Ramp Control Method Based On Vehicle Behavior Optimization Under Connected And Automated Vehicles Environment

With the rapid development of the internet of things,cloud computing,big data,artificial intelligence and the new generation of wireless mobile communications,the transportation industry is actively using technological innovation to explore the transition to the"Connected Automated Vehicle Highway（CAVH）"stage,which mainly includes vehicle automation,information connection,and system integration.As the skeleton of the transportation system,the freeway is a huge application challenge of CAVH,because it is facing serious traffic congestion under the normalization of flow oversaturation.Aiming at the on-ramp scenario where freeway congestion often occurs,this paper summarizes the hierarchical control framework of CAVH,and builds a vehicle behavior optimazition model based on rolling horizon control and presents ramp control strategies,in order to achieve the orderly and effectively incorporation of ramp vehicles under traffic oversaturation conditions,improve the efficiency of mainline traffic,optimize system safety performance and increase passenger comfort.Firstly,this paper studies the architecture of CAVH,and explains the composition of the control framework,main functions of cloud and vehicle-road system.Then,this paper introduces the idea of hierarchical control and control flow.Among them,the vehicle flow controller of the cloud system obtains the traffic flow status and control information of the road section,forms a traffic flow optimization control instruction and issues it to the vehicle controller,and the vehicle controller calculates the vehicle control curve to meet the requirements of the control instruction.Secondly,for the vehicle controller in hierarchical control,a vehicle behavior optimazition model based on rolling horizon control under connected and automated vehicles environment is established to calculate the optimal car following curve and lane change time.Since the lane change decision may occur at any time,in order to obtain the optimal solution of the model,the original problem is divided into several simplified sub-problems by discrete changing decision time.The numerical solution of the optimal control problem is solved based on Pontryagin’s minimization principle and steepest descent method.Thirdly,this paper builds the scene of the freeway on-ramp,and proposes two ramp control strategies of cooperative lane changing and ramp traffic flow control.Cooperative lane changing strategy,which is based on vehicle behavior optimazition model,creates a safe lane-change gap to ensure that the on-ramp vehicles smoothly enter the mainline at a lower cost.Meanwhile,based on cooperative lane changing strategies,this paper proposes ramp traffic flow control strategies.The full acceleration of ramp vehicles on the acceleration lane is satisfied by the segmented control strategy of the acceleration lane and the traffic flow state in downstream of mainlane keeps stable near the set value by using ALINEA controller.Finally,based on Matlab,a numerical simulation environment for freeway on-ramps is set up,and traffic flow simulation in connected and automated vehicles environment is performed.Indicators such as delay,reciprocal of time to collision(TTC^-1)and deceleration are set up to evaluate two ramp control strategies including cooperative lane changing and ramp traffic flow control and verify the effectiveness of the vehicle controller and the flow controller and analyze the sensitivity of the related parameters of ramp control strategies.The results show that when the length of the pure acceleration area is 80m,the influx of ramp vehicles has the least disturbance to the traffic flow of the mainline and under the condition of using the optimal pure acceleration zone length,the ALINEA controller will improve the mainline capacity by 10.7%.