融合侧翻稳定性的SUV换道轨迹规划方法研究

doi:10.3901/JME.2023.04.145

机械工程学报 ›› 2023, Vol. 59 ›› Issue (4): 145-154.doi: 10.3901/JME.2023.04.145

扫码分享

融合侧翻稳定性的SUV换道轨迹规划方法研究

金智林, 何少炜, 黄舒伟

南京航空航天大学车辆工程系南京 210016

收稿日期:2022-05-03 修回日期:2022-09-24 出版日期:2023-02-20 发布日期:2023-04-24
通讯作者: 金智林(通信作者),男,1978年出生,副教授。主要研究方向为车辆动力学与控制。E-mail:jinzhilin@nuaa.edu.cn
作者简介:何少炜,男,1999年出生,硕士研究生。主要研究方向为车辆动力学与控制。E-mail:1045832078@qq.com;黄舒伟,男,1997年出生,硕士研究生。主要研究方向为车辆动力学与控制。E-mail:272422991@qq.com
基金资助:
国家自然科学基金(51775269)和江苏省自然科学基金(BK20211190)资助项目。

Research on SUV Lane Changing Trajectory Planning Method Integrating Rollover Stability

JIN Zhilin, HE Shaowei, HUANG Shuwei

Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016

Received:2022-05-03 Revised:2022-09-24 Online:2023-02-20 Published:2023-04-24

摘要/Abstract

摘要： 针对运动型多功能汽车(Sport utility vehicle，SUV)换道过程中侧翻安全问题，提出融合侧翻稳定性的SUV换道轨迹规划方法。建立三自由度车辆动力学模型，推导SUV侧翻稳定性及侧滑稳定性评价指标。采集自车状态及环境信息，将换道轨迹规划分成预规划和重规划两个阶段；预规划阶段采用五次多项式模型生成横向轨迹簇，重规划阶段考虑周围车辆动态变化，生成包含自车纵向速度信息的轨迹簇。融合侧翻稳定性指标、侧滑稳定性指标以及双圆拟合的车辆外形最小距离，构建代价函数；进行轨迹簇碰撞筛选、稳定性筛选及轨迹选择。运用内点惩罚函数进行轨迹优化，求解最优轨迹。选取两种典型工况进行换道轨迹规划仿真，结果表明SUV沿着该方法规划的轨迹行驶可完成换道躲避障碍物，且横向位移小、换道效率高，可有效避免侧翻危险。

关键词: 换道轨迹规划, 侧翻稳定性, 轨迹筛选, 轨迹优化

Abstract: Aiming at SUV rollover safety during lane changing, an SUV lane changing trajectory planning method integrating rollover stability is proposed. A three degrees of freedom vehicle dynamics model is established. Rollover and sideslip stability evaluation indexes of SUV are derived. According to the vehicle status and environmental information, the lane change trajectory planning is divided into two stages: pre-planning and re-planning. In the pre-planning stage, the quintic polynomial model is used to generate the lateral track cluster of lane change. And in the re-planning stage, the dynamic change information of surrounding vehicles is considered to generate the track cluster with longitudinal speed change. The cost function is constructed by combining rollover stability index, sideslip stability index, and the minimum distance of vehicles shape fitted by double circles. Then a trajectory is selected from the track cluster using the cost function. Furthermore, the interior penalty function is used to optimize the selected trajectory. Finally, SUV lane change trajectory planning method is simulated in two typical cases. The results show that, driving along the trajectory planned by the proposed method, SUV can complete lane change and avoid obstacles, with small lateral displacement，high efficiency, and high level rollover stability.

Key words: lane changing trajectory planning, rollover stability, trajectory select, trajectory optimization

中图分类号:

U461

金智林, 何少炜, 黄舒伟. 融合侧翻稳定性的SUV换道轨迹规划方法研究[J]. 机械工程学报, 2023, 59(4): 145-154.

JIN Zhilin, HE Shaowei, HUANG Shuwei. Research on SUV Lane Changing Trajectory Planning Method Integrating Rollover Stability[J]. Journal of Mechanical Engineering, 2023, 59(4): 145-154.

