基于道路摩擦系数估计的智能小车紧急避障策略研究

Research on Emergency Obstacle Avoidance Strategy of Intelligent Car Based on Road Friction Coefficient Estimation

雾霾环境下驾驶员的视野受到限制,无法准确估计周围的环境信息,对行车安全具有重大影响。自主紧急制动(AEB)系统是一种重要的车辆主动安全功能,用来避免碰撞或减轻碰撞程度。通常,AEB系统利用一个碰撞时间TTC衡量与障碍物发生碰撞的危险程度。通常设计用于制动的TTC门槛值时假设道路摩擦系数为常数,然而,道路情况复杂多变,道路摩擦系数也是变化的,驾驶员在雾霾环境下更难准确估计道路摩擦系数。因此,开发了一个考虑不同摩擦系数对TTC门槛值影响的AEB控制策略。首先用一个复合滑移率轮胎模型来估计峰值道路摩擦系数,再用该系数计算TTC的门槛值,进而利用该TTC门槛值衡量与障碍物发生碰撞的危险程度。因为可以实时识别道路摩擦系数,提出的AEB策略可以自适应雾霾环境下不同的道路表面。仿真结果表明了该方法的有效性。

The driver＇s vision is limited in the haze environment and cannot accurately estimate the surrounding environmental information, thus it has a significant impact on the traffic safety. Autonomous emergency braking （AEB） system is an important vehicle active safety function, which is used to avoid collision or reduce the de- gree of collision. Typically, the AEB system uses a collision time TTC to measure the risk of collisions with an obstacles. The road friction coefficient is typically assumed to be constant when the TTC threshold value is de- signed for braking. However, the road conditions are complex and varied, the road friction coefficient is also variable, it is more difficult for the driver to estimate the road friction coefficient accurately in the haze environ- ment. Therefore, an AEB control strategy considering the influence of different friction coefficients on the TTC threshold is developed. First, a composite slip-rate tire model is used to estimate the peak road friction coeffi- cient, then the estimated peak friction coefficient is used to calculate the TTC threshold, which is used to meas- ure the risk of collision with an obstacle. Since the road friction coefficient can be identified in real time, the proposed AEB strategy can be adapted to different road surfaces in haze environment. Simulation results show the effectiveness of the proposed method.