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紧急避撞路径规划及其跟踪驾驶员转向模型
引用本文:赵治国,胡昊锐,周良杰,王凯,冯建翔.紧急避撞路径规划及其跟踪驾驶员转向模型[J].同济大学学报(自然科学版),2020,48(7):998-1006.
作者姓名:赵治国  胡昊锐  周良杰  王凯  冯建翔
作者单位:同济大学 汽车学院,上海 201804
基金项目:国家自然科学基金联合基金(Ul564208)
摘    要:针对紧急避撞工况,提出并设计了一种紧急避撞路径规划方法和路径跟踪反馈预瞄驾驶员模型。首先,提出了一种基于Sigmoid曲线与物理约束的避撞路径规划方法,并建立融合最优曲率预瞄与闭环反馈转向修正的驾驶员模型以对所规划路径实现快速和精确跟踪。之后,搭建了CarSim+Simulink离线联合仿真平台,对避撞路径规划和路径跟踪反馈预瞄驾驶员模型的有效性进行了验证。最后,基于自主改装的试验车辆,进行实车试验以验证所提出的路径规划方法及驾驶员模型的可行性与实时性。仿真及实车试验结果均表明,所规划的避撞路径和驾驶员模型可以控制车辆快速、安全地避让障碍物。

关 键 词:紧急避撞工况  路径规划  驾驶员模型  联合仿真  实车试验
收稿时间:2019/10/10 0:00:00

Emergency Collision Avoidance Path Planning and Driver Steering Tracking Model
ZHAO Zhiguo,HU Haorui,ZHOU Liangjie,WANG Kai,FENG Jianxiang.Emergency Collision Avoidance Path Planning and Driver Steering Tracking Model[J].Journal of Tongji University(Natural Science),2020,48(7):998-1006.
Authors:ZHAO Zhiguo  HU Haorui  ZHOU Liangjie  WANG Kai  FENG Jianxiang
Institution:School of Automotive Studies, Tongji University, Shanghai 201804, China
Abstract:For the emergency collision avoidance condition, a new method of path planning and a path tracking feedback preview driver model were proposed and designed. Firstly, a collision avoidance path planning method based on Sigmoid curve and physical limitation was proposed, and a driver model combined with optimal curvature preview and closed-loop feedback steering correction was established to achieve the fast and precise tracking of the planned path. Then, the effectiveness of the collision avoidance path planning and the path tracking feedback preview driver model was verified by CarSim+Simulink offline co-simulation platform. Finally, based on the self-modified test vehicle, a real vehicle test was carried out to verify the feasibility and real-time of the proposed path planning method and driver model. Both the simulation and real vehicle test results show that, the planned path and driver model for collision avoidance can control the vehicle to avoid obstacles quickly and safely.
Keywords:emergency collision avoidance condition  path planning  driver model  co-simulation  real vehicle test
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