基于车辆前方目标运动模型的主动避撞系统的研究

Research on Active Collision Avoidance System Based on Vehicle Forward Target Movement Model

为提高毫米波雷达在探测目标运动状态方面的精确性,针对车辆前方目标运动特点,基于目标运动模型,采用卡尔曼滤波跟踪方法,根据城市道路车辆行驶的实际情况,选取当前统计模型作为机动目标模型,采用基于当前统计模型的卡尔曼滤波跟踪算法,应用Simulink搭建仿真模型,就匀速运动、匀加速运动及变加速运动3种前方目标行驶工况进行目标跟踪仿真对比试验。仿真结果表明:该算法可用于3种工况的目标跟踪,且误差小,具有良好的跟踪效果。搭建实车试验平台,采用一种安全距离模型,对目标跟踪算法进行实车试验。结果表明:使用该算法后车辆避免了碰撞,所建立的模型是可靠的。

In order to improve the accuracy of the millimeter-wave radar in detecting the movement state of the target,aiming at the characteristics of the target movement in front of the vehicle,the Kalman filter tracking method based on the target movement model is adopted. According to the actual situation of the urban road vehicle driving,the current statistical model is selected as the maneuver.The target model is based on the Kalman filter tracking algorithm based on the current statistical model. Simulink is used to build a simulation model to simulate the target tracking in three kinds offorward moving targets under uniform,accelerating and variable-speed motions. The simulation results show that the algorithm can be used for target tracking in three conditions with small error and good tracking effect. Then it builds a real vehicle test platform,using a safety distance model,the target tracking algorithm for real car test. The results show that the vehicle avoids collisions using this algorithm and the established model is reliable.