基于动态稳定边界的智能车辆路径跟踪控制方法

doi:10.3901/JME.260449

机械工程学报 ›› 2026, Vol. 62 ›› Issue (8): 462-474.doi: 10.3901/JME.260449

• 特邀专辑：汽车线控底盘 • 上一篇下一篇

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基于动态稳定边界的智能车辆路径跟踪控制方法

张钰^1,2, 王成烨¹, 杜甫^1,2, 董明明¹, 秦也辰¹, 毛明^1,2

1. 北京理工大学机械与车辆学院北京 100081;
2. 中国北方车辆研究所槐树岭实验室北京 100072

收稿日期:2025-01-07 修回日期:2025-08-05 出版日期:2026-04-20 发布日期:2026-06-12
作者简介:张钰,男,1994年出生,博士。主要研究方向为智能车辆动力学控制。E-mail:zhyss_bit@bit.edu.cn;秦也辰(通信作者),男,1988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控制。E-mail:qinyechen@bit.edu.cn
基金资助:
国家自然科学基金(52502495,52272386,52522218);中国博士后科学基金(2024M764122,2024T171128);国家资助博士后研究人员计划(GZC20233402)资助项目。

Dynamic Region of Stability Integrated Path-tracking Control for Intelligent Vehicles

ZHANG Yu^1,2, WANG Chengye¹, DU Fu^1,2, DONG Mingming¹, QIN Yechen¹, MAO Ming^1,2

1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081;
2. Chinese Scholartree Ridge Laboratory, China North Vehicle Research Institute, Beijing 100072

Received:2025-01-07 Revised:2025-08-05 Online:2026-04-20 Published:2026-06-12

摘要/Abstract

摘要： 智能车辆路径跟踪控制是保障车辆行车安全与行驶稳定性的关键与核心。时变车速、路面条件影响车辆状态，现有路径跟踪控制方法结合较为保守的稳定性条件触发制动，维持路径跟踪过程中的车辆横向稳定性，存在着极限工况下路径跟踪性能恶化的问题。针对以上问题，结合椭圆几何模型表征车辆系统动态稳定域，构建了椭圆参数与行驶条件间的映射模型，实现车辆系统动态稳定域的显式表征，进而利用仿射变换设计优化问题所需的约束条件，提出基于动态稳定边界的智能车辆路径跟踪控制方法。基于硬件在环平台对所提方法进行了验证，结果显示，所提方法在保障行驶稳定性前提下，减少了车辆在高速、低附着条件下由于制动介入引起的车辆状态波动，并提升车辆路径跟踪精度达25.5%以上，同时满足实时性要求。

关键词: 显式稳定域, 稳定性约束, 稳定裕度, 路径跟踪控制, 智能车辆

Abstract: Intelligent vehicle path tracking control is crucial for ensuring driving safety and stability. Variable speed and road conditions affect the vehicle's states, and current path tracking methods, which trigger braking based on conservative stability conditions, aim to maintain lateral stability during path tracking. However, these methods tend to degrade path tracking performance under extreme conditions. To address this issue, an elliptical geometric model was applied to represent the dynamic stability region of the vehicle system, and a mapping model between elliptical parameters and driving conditions was established, which allowed for an explicit representation of the dynamic stability region of the vehicle system. Using affine transformations, the constraints for the optimization problem were designed, resulting in a dynamic region of stability integrated path-tracking control method. Verification on a hardware-in-the-loop platform showed that the proposed method reduces vehicle states' fluctuations caused by braking interventions under high-speed, low-friction conditions, while improving path tracking accuracy by more than 25.5%, and meeting real-time requirements.

Key words: explicit stability region, stability constraints, stability margin, path-tracking control, intelligent vehicle

中图分类号:

U461

张钰, 王成烨, 杜甫, 董明明, 秦也辰, 毛明. 基于动态稳定边界的智能车辆路径跟踪控制方法[J]. 机械工程学报, 2026, 62(8): 462-474.

ZHANG Yu, WANG Chengye, DU Fu, DONG Mingming, QIN Yechen, MAO Ming. Dynamic Region of Stability Integrated Path-tracking Control for Intelligent Vehicles[J]. Journal of Mechanical Engineering, 2026, 62(8): 462-474.

