Research On Adaptive Cruise Simulation Control Based On ADAS Experimental Platform

With the rapid development of the automotive industry and the advent of the 5G era,research on advanced automotive auxiliary driving systems(ADAS)by various industries and research scholars has become more in-depth.The adaptive cruise control(ACC)as an advanced driver assistance systems an integral part of(ADAS)is also received extensive attention.ACC can effectively reduce the driver's operating burden,improve road utilization,reduce road traffic accident rates,and also improve car comfort and fuel economy.Therefore,the research on adaptive cruise control is of great significance.This article takes adaptive cruise control system as the research object,carries out its control strategy and algorithm research,and carries out simulation experiments on the advanced assisted driving system(ADAS)experimental platform.The thesis mainly completes the following aspects:First,the function of the auto adaptive cruise control system is analyzed.Through the study of the system control strategy and the safety distance algorithm,the control strategy of adaptive cruise in the presence or absence of the vehicle is formulated,and the existing constant head distance(CTH)algorithm and variable head distance(VTH)algorithm for analysis,because the variable head time algorithm can maintain good robustness under complex working conditions,so the variable head time algorithm is finally adopted.Secondly,the controller algorithm of the adaptive cruise system is studied,and the working mode and switching strategy under different working conditions are formulated.The controller decides to adopt hierarchical control,which avoids the disadvantage of poor robustness of the direct control system in practical applications.Specifically divided into upper control and lower control.The upper controller is composed of cruise control algorithm and following mode algorithm,namely speed control and distance control.The cruise control algorithm uses traditional PID control,and the designed PID control algorithm is simulated in the MATLAB/Simulink development environment to debug the most ideal PID parameters;the linear quadratic optimal control(LQR)algorithm is used in the following mode.The LQR algorithm can make the vehicle have better following characteristics and smooth ride.The lower-level controller calculates the expected acceleration calculated by the upper-level controller and finally obtains the execution amount of the vehicle actuator,thereby realizing the control of the vehicle acceleration and braking.Once again,to verify the excellent performance of the adaptive cruise algorithm and strategy in this paper,this paper uses the test method of Car Sim and MATLAB/Simulink co-simulation,respectively for the front vehicle speed is greater than the current speed,the front vehicle speed is less than the current speed,and the front vehicle speed is sinusoidal Next,through joint simulation experiments to verify the feasibility of the algorithms and control strategies mentioned in the paper.Finally,the adaptive cruise control algorithm and control strategy studied in this paper are verified on the ADAS experimental platform.The verification results show that the proposed algorithm and control strategy can meet the requirements of automobile adaptive cruise control system,and can provide reference and reference for related research.