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...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。展开更多
To improve the safety of the intended functionality(SOTIF)performance of autonomous driving systems,this paper proposed a design method for autonomous driving systems with uncertainties.The automatic emergency braking...To improve the safety of the intended functionality(SOTIF)performance of autonomous driving systems,this paper proposed a design method for autonomous driving systems with uncertainties.The automatic emergency braking(AEB)system is taken as an example to demonstrate the methodology.Firstly,uncertainty parameters in the AEB system model of typical working scenarios are defined and quantified,and a stochastic model of the AEB system with uncertainty parameters is established.Subsequently,the Monte Carlo simulation is employed to ascertain the actual safety distance distribution characteristics of the AEB system with uncertainties.The variance and width of the actual safety distance distribution are taken as response values to measure the reliability and robustness of the AEB system.The Box–Behnken design method is employed to design the uncertainty combination simulation test schemes.The surrogate models of uncertainty parameters with response variance and distributed width are established respectively,and the significance analyses are conducted.Finally,based on the variance surrogate models,the impact of uncertainties on the AEB system reliability and robustness is analyzed.This analysis provides the basis for the design of AEB system sensors.Based on the distributed width surrogate model,a dynamic safety distance adjustment mechanism is established to adjust the theoretical safety distance according to different uncertainties,thereby improving the reliability and robustness of the AEB system with multiple uncertainties.The method proposed in this paper provides a new idea for solving the SOTIF problems for autonomous driving systems.展开更多
文摘为提高雨、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。
基金financial support of the Key Research and Development Projects of Anhui Province(Grant No.202304a05020087)the Fundamental Research Funds for the Central Universities(Grant No.JZ2023YQTD0073)the Innovation Project of New Energy Vehicle and Intelligent Connected Vehicle of Anhui Province(Grant No.JZ2021AFKJ00002).
文摘To improve the safety of the intended functionality(SOTIF)performance of autonomous driving systems,this paper proposed a design method for autonomous driving systems with uncertainties.The automatic emergency braking(AEB)system is taken as an example to demonstrate the methodology.Firstly,uncertainty parameters in the AEB system model of typical working scenarios are defined and quantified,and a stochastic model of the AEB system with uncertainty parameters is established.Subsequently,the Monte Carlo simulation is employed to ascertain the actual safety distance distribution characteristics of the AEB system with uncertainties.The variance and width of the actual safety distance distribution are taken as response values to measure the reliability and robustness of the AEB system.The Box–Behnken design method is employed to design the uncertainty combination simulation test schemes.The surrogate models of uncertainty parameters with response variance and distributed width are established respectively,and the significance analyses are conducted.Finally,based on the variance surrogate models,the impact of uncertainties on the AEB system reliability and robustness is analyzed.This analysis provides the basis for the design of AEB system sensors.Based on the distributed width surrogate model,a dynamic safety distance adjustment mechanism is established to adjust the theoretical safety distance according to different uncertainties,thereby improving the reliability and robustness of the AEB system with multiple uncertainties.The method proposed in this paper provides a new idea for solving the SOTIF problems for autonomous driving systems.
