一种噪声环境下的汽车自适应巡航控制策略

A Vehicle Adaptive Cruise Control Strategy in Noise Environment

为了满足车辆在实际跟车环境下的行驶需求,设计了一种面向噪声环境的自适应巡航控制策略。控制策略根据两车跟车运动学模型,针对信息采集过程中,噪声对车载传感器信号准确性影响较大的问题,设计了面向跟车模式的卡尔曼滤波器对传感器信号进行降噪处理。通过对模糊控制算法的设计,实现对汽车期望加速度的计算,并将结果交由底层控制算法,达到对汽车速度与车距的精确控制。在PreScan和Matlab/Simulink环境下搭建了联合仿真模型,并对策略控制效果进行比较分析。结果表明,在噪声环境中,该制策略对不同水平的噪声干扰信号有较强的适应能力,并能实现对车速与车距的精确且快速控制,满足跟车环境下安全性与舒适性。

In order to meet the driving needs of vehicles in the actual following car environment,an adaptive cruise control strategy for noise environment was designed.According to the kinematics model of two vehicles following,for information acquisition process,the noise problem of on-board sensor signal had a great influence on the accuracy,a Kalman filter for following mode is designed to de-noise the sensor signals.Through the design of the fuzzy control algorithm,the calculation of the expected acceleration of the vehicle is realized,and the results are handed over to the underlying control algorithm to achieve the precise control of the vehicle speed and vehicle distance.A co-simulation model was built under the environment of PreScan and Matlab/Simulink,and the effect of strategy control was compared and analyzed.The results show that in the noise environment,this control strategy has strong adaptability to different levels of noise interference signals,and can achieve accurate and rapid control of vehicle speed and vehicle distance,and meet the safety and comfort in the following environment.