参考文献

[1] MONTANARO U,DIXIT S,FALLAH S,et al. Towards connected autonomous driving:Review of use-cases[J]. Vehicle System Dynamics,2019,57(6):779-814.
[2] GOLESTAN K,SOUA R,KARRAY F,et al. Situation awareness within the context of connected cars:A comprehensive review and recent trends[J]. Information Fusion,2016,29(1):68-83.
[3] 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.
[4] HU J,XIONG S,ZHA J,et al. Lane detection and trajectory tracking control of autonomous vehicle based on model predictive control[J]. International Journal of Automotive Technology,2020,21(2):285-295.
[5] National Highway Traffic Safety Administration. Traffic safety facts 2019:A compilation of motor vehicle crash data from the fatality analysis reporting system and the general estimates system[R]. Washington,DC:Department of Transportation,2021.
[6] PADEN B,CAP M,YONG S,et al. A survey of motion planning and control techniques for self-driving urban vehicles[J]. IEEE Transactions on Intelligent Vehicles,2016,1(1):33-55.
[7] 刘志强,王一凡,吴雪刚,等. 基于线性路径跟踪控制的换道避撞控制策略研究[J]. 中国公路学报,2019,32(6):86-95.
LIU Zhiqiang,WANG Yifan,WU Xuegang,et al. Collision avoidance by lane changing based on linear path-following control[J]. China Journal of Highway and Transport,2019,32(6):86-95.
[8] 周健. 多车交通环境中智能车辆换道轨迹规划与重规划方法研究[D]. 长春:吉林大学,2020.
ZHOU Jian. Investigation of lane-change trajectory planning and replanning methods for intelligent vehicles in multi-vehicle traffic environments[D]. Changchun:Jilin University,2020.
[9] SUH J,CHAE H,YI K. Stochastic model-predictive control for lane change decision of automated driving vehicles[J]. IEEE Transactions on Vehicular Technology,2018,67(6):4771-4782.
[10] SHILP D,UMBERTO M,MEHRDAD D,et al. Trajectory planning for autonomous high-speed overtaking in structured environments using Robust MPC[J]. IEEE Transactions on Intelligent Transportation Systems,2020,21(6):2310-2323.
[11] JIN Zhilin,LI Jingxuan,WANG Hong,et al. Rollover prevention and motion planning for an intelligent heavy truck[J]. Chinese Journal of Mechanical Engineering,2021,34(1):1-15.
[12] 张家旭,施正堂,赵健,等. 基于Radau伪谱法的汽车高速紧急换道避障最优控制策略设计[J]. 汽车工程,2020,42(8):1040-1049.
ZHANG Jiaxu,SHI Zhengtang,ZHAO Jian,et al. Optimal control strategy design for vehicle high-speed emergency lane change collision avoidance cased on Radau pseudospectral method[J]. Automotive Engineering,2020,42(8):1040-1049.
[13] WANG H,HUANG Y,KHAJEPOUR A,et al. Crash mitigation in motion planning for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems,2019,20(9):3313-3323.
[14] YANG I,KIM H,JEON W,et al. Development of realistic shortest path algorithm considering lane changes[J]. Journal of Advanced Transportation,2016,50(4):541-551.
[15] MADAS D,NOSRATINIA M,KESHAVARZ M,et al. On path planning methods for automotive collision avoidance[C]//2013 IEEE Intelligent Vehicles Symposium (IV). IEEE,2013:931-937.
[16] LAN X,DI C. Continuous curvature path planning for semi-autonomous vehicle maneuvers using RRT[C]//2015 European Control Conference (ECC). IEEE,2015:2360-2365.
[17] KARAMAN S,FRAZZOLI E. Sampling-based algorithms for optimal motion planning[J]. International Journal of Robotics Research,2011,30(7):846-894.
[18] KIUMARSI B,VAMVOUDAKIS K,MODARES H,et al. Optimal and Autonomous control using reinforcement learning:A survey[J]. IEEE Transactions on Neural Networks & Learning Systems,2018,29(6):2042-2062.
[19] NDIKUMANA A,TRAN N,KIM D,et al. Deep learning based caching for self-driving cars in multi-access edge computing[J]. IEEE Transactions on Intelligent Transportation Systems,2020,22(5):1-16.
[20] LEFEVRE S,CARVALHO A,BORRELLI F. A learning-based framework for velocity control in autonomous driving[J]. IEEE Transactions on Automation Science & Engineering,2016,13(1):32-42.
[21] TAKAHASHI A,HONGO T,NINOMIYA Y,et al. Local path planning and motion control for AGV in positioning[C]//IEEE/RSJ International Workshop on Intelligent Robots & Systems 89 the Autonomous Mobile Robots & Its Applications Iros. IEEE,2002.

融合侧翻稳定性的SUV换道轨迹规划方法研究

Research on SUV Lane Changing Trajectory Planning Method Integrating Rollover Stability

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

编辑推荐

Metrics

本文评价

[1]	秦涛, 李运华, 范茹军. 强力摇臂矿用液压挖掘机自主挖掘轨迹优化[J]. 机械工程学报, 2024, 60(18): 374-384.
[2]	夏光, 李嘉诚, 唐希雯, 张洋, 陈无畏. 基于侧倾能量分级的平衡重式叉车防侧翻控制研究[J]. 机械工程学报, 2023, 59(10): 275-289.
[3]	宋冬冬, 薛飞, 赵万华, 卢秉恒. 九轴联动叶片双刀对顶铣削的非线性误差分析与控制算法[J]. 机械工程学报, 2020, 56(3): 197-206.
[4]	陈子明, 卢杰, 邓朋, 郭玉, 李艳文. 一种稳定跳跃型机器人的设计与空中姿态控制[J]. 机械工程学报, 2020, 56(23): 34-44.
[5]	段书用, 王启帆, 韩旭, 刘桂荣. 具有确保安全距离的A*路径优化方法[J]. 机械工程学报, 2020, 56(18): 205-215.
[6]	金智林, 严正华, 赵万忠. 驾驶员影响汽车侧翻稳定性机理分析与控制[J]. 机械工程学报, 2019, 55(4): 109-117.
[7]	张志宇;李锐钢;郑立功;张学军. 离轴非球面SiC反射镜的精密铣磨加工技术[J]. , 2013, 49(17): 39-45.
[8]	邵君奕;张传清;刘召;陈恳. 考虑振动抑制的多冗余度特种操作机器人轨迹优化方法[J]. , 2012, 48(1): 13-18.