基于碰撞风险评估的智能汽车局部路径规划方法研究

doi:10.3901/JME.2021.10.028

机械工程学报 ›› 2021, Vol. 57 ›› Issue (10): 28-41.doi: 10.3901/JME.2021.10.028

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基于碰撞风险评估的智能汽车局部路径规划方法研究

王明强^1,2, 王震坡^1,2, 张雷^1,2

1. 北京理工大学电动车辆国家工程实验室北京 100081;
2. 北京理工大学北京电动车辆协同创新中心北京 100081

收稿日期:2020-07-13 修回日期:2020-12-21 出版日期:2021-07-23 发布日期:2021-07-23
通讯作者: 张雷(通信作者),男,1987年出生,博士,特别副研究员,硕士研究生导师。主要研究方向为车辆动力学理论与控制,电动车辆储能系统管理技术等。E-mail:lei_zhang@bit.edu.cn
作者简介:王明强,男,1993年出生,博士研究生。主要研究方向为智能驾驶汽车运动规划理论与控制。E-mail:373435986@qq.com;王震坡,男,1976年出生,博士,教授,博士研究生导师。主要研究方向为车辆动力学理论与控制,车用锂离子动力电池成组理论与技术。E-mail:wangzhenpo@bit.edu.cn
基金资助:
国家重点研发计划资助项目（2017YFB0103600）。

Local Path Planning for Intelligent Vehicles Based on Collision Risk Evaluation

WANG Mingqiang^1,2, WANG Zhenpo^1,2, ZHANG Lei^1,2

1. National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081;
2. Collaborative Innovation Center for Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081

Received:2020-07-13 Revised:2020-12-21 Online:2021-07-23 Published:2021-07-23

摘要/Abstract

摘要： 针对结构化道路环境下智能汽车的动态路径规划问题，提出了一种基于碰撞风险评估的局部路径规划算法。利用三次样条曲线参数化表达全局路径，获取道路基准线；综合考虑车辆行驶安全性、规划路径平滑性等性能指标生成候选路径，通过归一化加权代价函数评估生成的候选路径；在全局路径信息引导下，获得当前状态下的局部最优路径。针对性能代价函数，引入风险场的概念，建立了符合行车风险客观规律的静态与移动障碍物风险模型，并结合高斯卷积建立了安全性代价函数；考虑候选路径曲率变化及全局路径追踪能力，设计了路径平滑性及偏移代价函数。仿真结果表明，提出的局部路径规划算法能够实时生成平滑、无碰撞路径，且在多种道路场景中实现对静态和移动障碍物的有效规避，满足实时性的要求。

关键词: 智能汽车, 路径规划, 实时避障, 风险场, 代价函数

Abstract: A local path planning algorithm for intelligent vehicles under structured road environments is proposed based on collision risk evaluation. Firstly, the cubic spline curve is used to express the global path. Secondly, the candidate paths are generated considering vehicle safety and path smoothness, and the generated candidate paths are evaluated by the normalized cost function. Finally, the optimal local path is obtained at the current state under the guidance of global path information. For the cost function, the driving risk field is proposed, and a static and moving obstacle risk model is designed, where the safety cost function is established based on collision risk evaluation combined with the Gaussian convolution. Concerning with the curvature and path-following effect of the generated path, a path smoothness and an offset cost function are respectively built. The simulation results show that the proposed algorithm can generate smooth, collision-free paths in real-time, and the test intelligent vehicle can effectively avoid static and moving obstacles under various road scenarios.

Key words: intelligent vehicles, path planning, obstacle avoidance, driving risk field, cost function

中图分类号:

TG156

王明强, 王震坡, 张雷. 基于碰撞风险评估的智能汽车局部路径规划方法研究[J]. 机械工程学报, 2021, 57(10): 28-41.

WANG Mingqiang, WANG Zhenpo, ZHANG Lei. Local Path Planning for Intelligent Vehicles Based on Collision Risk Evaluation[J]. Journal of Mechanical Engineering, 2021, 57(10): 28-41.

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基于碰撞风险评估的智能汽车局部路径规划方法研究

Local Path Planning for Intelligent Vehicles Based on Collision Risk Evaluation

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