Research On Simulation And Test Of Lane Departure Warning And Keeping Control System

With the rapid growth of the global motorization,the traffic safety problems caused by human factors such as driver errors or distractions are becoming more and more prominent.The advanced driver assistance system,as the representative of vehicle active safety technology,is an effective measure to alleviate or solve the traffic safety problems.And the lane departure warning and keeping control system is an important part of the advanced driver assistance system.it can help the driver to improve the driving safety and comfort.Thus,the theoretical and experimental research on lane departure warning algorithm and lane keeping control algorithm are carried out in this paper.Firstly,the background and significance of lane departure warning and keeping control system,especially lane departure warning technology and lane keeping control technology,are introduced.On the basis of analyzing the technical requirements of lane departure warning and keeping control system,the frame structure of the system is established.The electric power steering system is also the actuator of lane keeping control system.In order to avoid the conflict of two working modes,steering system control strategy is designed,which includes mode switching control strategy?the conventional power control strategy and active steering control strategy.Secondly,by analyzing the advantages and disadvantages of several common warning algorithms at home and abroad,a joint warning algorithm of TLC and CCP is proposed to improve the accuracy and effectiveness of warning algorithm.And the joint warning algorithm is verified by the CarSim/Simulink simulation experiment.The driver's intention recognition module is established based on signals of steering lamp,steering wheel and brake or accelerator pedal.The system combines warning algorithm to decide whether or not to warn the driver.Thirdly,this paper presents a PSO-BP neural network PID lane keeping control algorithm.Elitist strategy and adaptive inertia weight are used to improve the basic PSO algorithm,and the improved PSO algorithm optimizes BP neural network's initial weights and threshold,then the BP neural network is used to adjust PID controller's proportion,integral and differential parameters on-line.The PSO-BP neural network PID lane keeping control algorithm is verified by the CarSim/Simulink simulation experiment.Finally,based on the 32 bit fixed-point DSP multimedia processor,lane departure warning system's vehicle test hardware platform is established.And by performing vehicle test both on straight and curve road under different weather and traffic conditions,the lane departure warning system's effectiveness and accuracy are verified.Based on the LabVIEWRT system of NI company,hardware in the loop test platform of the lane keeping control system is established,which includes the main/target machine,interface system and hardware system.The results of hardware in the loop test are consistent with the simulation results,so the effectiveness and reliability of the lane keeping control system is verified.