Research On Vehicle Cooperative Adaptive Cruise Control System

With the continuous development of intelligent transportation systems,Cooperative Adaptive Cruise Control(CACC)system has gradually become one of the important directions for the future development of the automotive industry.To further improve the performance of CACC system in tracking,comfort,fuel economy and road utilization,and reduce the impact of communication delay on the stability and safety of CACC system.This paper mainly studies the following aspects:Firstly,aiming at the predecessor-follower topology structure,a distributed CACC system is designed,in which the node controller is the upper-lower layer structure.The upper controller adopts the model predictive control(MPC)algorithm.By designing the performance cost function and inequality constraints,the conflicting control objectives of safety,tracking,comfort and fuel economy are comprehensively coordinated,and the relaxation vector method is introduced to solve the infeasible solution problem caused by hard constraints.The lower controller adopts PID control and feedforward control method to reduce the influence of vehicle parameters and environmental changes to the robustness of CACC system.Based on the Lyapunov theory,the asymptotic stability of the CACC system is proved,and the description method of string stability is given.Then,the evaluation index is established to quantify the comprehensive performance of the CACC system.Secondly,to give full play to the communication advantages of CACC system,aiming at the spacing strategy of CACC system,an error compensation prediction constant time headway spacing strategy considering relative speed,relative acceleration and spacing error is proposed.The spacing strategy is introduced into the MPC algorithm to optimize the prediction model and improve the forward-looking of the vehicles in the platoon.The numerical simulation results show that the CACC system has asymptotic stability and string stability under this strategy,which ensures the security of the platoon.Under different time headway,the tracking,comfort,fuel economy and platoon volatility of CACC system are further improved.Thirdly,aiming at the influence of communication delay on the comprehensive performance of CACC system,an MPC algorithm combined with improved grey prediction model is proposed.By adding differential operation and differential restoration operation,and introducing weight matrix,the prediction accuracy of the grey prediction model for the preceding vehicle state information in the communication delay time period is improved.The numerical simulation results show that the algorithm effectively reduces the influence of communication delay on the tracking,comfort,fuel economy and platoon volatility of CACC system under different delay scenarios.Finally,The vehicle model,simulation scene and sensor are set up in PreScan software.The upper controller and lower controller are built in Matlab/Simulink software,and the interface is connected to realize the co-simulation platform.The co-simulation is carried out under the Worldwide Harmonized Light Vehicles Test Cycle(WLTC)conditions.The results show that the MPC algorithm combining the error compensation prediction constant time headway strategy and the improved grey prediction model can further improve the comprehensive performance of the CACC system and reduce the impact of communication delay on the CACC system.The results verify the effectiveness and rationality of the algorithm.The research in this paper has certain reference value for the application of vehicle assisted driving.