基于多目标优化的高速超车轨迹规划

doi:10.3969/j.issn.1674-0696.2024.04.10

重庆交通大学学报（自然科学版） ›› 2024, Vol. 43 ›› Issue (4): 67-73.DOI: 10.3969/j.issn.1674-0696.2024.04.10

• 交通+大数据人工智能 • 上一篇

基于多目标优化的高速超车轨迹规划

刘刚1 ，张泽1，范群1 ，任宏斌2，杨旭3

（1.沈阳航空航天大学机电工程学院，辽宁沈阳 110136；2.北京理工大学机械与车辆学院，北京 100081; 3.辽宁陆平机器股份有限公司,辽宁铁岭 112001）

收稿日期:2023-03-30 修回日期:2023-12-13 发布日期:2024-04-22
作者简介:刘刚(1975—)，男，满族，辽宁昌图人，讲师，博士，主要从事车辆悬架系统理论与控制、智能车辆控制方面的研究。E-mail：liugang_209209@163.com
基金资助:
国家自然科学基金项目(52002025)；辽宁省教育厅项目（LJKZ0203）

High-Speed Overtaking Trajectory Planning Based on Multi-objective Optimization

LIU Gang1，ZHANG Ze1，FAN Qun1，REN Hongbin2，YANG Xu3

（1. School of Mechatronics Engineering, Shenyang Aerospace University， Shenyang 110136， Liaoning， China； 2. School of Mechanical Engineering, Beijing Institute of Technology， Beijing 100081， China； 3. Liaoning Luping Machinery Co.，Ltd.，Tieling 112001， Liaoning， China）

Received:2023-03-30 Revised:2023-12-13 Published:2024-04-22

摘要/Abstract

摘要： 为保障高速超车规划过程中的安全，同时提升轨迹的舒适性，笔者提出一种基于多目标的高速超车轨迹规划算法。该算法在可行凸空间的基础上求解出高速超车边界条件，再通过安全超车策略对超车行为的可行性进行分析，随后根据建立的超车轨迹规划目标函数和舒适性优化函数对轨迹的平顺性和乘坐的舒适性等目标进行优化，并且算法实时规划轨迹直至超车行为完成。为验证该算法的有效性，利用Prescan和MATLAB/Simulink构建联合仿真平台，对所设计的两种常见超车场景进行验证分析。仿真结果表明：在匀速超车以及加速超车场景下，相较于单目标优化，经多目标优化的超车轨迹的横向位移峰值、横向加速度峰值、横摆角速度峰值、曲率峰值，以及车速峰值的优化效果都获得了提升，有效的提高了所规划超车轨迹的舒适性和安全性。

关键词: 交通运输工程；高速超车;自动驾驶;轨迹规划; 超车策略;多目标优化

Abstract: In order to ensure the safety during the high-speed overtaking planning process and improve the comfort of the trajectory, a multi-objective high-speed overtaking trajectory planning algorithm was proposed. In the proposed algorithm, the boundary conditions for high-speed overtaking were solved based on a feasible convex space, and the feasibility of overtaking behavior was analyzed through a safe overtaking strategy. Then the goals such as trajectory smoothness and ride comfort were optimized according to the established overtaking trajectory planning objective function and comfort optimization function. Moreover, the proposed algorithm planned the trajectory in real time until the overtaking behavior was completed. In order to verify the effectiveness of the proposed algorithm, a joint simulation platform was built by Prescan and Matlab/Simulink to validate and analyze the two designed common overtaking scenarios. The simulation results demonstrate that, in scenarios involving constant speed overtaking and acceleration overtaking, the optimization effects of lateral displacement peak, lateral acceleration peak, yaw velocity peak, curvature peak, and speed peak of the overtaking trajectory are significantly enhanced through multi-objective optimization compared to single objective optimization. The comfort and safety of the planned overtaking trajectory are effectively improved.

Key words: traffic and transportation engineering; high-speed overtaking; autonomous driving; trajectory planning; overtaking strategy; multi-objective optimization

中图分类号:

U463.6
TP18

刘刚1 ，张泽1，范群1 ，任宏斌2，杨旭3. 基于多目标优化的高速超车轨迹规划[J]. 重庆交通大学学报（自然科学版）, 2024, 43(4): 67-73.

LIU Gang1，ZHANG Ze1，FAN Qun1，REN Hongbin2，YANG Xu3. High-Speed Overtaking Trajectory Planning Based on Multi-objective Optimization[J]. Journal of Chongqing Jiaotong University(Natural Science), 2024, 43(4): 67-73.

