Research on the Behavior Decision of Connected and Autonomous Vehicle at the Signalized Intersection

In the traditional environment, there are traffic congestion and frequent traffic accidents at signalized intersections due to the lack of timely provision of vehicle and road-related information and insufficient management measures. This suggests that it is necessary to apply environmental awareness technology to solve the problem of multi-vehicle coordination at intersections, so as to improve the traffic safety and efficiency of existing traffic roads. In this paper, aiming at the information perception and behavior decision of Connected and Autonomous Vehicles at the signalized intersections, quantitative analysis is carried out through the vehicle speed trajectory optimization algorithm and the integrated analysis model of energy consumption and emission under different traffic conditions. The simulation results directly prove that the optimized speed guidance strategy can effectively improve the traffic efficiency of signalized intersections.