Traffic big data assisted V2X communications toward smart transportation

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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