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参考文献

[1] 陈虹,郭露露,宫洵,等.智能时代的汽车控制[J].自动化学报,2020,46(7):1313-1332.CHEN Hong,GUO Lulu,GONG Xun,et al. Automotive control in intelligent era[J]. Acta Automatica Sinica,2020,46(7):1313-1332.
[2] 汪洪波,周俊涛,陈无畏,等.基于转向/横摆纳什博弈的智能车辆路径跟踪协调控制[J].机械工程学报,2024,60(10):439-452.WANG Hongbo,ZHOU Juntao,CHEN Wuwei,et al.Intelligent vehicle path tracking coordinated control based on steering/yaw nash game[J]. Journal of Mechanical Engineering,2024,60(10):439-452.
[3] KREMER M A. The electronic stability program(ESP)on the ford focus[C] //Proceedings of the European Conference on Vehicle Electronic Systems. Stratfordupon-Avon,UK:Vehicle electronic systems,2000.
[4] WANG Fanxun,SHEN Tong,ZHAO Mingzhuo,et al.Lane-change trajectory planning and control based on stability region for distributed drive electric vehicle[J].IEEE Transactions on Vehicular Technology,2024,73(1):504-521.
[5] LIU Jun, DAI Ang. Distributed-drive vehicle lateral-stability coordinated control based on phase-plane stability region[J]. World Electric Vehicle Journal,2024,15(5):202.
[6] FARRONI F, RUSSO M, RUSSO R, et al. A combined use of phase plane and handling diagram method to study the influence of tyre and vehicle characteristics on stability[J]. Vehicle System Dynamics,2013,51(8):1265-1285.
[7] IMANI M M,LIMEBEER D J. Region of attraction analysis for nonlinear vehicle lateral dynamics using sum-of-squares programming[J]. Vehicle System Dynamics,2018,56(7):1118-1138.
[8] HU Xiao,CHEN Hong,REN Qiao,et al. Estimation and expansion of vehicle stability region with sums of squares programming[J]. IEEE/ASME Transactions on Mechatronics,2023,28(5):2820-2831.
[9] FARAG W. Complex trajectory tracking using PID control for autonomous driving[J]. International Journal of Intelligent Transportation Systems Research, 2020,18(2):356-366.
[10] SABIHA A D, KAMEL M A, SAID E, et al.ROS-based trajectory tracking control for autonomous tracked vehicle using optimized backstepping and sliding mode control[J]. Robotics Autonomous Systems,2022,152:104058.
[11] HU Chuan, CHEN Yimin, WANG Junmin. Fuzzy observer-based transitional path-tracking control for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems,2020,22(5):3078-3088.
[12] AHN J,SHIN S,KIM M,et al. Accurate path tracking by adjusting look-ahead point in pure pursuit method[J].International Journal of Automotive Technology,2021,22:119-129.
[13] LIU Yiping,PEI Xiaofei,ZHOU Honglong,et al.Spatiotemporal trajectory planning for autonomous vehicle based on reachable set and iterative LQR[J]. IEEE Transactions on Vehicular Technology,2024,73(8):10932-10947.
[14] CHENG Shuo, LI Liang, CHEN Xiang, et al.Model-predictive-control-based path tracking controller of autonomous vehicle considering parametric uncertainties and velocity-varying[J]. IEEE Transactions on Industrial Electronics,2020,68(9):8698-8707.
[15] SUN Xiaoqiang,WANG Yulin,CAI Yingfeng,et al.Nonsingular terminal sliding mode-based direct yaw moment control for four-wheel independently actuated autonomous vehicles[J]. IEEE Transactions on Transportation Electrification,2022,9(2):2568-2582.
[16] ZHANG Yu,LIN Yutian,QIN Yechen,et al. A new adaptive cruise control considering crash avoidance for intelligent vehicle[J]. IEEE Transactions on Industrial Electronics,2024,71(1):688-696.
[17] XIA Xin, HASHEMI E, XIONG Lu, et al.Autonomous vehicle kinematics and dynamics synthesis for sideslip angle estimation based on consensus Kalman filter[J]. IEEE Transactions on Control Systems Technology,2022,31(1):179-192.
[18] TIAN Yang,MA He,MA Lei,et al. Path tracking control of commercial vehicle emergency obstacle avoidance based on mpc and active disturbance rejection control[J]. IEEE Transactions on Transportation Electrification,2025,11(3):7162-7170.
[19] VIADERO-MONASTERIO F, NGUYEN A T,LAUBER J,et al. Event-triggered robust path tracking control considering roll stability under network-induced delays for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12):14743-14756.
[20] ZHU Zhewei,TANG Xiaolin,QIN Yechen,et al. A survey of lateral stability criterion and control application for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(10):10382-10399.
[21] HASHEMI E,JALALI M,KHAJEPOUR A,et al.Vehicle stability control:Model predictive approach and combined-slip effect[J]. IEEE/ASME Transactions on Mechatronics,2020,25(6):2789-2800.
[22] HASHEMI E,PIRANI M,KHAJEPOUR A,et al.Corner-based estimation of tire forces and vehicle velocities robust to road conditions[J]. Control Engineering Practice,2017,61:28-40.
[23] ZANELLI A, DOMAHIDI A, JEREZ J, et al.FORCES NLP:An efficient implementation of interior-point methods for multistage nonlinear nonconvex programs[J]. International Journal of Control,2020,93(1):13-29.
[24] ZHANG Yu, XU Mingfan, QIN Yechen, et al.MILE:Multiobjective integrated model predictive adaptive cruise control for intelligent vehicle[J]. IEEE Transactions on Industrial Electronics,2023,19(7):8539-8548.
[25] ZHANG Yu,HU Yuxuan,HU Xuepeng,et al. Adaptive crash-avoidance predictive control under multi-vehicle dynamic environment for intelligent vehicles[J/OL]. IEEE Transactions on Intelligent Vehicles,2024[2025-01-05].https://doi:10.1109/TIV. 2024.3394845.
[26] 张钰,徐明帆,白光宇,等.考虑稳定性约束的智能车辆切换控制方法[J].汽车工程,2023,45(5):709-718.ZHANG Yu, XU Mingfan, BAI Guangyu, et al.Intelligent vehicle switching control considering dynamic stability constraints[J]. Automotive Engineering,2023,45(5):709-718.

基于动态稳定边界的智能车辆路径跟踪控制方法

Dynamic Region of Stability Integrated Path-tracking Control for Intelligent Vehicles

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