Research And Experimental Verification Of Cooperative Adaptive Cruise Control In Intelligent Networked Environment

In recent years,thanks to the rapid development of low delay and high reliability communication technology represented by dedicated short distance communication technology,it is possible to share information in real time among vehicles or between vehicles and transportation facilities.Based on the ACC system,the CACC system realizes the sharing of vehicle driving state information by means of communication between vehicles.Compared with the ACC system,the CACC system responds more quickly to road emergencies,which can better guarantee the safety of vehicles,shorten the following distance between vehicles,reduce vehicle energy consumption and improve road traffic efficiency.This thesis mainly studies the CCAC algorithm,and designs an intelligent mini-car test platform to test the algorithm.Firstly,aiming at the problems of high danger,high test cost,long test cycle and difficulty in building test platform in the test of control algorithm using Intelligent and Connected Vehicles,in this thesis,a test platform based on intelligent mini-car is built,and the CACC control algorithm is validated by simulating Intelligent and Connected Vehicles with intelligent mini-car.This thesis introduces the overall design of the test platform,the hardware and software system architecture design,the working principle and hardware implementation of each module in detail.Secondly,in the validation of CACC algorithm,the ability to drive automatically is the foundation,which can be understood as having the ability of lane keeping in this thesis.he lane image in front of the mini-car is acquired by the intelligent mini-car through on-board camera in real time,and the lane binary image is obtained through the pre-processing steps of region of interest selection,image graying and binarization.This thesis designs an lane edge point extraction algorithm based on lane width feature in binary image.The lane line equation is obtained by fitting the set of extracted lane line edge points through Hough transform.At the same time,the lane line equation is transformed from pixel coordinate system to world coordinate system,and the relative position between intelligent mini-car and lane line is determined.The yaw angle and yaw displacement are input into the lateral controller to calculate the control quantity of steering gear,and the lane keeping function of the mini-car is completed.Thirdly,based on the analysis of commonly used calculation methods of safety distance between vehicles and the existing CACC follow-up control strategies,this thesis designs a CACC system which is divided into upper and lower layers.The upper layer obtains the position and speed information of the front car through vehicle communication,based on the constant time headway calculation method of safety distance,The LQR controller is used to calculate the optimal acceleration of the vehicle,and the lower layer calculates the speed control quantity of the intelligent mini-car through the fuzzy PID controller.Aiming at the speed planning problem of the head car in CACC system,the head car in this thesis interacts with the signal lights.Based on the SPAT model,the optimal speed of the head car is determined according to the signal state information,so that the fleet can pass the signal lights in the green light time window as much as possible.Finally,the lane keeping test of a single mini-car and the CCAC algorithm test of two mini-cars are completed by test platform.Through a large number of experiments and data analysis,not only the feasibility and reliability of the intelligent mini-car and the test platform are verified,but also the effectiveness of the control algorithm of the CACC system is verified.