Traffic flow control of the intersection in urban traffic system under the environment of internet of vehicles

In order to overcome the problems of poor effect of the traditional traffic flow control method and vehicle congestion queuing, this paper proposes a traffic flow control method based on genetic algorithm for the intersection of the urban traffic system under the environment of the Internet of vehicles. Under the environment of the Internet of vehicles, the vehicle-road communication architecture is constructed, the vehicle module, the roadside module and the communication module are designed, and the traffic flow information data is collected on this basis. Taking the total delay reduction at intersections as the optimization objective function, saturation, phase sequence of signal control strategy, green time of each phase after optimization and induced driving speed as constraints, the traffic flow control objective model is constructed. The optimal control scheme is obtained by using iterative optimization method and genetic algorithm to control the traffic flow at the intersection of urban traffic system. The experimental results show that under the control of the research method, the total number of queuing vehicles at intersections is significantly reduced, which effectively reduces the traffic congestion. According to the experimental results, it can be concluded that the research method has a good application prospect and provides theoretical support for the research in related fields.