Cooperative Control Method Of Mixed Vehicle Groups Based On Spatiotemporal Equilibrium Assignment Of Traffic Flow

Facing the increasing urban traffic load,traditional traffic equipment and control methods cannot fundamentally solve the problem of traffic congestion.The development of cooperative vehicle infrastructure technology and autonomous driving technology has brought new means to solve this problem.Cooperative vehicle infrastructure system is gradually applied,and intelligent vehicles are continuously integrated into urban traffic to form a mixed traffic operation environment with traditional vehicles.This phenomenon has changed the traditional traffic management and control mode,and traditional traffic control methods have been unable to effectively deal with new traffic problems in the mixed traffic environment.Aiming at the mixed traffic operation environment composed of human-driven vehicle and connected and autonomous vehicle,this thesis aims to balance the spatiotemporal distribution of road network traffic,establishes a spatiotemporal equilibrium assignment model of traffic flow,and proposes a cooperative control method of mixed vehicle group to improve the traffic distribution and the overall efficiency of the road network.The main research contents of this thesis are as follows:(1)Aiming at the mixed traffic in the cooperative vehicle infrastructure environment,the macroscopic characteristics of the mixed traffic flow are analyzed based on macroscopic fundamental diagram model,and a mixed traffic flow transmission model is established on the basis of the traditional link transmission model,which can effectively characterize the mixed traffic flow transmission process.(2)The method of spatiotemporal equilibrium assignment of traffic flow is studied.Aiming at the overall efficiency optimization needs of the road network,according to the concept of spatiotemporal equilibrium,taking path distance,travel time and expected arrival time between origin and destination as indexs,the spatiotemporal equilibrium assignment model of traffic flow is established,and the solution process of the fixed-point algorithm is given to analyze the spatiotemporal distribution characteristics of traffic flow.(3)The cooperative control method of the mixed vehicle group is studied.Firstly,a discretization method of the traffic flow assignment scheme is proposed to generate the initial path scheme of the vehicle group cooperative control.Secondly,considering the different characteristics of the mixed vehicles,based on the The Logit model and IDUE principle,the path selection model of the human-driven vehicle is established,further the cooperative control strategy of the connected and autonomous vehicle group paths is established based on the concept of spatiotemporal equilibrium.Finally,a cooperative optimization method based on ant colony optimization simulated annealing algorithm is designed to improve the road traffic efficiency by optimizing the path selection of the vehicle group.(4)This thesis uses MATLAB software to build a mixed traffic flow transmission model to analyze the established traffic flow spatiotemporal equilibrium distribution model,and uses Paramics traffic simulation software to build a mixed traffic environment under vehicle-road coordination to simulate and verifie the proposed cooperative control method of mixed vehicle groups Based on spatiotemporal equilibrium assignment of traffic flow.Set different traffic demand and penetration rate of connected and autonomous vehicle,select different spatiotemporal equilibrium model parameters,and compare the spatiotemporal distribution characteristics of road network traffic flow;in the simulation environment,according to the traffic operation evaluation index,the effect of vehicle group cooperative control under different penetration rates is compared,and the method in this thesis is compared with the no-control mode to verify the effectiveness of the mixed vehicle group cooperative control.The results show that the method proposed in this thesis can balance the spatiotemporal distribution of road network traffic,improve road network traffic efficiency,alleviate road network traffic congestion,and efficiently utilize road network resources.The thesis includes 41 figures,15 tables and 71 references.