Cooperative Control Method Of Automated Vehicles And Intersections Under Mixed Traffic Environment

With the development of connected and automated vehicle(CAV)technology,improving the operation efficiency of urban road traffic system through CAV technology is considered as a new way to solve the problem of urban traffic congestion.Since the replacement of the traditional human-driven vehicles takes some time,the urban traffic system is likely to be in a mixed traffic environment for a long time,including the automatic driving,connected humandriven and traditional human-driven vehicles.With the mixed traffic flow as the research background,this paper explores the cooperative control strategies and methods of connected and automated vehicles and intersections.In this paper,a platoon-based control optimization model is proposed for the mixed traffic environment.The vehicles in the same lane are divided into different platoons as the basic unit,and the overall traffic state of the platoon is estimated according to the information of connected vehicles.This model not only ensures the accuracy of information prediction but also reduces the complexity of the model.By judging the behavior of the platoon in different traffic scenarios,the delay prediction of the platoon is obtained.Therefore,an optimization model aiming at minimizing travel delay is established.In this process,the signal scheme is taken as the decision variable,and the speed guidance of the connected and automated vehicle is considered.The branch-and-bound method is used to solve the model,and the signal scheme is updated in real time.At the same time,the vehicle adjusts the acceleration and deceleration according to the established guidance speed.Finally,this paper builds a simulation platform to analyze and evaluate the model algorithm,and it was compared with other control methods in different traffic scenarios.The results show that the range of travel delay reduction of the cooperative control model proposed in this paper is significantly larger than that of the adaptive control and fixed-time control under the condition of medium and high degree of saturation.At low degree of saturation,the improvement of performance is marginally compared with that of the adaptive control,but it is still better than that of the fixed time control.When the degree of saturation is constant and the penetration rate of connected vehicles is lower than 40%,the higher the penetration rate of connected vehicles(connected autonomous driving vehicles and connected human-driven vehicles),the better the performance is.However,when the penetration rate of connected vehicles exceeds 40%,the performance improvement is marginal.In addition,the more autonomous vehicles connected to the network,the lower the trip delays are.