Design And Simulation Of Connected And Autonomous Vehicles Control Strategy In Ramp Merging Area

The ramp is an important node connecting the mainline with other roads.Traditional traffic control methods with the help of a semaphore or set the speed limit to control of ramp vehicles and the mainline.Due to part of the ramp vehicles in the process of trying to import the mainline traffic flow from seeking to can be inserted into the gap,which causes in the end of the acceleration lane vehicle lane-changing behavior to take mandatory and interferes with the normal operation of the mainline traffic flow.When the traffic flow is large,it may lead to congestion in the merging area.The intelligent network connection technology can expand the vehicle's perception range and cooperate with the real-time information interaction of the traffic control center.So it can improve the vehicle operation in the ramp merging area.Therefore,the study on the control strategy of the ramp merging in the intelligent network environment is of great significance to improve the traffic capacity and vehicle operation efficiency in the ramp merging area.This paper first analyzes the traffic characteristics of the ramp merging area.This paper studies and analyzes the vehicle operation characteristics of each section in the merging zone from the macroscopic traffic flow and microscopic vehicle operation mechanism,and analyzes the characteristics of the time headway and interchangeable vehicle clearance in the merging zone,so as to provide theoretical basis for the proposal of the ramp merging control scheme.Secondly,the intelligent network vehicle control scheme is designed in the ramp merging area.The control system architecture of the ramp merging control is constructed by the maximum capacity of the merging area and the minimum vehicle travel time as the control targets and the vehicle spacing of upstream vehicles in the merging area as the control content.Based on the model predictive control method,the vehicle spacing in the merging process was optimized and the genetic algorithm was established to solve the process.Thirdly,the simulation architecture of control strategy based on cellular automata model is constructed.According to the intelligent network environment and control scene,the simulation environment based on cellular automata was built.The vehicle driving model under the intelligent network environment is constructed,including the following model and lane changing model.Calibrate the control parameters of each region;MATLAB language is used for programming to reproduce the running state of the traffic flow in the merging area.Finally,the ramp merging process under different environment is evaluated from three aspects of traffic flow,vehicle journey time and unsuccessful merging ratio,and the influence relationship between ramp flow and main traffic flow is discussed,as well as the effectiveness of intelligent network connection on-ramp merging control strategy.The simulation results show that the adoption of intelligent network technology can increase the traffic efficiency in ramp merging area.Different traffic flow density and different control strategies have different effects on the main line and ramp vehicle operation in the ramp merging area.In the low density traffic flow,the adoption of intelligent network technology has little influence on the vehicle operation in the merging area.The intelligent network vehicle control strategy can significantly reduce the travel time of vehicles and improve the success rate of ramp merging.