参考文献

［1］ ZHANG Senlin, DENG Guohong, YANG Echuan, et al. Optimal vehicle lane change trajectory planning in multi-vehicle traffic environments［J］.Applied Sciences, 2022, 12(19): 9662.
［2］赵奉奎, 葛振, 董锋威, 等. 基于改进人工势场法的智能汽车轨迹规划算法研究［J］. 重庆交通大学学报(自然科学版), 2022, 41(11): 153-160.
ZHAO Fengkui, GE Zhen, DONG Fengwei,et al. Intelligent vehicle trajectory planning algorithm based on improved artificial potential field method ［J］. Journal of Chongqing Jiaotong University (Natural Science), 2022, 41(11): 153-160.
［3］牛国臣, 李文帅, 魏洪旭. 基于双五次多项式的智能汽车换道轨迹规划［J］. 汽车工程, 2021, 43(7): 978-986.
NIU Guochen, LI Wenshuai, WEI Hongxu. Intelligent vehicle lane changing trajectory planning based on double quintic polynomials［J］.Automotive Engineering, 2021, 43(7): 978-986.
［4］陈鹏宇, 孔令安, 彭忆强. 基于五阶Bezier曲线的无人车避障轨迹规划［J］. 科学技术与工程, 2022, 22(31): 13933-13941.
CHEN Pengyu, KONG Lingan, PENG Yiqiang. Obstacle avoidance path planning for unmanned vehicle based on fifth-order Bezier curve［J］. Science Technology and Engineering, 2022, 22(31): 13933-13941.
［5］郑亮, 孙龙龙, 陈双. 一种改进工业自动导引车路径规划算法［J］. 科学技术与工程, 2021, 21(16): 6758-6763.
ZHENG Liang, SUN Longlong, CHEN Shuang. An improved industrial automated guided vehicle path planning algorithm［J］.Science Technology and Engineering, 2021, 21(16): 6758-6763.
［6］荆学东, 陈亚楠. 基于改进A*算法的一种智能车路径规划方法［J］. 科学技术与工程, 2020, 20(27): 11161-11165.
JING Xuedong, CHEN Yanan. Intelligent vehicle trajectory planning based on improved genetic algorithm［J］.Science Technology and Engineering, 2020, 20(27): 11161-11165.
［7］ XU Wenda, WANG Qian, DOLAN J M. Autonomous vehicle motion planning via recurrent spline optimization ［C］// 2021 IEEE International Conference on Robotics and Automation (ICRA). Xian, China. IEEE, 2021: 7730-7736.
［8］陈治莹. 高速公路自动驾驶汽车超车控制方法研究［D］. 武汉: 武汉理工大学, 2019.
CHEN Zhiying.Research on the Overtaking Control Method for Autonomous Vehicle on Highway［D］. Wuhan: Wuhan University of Technology, 2019.
［9］曾超, 崔子豪. 基于改进Dijkstra算法的水平循环类立体车库存取车辆路径优化模型［J］. 重庆交通大学学报(自然科学版), 2023, 42(2):93-98.
ZENG Chao， CUI Zihao. Path optimization model in vehicle storage and retrieval system of horizontal circulating three-dimensional garage based on improved Dijkstra algorithm［J］. Journal of Chongqing Jiaotong University (Natural Science), 2023, 42(2): 93-98.
［10］马凯. 典型潜在危险驾驶情景研究［D］. 长春: 吉林大学, 2017.
MA Kai.Research on Typical Potential Dangerous Driving Scenarios［D］. Changchun: Jilin University, 2017.
［11］张志勇, 龙凯, 杜荣华, 等. 自动驾驶汽车高速超车轨迹跟踪协调控制［J］. 汽车工程, 2021, 43(7): 995-1004.
ZHANG Zhiyong, LONG Kai, DU Ronghua,et al. Trajectory tracking coordinated control for autonomous vehicle in high-speed overtaking［J］. Automotive Engineering, 2021, 43(7): 995-1004.
［12］王峥, 李欣格, 张天慈. 基于模型预测控制的无人驾驶车辆纵向跟车控制研究［J］. 智能计算机与应用, 2023, 13(4): 163-166.
WANG Zheng, LI Xinge, ZHANG Tianci. Research on longitudinal car-following control of unmanned vehicle based on model predictive control［J］.Intelligent Computer and Applications, 2023, 13(4): 163-166.
［13］ SRITHAR S, SARAVANAKUMAR D N M. Comfort and danger zone boundary prediction for flying car safe overtaking in highways［J］. International Journal of Recent Technology and Engineering (IJRTE), 2020, 8(5): 1155-1159.

[1]	安治国，豆旺，李亚坤，王善明. 改进型并联流道液冷开关磁阻电机散热研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(06): 136-142.
[2]	王俊明，周宏伟. 基于ISO26262的车道保持辅助的功能安全概念设计[J]. 重庆交通大学学报（自然科学版）, 2019, 38(03): 135-142.
[3]	侯小梅,刘建勋,李洋. 汽车前照灯随动转向控制系统边界条件研究[J]. 重庆交通大学学报（自然科学版）, 2009, 28(2): 298-301.
[4]	陈锋，丁养燕，黄建. 汽车电控系统故障监测与自诊断[J]. 重庆交通大学学报（自然科学版）, 2007, 26(6): 156-161.
[5]	刘小根,杨志刚,杜子学. 汽车转向器空载转矩测量的抗干扰措施[J]. 重庆交通大学学报（自然科学版）, 2004, 23(4): 103-106.

基于多目标优化的高速超车轨迹规划

High-Speed Overtaking Trajectory Planning Based on Multi-objective Optimization

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics