基于PreScan的AEB系统控制策略

吕晓娇¹，李方媛^1*，徐月云²，赵长利¹，郑刘源¹

1.山东交通学院汽车工程学院，山东 济南  250357；2.国家智能网联汽车创新中心，北京  100176

摘要：为提高雨、雾等恶劣天气下汽车自动紧急制动（automatic emergency braking，AEB）系统的适用性，提出一种基于有限状态机的分级预警与分级制动控制策略。综合考虑驾驶员特性和车辆运行状态，优化碰撞时间（time to collision，TTC）预警阈值与制动临界安全距离，通过控制制动减速度变化率，提高制动过程中的驾乘舒适性。在中国新车评价规程（China New Car Assessment Program，C-NCAP）2021版提出的前车静止（car-to-car rear stationary，CCRs）、前车匀速（car-to-car rear moving，CCRm）和车辆碰撞纵向行驶自行车（car-to-bicyclist longitudinal adult，CBLA-50）典型工况下，构建雾天测试场景，通过软件PreScan和MATLAB/Simulink联合仿真AEB分级控制策略，并与固定TTC阈值控制策略进行对比，验证AEB分级控制策略的可行性。仿真结果表明：天气状况为雾天时，固定TTC阈值控制策略在CCRs、CCRm、CBLA-50工况下避撞成功率分别为28.6%、66.7%、60.0%，车速较高时，无法实现避撞；分级控制策略在CCRs、CCRm、CBLA-50工况下的避撞成功率分别为100.0%、100.0%、93.3%，有效避撞的同时保证制动时的驾乘舒适性。

关键词：AEB系统；控制策略；制动；TTC

Control strategy of AEB system based on PreScan

LÜXiaojiao¹, LI Fangyuan^1*, XU Yueyun², ZHAO Changli¹, ZHENG Liuyuan¹

1.School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China;

2.National Innovation Center of Intelligent and Connected Vehicles, Beijing 100176, China

Abstract: In order to improve the applicability of the automatic emergency braking(AEB) system in severe weather such as rain and fog, a hierarchical warning and braking control strategy based on finite-state machine is proposed. Taking into account the driver′s characteristics and vehicle operating status, the time-to-collision(TTC) warning threshold and braking critical safety distance are optimized to improve the driving comfort during the braking process and control the rate of change of braking deceleration. Under the typical working conditions of car-to-car rear stationary(CCRs), car-to-car rear moving(CCRm), and car-to-cyclist longitudinal adult (CBLA-50) proposed in the 2021 version of the China New Car Assessment Program(C-NCAP), a foggy test scenario was constructed to simulate the AEB hierarchical control strategy through software PreScan and MATLAB/Simulink, and compared with the fixed TTC threshold control strategy to verify the feasibility of the AEB hierarchical control strategy. The simulation results show that when the weather conditions are foggy, the success rate of collision avoidance of the fixed TTC threshold control strategy under CCRs, CCRm, and CBLA-50 working conditions is 28.6%, 66.7%, and 60.0%, respectively. When the vehicle speed is high, collision avoidance cannot be achieved. The success rate of collision avoidance of the hierarchical control strategy under CCRs, CCRm, and CBLA-50 working conditions is 100.0%, 100.0%, and 93.3%, respectively, which effectively avoids collisions while ensuring driving comfort during braking.

Keywords: AEB system; control strategy; braking; TTC