| 引用本文: | 马庆禄,李美强,黄光浩,高勇.智能网联汽车超车路径规划方法[J].控制理论与应用,2024,41(10):1882~1898.[点击复制] |
| MA Qing-lu,LI Mei-qiang,HUANG Ghuang-hao,Gao Yong.Overtaking path planning method for intelligent connected vehicle[J].Control Theory and Technology,2024,41(10):1882~1898.[点击复制] |
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| 智能网联汽车超车路径规划方法 |
| Overtaking path planning method for intelligent connected vehicle |
| 摘要点击 2296 全文点击 58 投稿时间：2022-09-02 修订日期：2024-07-15 |
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| DOI编号 10.7641/CTA.2023.20778 |
| 2024,41(10):1882-1898 |
| 中文关键词 自动驾驶 超车路径规划 人工势场法 联合仿真 |
| 英文关键词 automatic drive overtaking path planning artificial potential field method joint simulation |
| 基金项目 国家社会科学基金项目(20VYJ023), 宁夏回族自治区交通运输厅科技项目(NJGF20200301)资助. |
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| 中文摘要 |
| 针对自动驾驶车辆超车路径规划的问题, 本文提出改进的人工势场法并引入相对速度构建新的引力势场和斥力势场. 建立道路边界势场规范行车区域, 对障碍物的影响距离进行分段解决局部极值问题, 将自动驾驶车辆动力学相关约束融入人工势场法建立超车路径行驶势场模型. 选取重庆市内环快速路为试验路网原型, 利用无人机以及定点摄像等数据采集方法进行实地调查, 并采用MATLAB/Simulink, CarSim和PreScan进行联合仿真分析. 实验结果表明: 相比传统的人工势场法, 在前车静止、前车匀速、前车减速这3种条件下的超车路径曲率分别降低了85.07%, 62.69%和83.86%, 横向加速度均小于0.13m/s2, 改进后的路径规划算法可成功实现平稳超车, 驾乘人员的舒适性上有显著提升. |
| 英文摘要 |
| Aiming at the problem of overtaking path planning of autonomous vehicles, an improved artificial potential field method is proposed, and a new gravitational potential field and a repulsive potential field are constructed by introducing relative speed. A road boundary potential field is established to regulate the driving area. The influence distance of obstacles is segmented to solve the local extreme value problem. The vehicle dynamics-related constraints are integrated into the artificial potential field method to establish the overtaking path driving potential field model. The inner ring expressway in Chongqing is selected as the prototype of the test road network. Data collection methods such as unmanned aerial vehicles and fixed-point cameras are used for field investigation, and use the MATLAB/Simulink, the CarSim, and the PreScan for joint simulation analysis. The experimental results show that compared with the traditional artificial potential field method, the curvature of the overtaking path is reduced by 85.07%, 62.69% and 83.86%, respectively, under the conditions that the preceding vehicle is stationary, the preceding vehicle is at a uniform speed, and the preceding vehicle is decelerating. The lateral acceleration is less than 0.13 m/s2. The improved path planning algorithm can successfully achieve smooth overtaking, and the comfort of drivers and passengers is significantly improved. |
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