摘要
AEB系统是一种通过自动制动来避免或减轻碰撞的主动安全技术,是生命安全和生产安全的重要保障,但AEB系统在无人驾驶的重型汽车的应用研究不充分,具有制动距离计算与此时刻路面信息无关、制动策略不分级和不考虑重型汽车轮胎刚度变化等问题。为提高无人驾驶重型底盘汽车AEB系统的安全性,以Duffgo轮胎模型为基础,通过计算实时的地面附着系数,从而准确计算制动距离,结合马自达安全距离模型建立分级的安全距离模型。建立TruckSim和Simulink联合仿真,将仿真结果与无迹卡尔曼滤波估计仿真结果进行比较,以制动结束时两车距离评价算法的纵向避撞性能,得出本文算法与无迹卡尔曼滤波估计算法相比在相同工况下更加平稳、介入时机更及时和准确的结论。本文提供了一种算法精简、安全距离可根据附着系数实时计算的AEB策略算法,促进了无人驾驶重型底盘汽车主动安全技术的发展。
Automatic emergency braking(AEB)is an active safety system that activates a car’s brakes when a potential collision is detected.It can save lives and ensure safety in industrial production.However,the AEB system of pilotless heavy vehicle has some problems,such as estimating braking distance calculation has nothing to do with road information at this moment,braking strategy is fixed,without level classification for different situations and tire stiffness changes of heavy vehicles are not considered.The research aims to enhance the safety performance of heavy vehicle AEB system.In this paper,based on the Dugoff tire model,by calculating the real-time ground adhesion coefficient,the accurate braking distance is calculated.Combined with Mazda-Model,a graded safety distance model is established,The co-simulation of TruckSim and Simulink is established,and the simulation results are compared with the simulation results of Unscented Kalman filter estimation.the longitudinal braking performance is judged by the distance between two vehicles at the end of braking.It is concluded that compared with the traditional algorithm,the minimum distance between two vehicles under the same working conditions is more stable,and the braking intervention time is timely and accurate.This paper provides an AEB strategy algorithm with simplified algorithm and real-time calculation of safety distance according to adhesion coefficient,which promotes the development for active safety technology of driverless heavy vehicle.
作者
宁满旭
王三舟
巴腾跃
唐小林
NING Manxu;WANG Sanzhou;BA Tengyue;TANG Xiaolin(Beijing Institute of Mechanical Equipment, Beijing 100854, China;College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2022年第6期72-80,共9页
Journal of Chongqing University of Technology：Natural Science
