Vehicle Route Selection Based on Game Evolution in Social Internet of Vehicles

Social development and technological advances have enabled the Internet of Vehicles (IoV) to combine the social factors to form a new intelligent transportation system: Social IoV (SIoV). The emergence of SIoV helps to find new traffic management solutions of the serious problems caused by the ever-increasing traffic flow. In this paper, we propose an algorithm called social vehicle route selection (SVRS) to reduce traffic congestion and achieve the purpose of traffic flow control. First, a social clustering method for SIoV is designed by utilizing both historical and current driving information. Then we use game evolution to calculate the optimal route for vehicles, and prove the vehicle route selection game is a potential game and its strategy selection converges to Nash equilibrium. Extensive simulations are carried out to evaluate the SVRS with several performance criteria. Our analysis and simulation results demonstrate that SVRS algorithm can achieve high performance in clustering the vehicles and reducing traffic congestion.