主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

汽车实用技术 ›› 2022, Vol. 47 ›› Issue (9): 14-23.DOI: 10.16638/j.cnki.1671-7988.2022.009.004

• 智能网联汽车 • 上一篇    

多条件约束下的汽车微观动态滚动轨迹规划

王雪莹 1,袁盛玥 1,张译芳 1,马世峰 2   

  1. 1.北京新能源汽车股份有限公司;2.长春孔辉汽车科技股份有限公司
  • 出版日期:2022-05-15 发布日期:2022-05-15
  • 通讯作者: 王雪莹
  • 作者简介:王雪莹(1985—),女,高级工程师,研究方向为智能驾驶,E-mail:wangxueying2007@163.com。

The Vehicle Micro Dynamic Rolling Trajectory Planning under Multi-condition Constraints

WANG Xueying1, YUAN Shengyue1 , ZHANG Yifang1 , MA Shifeng2   

  1. 1.Beijing New Electric Vehicle Company Limited by Shares; 2.Kh Automotive Technologies (Changchun) Company Limited
  • Online:2022-05-15 Published:2022-05-15
  • Contact: WANG Xueying

摘要: 针对高度复杂未知运动环境下最优车辆轨迹的生成问题,在考虑道路形状、路面附着 系数、道路宽度、障碍物及车辆外型尺寸、驾驶风格等因素的基础上,文章提出一种基于多 条件约束的汽车微观动态滚动轨迹规划方法。以距离最短为优化目标,对基于多项式的曲线, 进行躲避障碍物和免于碰撞道路边界的轨迹规划;以预瞄距离、最大侧向加速度限制值定义 不同风格驾驶员作为寻优约束,分析不同驾驶员对行驶轨迹的决策。考虑到真实驾驶员的规 划习惯,根据车辆当前位置及预瞄区间,更新规划范围,滚动寻优,确定轨迹。文章最后利 用 Simulink 仿真平台进行仿真实验,验证了该方法的有效性。

关键词: 车辆工程;动态轨迹规划;汽车智能化;车辆动力学

Abstract: Aiming at the problem of generating optimal vehicle trajectory in highly complicated unknown motion environment, a microdynamic rolling trajectory planning method based on multicondition constraints was proposed on the basis of considering road shape, road adhesion coefficient, road width, obstacles, vehicle size and driving style, etc in this paper. Aiming at the shortest distance, the path planning of obstacle avoidance and collision avoidance was carried out for the curve based on polynomial. Drivers with different driving styles were defined by the preview distance and the maximum lateral acceleration as optimization constraints, and the driving trajectory decisions of different drivers were analyzed.Considering the planning habits of real drivers, the planning range is updated according to the current position of the vehicle and the pre-view range, and the trajectory is determined by rolling optimization. Finally, simulation experiments are carried out using Simulink simulation platform to verify the effectiveness of the proposed method in this paper.

Key words: Vehicle engineering; Dynamic trajectory planning; Vehicle intelligence; Vehicle dynamics