Task Offloading Strategy of Internet of Vehicles Based on Stackelberg Game

Moving vehicles generate a large amount of sensor data every second. To ensure automatic driving in a complex driving environment, it needs to fulfill a large amount of data transmission, storage, and processing in a short time. Real-time perception of traffic, target characteristics, and traffic density are important to achieve safe driving and a stable driving experience. However, it is very difficult to adjust the pricing strategy according to the actual demand of the network. In order to analyze the interaction between task vehicle and service vehicle, the Stackelberg game model is introduced. Considering the communication model, calculation model, optimization objectives, and delay constraints, this paper constructs the utility function of service vehicle and task vehicle based on the Stackelberg game model. Based on the utility function, we can obtain the optimal price strategy of service vehicles and the optimal purchase strategy of task vehicles.