基于蒙特卡洛的自动驾驶转向影响因子研究

Research on the Influence Factors of Autonomous Driving Steering Based on Monte Carlo

针对自动驾驶转向问题,基于蒙特卡洛算法进行影响因子对转向影响程度分析研究。首先,基于车辆运动状态创建车辆单点预瞄驾驶员模型,基于CarSim建立整车模型;然后,利用PB实验法对车辆转向显著影响因子进行筛选;其次,基于所建驾驶员模型和转向显著性影响因子,运用蒙特卡洛算法,完成自动驾驶转向横向偏差影响因子定量分析。研究结果表明,路面附着系数、丝杠导程、轮胎垂向刚度等对自动驾驶转向具有显著影响。

In response to the problem of autonomous driving steering,a Monte Carlo algorithm is used to analyze the degree of influence of influencing factors on steering.Firstly,the study creates a vehicle single point preview driver model based on the vehicle's motion state,and establishes a vehicle model based on CarSim.Then,the PB experimental method was used to screen the significant influencing factors of vehicle steering.Secondly,based on the established driver model and steering significance influencing factors,the Monte Carlo algorithm is used to quantitatively analyze the influencing factors of lateral deviation in autonomous driving steering.The research results indicate that road adhesion coefficient,screw lead,and tire vertical stiffness have a significant impact on autonomous driving steering.