Research On Intelligent Adaptive Cruise System Based On Model Predictive Control For Low Adhesion Road

With the increasing number of car ownership in the world,the traffic congestion,traffic accidents and environmental pollution problems caused by this have become more and more serious.As an important part of Advanced Driver Assistance Systems(ADAS),Adaptive Cruise Control(ACC)plays an important role in reducing the driver's operating burden,improving passenger comfort,improving road capacity and reducing fuel consumption.The research direction of this subject is: aiming at the intelligent adaptive cruise control of intelligent vehicle on low adhesion coefficient road surface,to control the adaptive cruising vertical and horizontal of the car on the low adhesion coefficient road such as ice and snow.The intelligent adaptive cruise system of this paper needs to identify the current road surface adhesion coefficient parameters.Therefore,parameters such as longitudinal acceleration and lateral acceleration of the vehicle traveling under different road conditions are collected.The NARX neural network algorithm is used to establish the road surface adhesion coefficient estimation model.The vehicle parameters collected above are used as the input of the model to estimate the adhesion coefficient of the road surface.For the lateral control of the vehicle,a lane keeping controller based on the model predictive control algorithm is proposed.Firstly,the lateral dynamics of the vehicle and the lateral characteristics of the tire are analyzed,and an improved tire model is introduced.A quasi-linear lateral dynamics system is established by using the method of linear variable parameters.It does not increase the computational complexity of the algorithm,but also overcomes the influence of low adhesion coefficient pavement on the model.In the framework of MPC algorithm,the control objectives and system constraints of lane keeping are established to reduce the lateral error of the vehicle as the control target,while restraining the increment of the front wheel angle to ensure the stability of the lane keeping control.For vehicle longitudinal control,the upper controller is designed to calculate the desired longitudinal acceleration,and the lower controller is designed to control the throttle and brake,so that the vehicle can accurately follow the desired acceleration.The upper controller can be divided into constant speed cruise and adaptive cruise according to the driving conditions.The cruise control uses the PID algorithm to calculate the desired longitudinal acceleration.The adaptive cruise system uses the MPC algorithm and selects a safe distance model that reflects the road surface attachment characteristics,which ensures the safety of the vehicle during actual driving.The lower controller establishes the switching strategy of acceleration/braking control,and establishes the inverse model of engine and brake respectively to track the desired acceleration.Combining with the longitudinal and lateral control of the vehicle,considering the influence of the longitudinal speed on the lateral control,the change of the longitudinal speed is input into the lateral control in real time to improve the control stability of the whole control system,and the adaptive longitudinal and lateral control of low adhesion coefficient pavement is realized.Finally,CarSim and Simulink are used to simulate the effectiveness of the algorithm under different conditions.