Research On Cooperative Adaptive Cruise Control System Based On Robust Model Predictive Control

Due to the accelerating urbanization process,the pressure on the transportation is also rising sharply,such as the frequent occurrence of traffic accidents,the serious road congestion,and the low efficiency of travel.Smart cars can solve this series of problems very well,that's why smart cars have been called research hotspots.As a main component of smart cars,the collaborative adaptive cruise control system has a great effect on improving travel efficiency and improving road safety.In this paper,a vehicle queue is taken as the research object,and a robust following control algorithm based on the model predictive control principle is adopted and the collaborative adaptive cruise control system is studied accordingly.Firstly,based on the idea of sub-module modeling,with the analysis of vehicle longitudinal dynamics,the inverse model of vehicle engine and the inverse model of braking system required by this subject are established.At the same time,through the actual test of the vehicle in CarSim,the transition curve of the vehicle during braking and driving work is obtained.The joint simulation of CarSim and Simulink are used to verify the accuracy and effectiveness of the model,which lays a foundation for the next research of collaborative adaptive cruise control system.Then,the longitudinal kinematics system model of the vehicle queue is established with the relative vehicle spacing,relative vehicle speed,self-vehicle speed,self-vehicle acceleration,and self-vehicle acceleration rate as state quantities.Through the analysis of the control objectives,safety and comfort are mainly taken into the analysis consideration,including the analysis of safety distance,relative speed,acceleration of vehicle and acceleration rate,and get the output of the system state.The first-order exponential function is chosen as the reference for the state output to avoid jitter caused by sudden changes in state.At the same time,in order to improve the robustness of the system,the feedback correction method is used to strengthen the robustness of the model predictive control algorithm and the MPC robust control algorithm is established,and the prediction equation,constrained optimization and feasible domain expansion are analyzed.By mathematical transformation,the objective function is transformed into a quadratic form,and the optimal control input sequence of the whole process is obtained,and the first element of the control input sequence of the optimal solution is input into the inverse longitudinal dynamic model,and get the throttle opening and brake pedal force required for the car to travel through the inverse vertical kinetic model.Finally,through the CarSim/Simulink joint simulation platform,five simulation conditions are set up to verify the effectiveness of the established control system.Through the hardware-in-the-loop real-time simulation platform,three kinds of simulation conditions are set up to verify the real-time and stability of the built control system.The two simulation results show that the robust adaptive predictive control cooperative adaptive cruise control system has good follow-up effect,and the safety and ride comfort of the vehicle are guaranteed.