白国星, 孟宇, 刘立, 顾青, 王国栋, 周碧宁. 无人驾驶车辆路径跟踪控制研究现状[J]. 工程科学学报, 2021, 43(4): 475-485. DOI: 10.13374/j.issn2095-9389.2020.11.12.003
引用本文: 白国星, 孟宇, 刘立, 顾青, 王国栋, 周碧宁. 无人驾驶车辆路径跟踪控制研究现状[J]. 工程科学学报, 2021, 43(4): 475-485. DOI: 10.13374/j.issn2095-9389.2020.11.12.003
BAI Guo-xing, MENG Yu, LIU Li, GU Qing, WANG Guo-dong, ZHOU Bi-ning. Current status of path tracking control of unmanned driving vehicles[J]. Chinese Journal of Engineering, 2021, 43(4): 475-485. DOI: 10.13374/j.issn2095-9389.2020.11.12.003
Citation: BAI Guo-xing, MENG Yu, LIU Li, GU Qing, WANG Guo-dong, ZHOU Bi-ning. Current status of path tracking control of unmanned driving vehicles[J]. Chinese Journal of Engineering, 2021, 43(4): 475-485. DOI: 10.13374/j.issn2095-9389.2020.11.12.003

无人驾驶车辆路径跟踪控制研究现状

Current status of path tracking control of unmanned driving vehicles

  • 摘要: 近年来路径跟踪控制的发展十分迅猛,研究者们发表了大量的研究成果。考虑到在相同或相近工况下的路径跟踪控制存在一些共性的技术问题与解决思路,从低速路径跟踪控制和高速路径跟踪控制两个角度对近年来的研究成果进行了回顾。在关于低速路径跟踪控制的研究工作中,研究者们较为重视前轮转角速度约束等系统约束对路径跟踪精确性的影响。目前减少系统约束影响的方法包括在规划参考路径时将系统约束纳入考虑,采用预瞄控制使控制器提前响应,以及采用线性模型预测控制(LMPC)或非线性模型预测控制(NMPC)等模型预测控制方法作为路径跟踪控制方法等。考虑到NMPC既能减少系统约束的影响,又无需人为设置预瞄距离,且对定位误差等扰动因素具有较强的鲁棒性,加之低速路径跟踪控制对实时性的需求较低,因此可以认为NMPC能够满足低速路径跟踪控制的绝大多数需求。高速路径跟踪控制在受系统约束影响之外,还面临着较高车速带来的行驶稳定性不足问题的挑战,因此常采用能够将动力学层面的复杂系统约束纳入考虑且计算成本较低的LMPC作为路径跟踪控制方法。不过仅采用动力学层面的LMPC控制方法无法完全解决高速路径跟踪控制中路径跟踪精确性和车辆行驶稳定性之间存在耦合的问题,目前常见的解决思路是在路径跟踪控制中加入额外的速度调节或权重分配模块。此外,在高速路径跟踪控制中,地面附着系数等环境参数的影响也较大,因此地面附着系数等环境参数的估算也成为了高速路径跟踪控制领域的重要研究方向。

     

    Abstract: Path tracking control is a key technology in the hierarchical unmanned driving system. Its function is to control the vehicle so that it drives along the reference path given by the path planning system. The information such as the position and posture of the vehicle required for path tracking control is provided by the perception and positioning system. In recent years, the development of path tracking control has been very rapid, and researchers have published considerable research. As there are some common technical problems and solutions in path tracking control under the same or similar scenarios, recent research results are reviewed from the perspective of both low-speed and high-speed path tracking control. In the research of low-speed path tracking control, researchers pay more attention to the influence of system constraints on the accuracy of path tracking such as front-wheel angle speed. At present, methods to reduce the influence of system constraints include: (1) taking the system constraints into consideration when planning a reference path; (2) using preview control to make the controller respond early; and (3) using model predictive control methods, such as linear model predictive control (LMPC) or non-linear model predictive control (NMPC), as path tracking control methods. NMPC can reduce the impact of system constraints and does not need manual setting of preview distance. It has strong resistance to disturbance factors such as positioning errors. Since low-speed path tracking control has low real-time requirements, it can be considered that NMPC can meet most needs of low-speed path tracking control. High-speed path tracking control, in addition to being affected by system constraints, is also challenged by insufficient driving stability caused by higher vehicle speeds. Therefore, LMPC, which can take the dynamics-level complex system constraints into account, has a lower computational cost. It is often used as the path tracking control method. However, due to high-speed path tracking control, there is a coupling relationship between path tracking accuracy and vehicle driving stability. The use of dynamics-level LMPC or other dynamics-level control methods cannot completely solve the problem caused by this coupling relationship. The current common solution is to add an extra speed adjustment module or weight distribution module to path tracking control. Additionally, in high-speed path tracking control, the influence of environmental parameters, such as ground adhesion coefficient, is also greater. Hence, the estimation of environmental parameters, such as ground adhesion coefficient, has also become an important research direction in the field of high-speed path tracking control.

     

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