundation.

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Authors and Affiliations

  1. Inner Mongolia Normal University, Hohhot, 010010, China

    Chang An

  2. The Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu-shi, Tokyo, 182-8585, Japan

    Celimuge Wu

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Correspondence to Celimuge Wu.

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An, C., Wu, C. Traffic big data assisted V2X communications toward smart transportation. Wireless Netw 26, 1601–1610 (2020). https://doi.org/10.1007/s11276-019-02181-6

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