Current status of path tracking control of unmanned driving vehicles

BAI Guo-xing; MENG Yu; LIU Li; GU Qing; WANG Guo-dong; ZHOU Bi-ning

doi:10.13374/j.issn2095-9389.2020.11.12.003

Volume 43 Issue 4

Mar. 2021

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Article Navigation > Chinese Journal of Engineering > 2021 > 43(4): 475-485

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

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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

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Current status of path tracking control of unmanned driving vehicles

doi: 10.13374/j.issn2095-9389.2020.11.12.003

BAI Guo-xing¹,
MENG Yu^{1
,
,},
LIU Li¹,
GU Qing^{1, 2},
WANG Guo-dong¹,
ZHOU Bi-ning¹

1.
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
2.
Shunde Graduate School of University of Science and Technology Beijing, Shunde 528300, China

More Information

Corresponding author: E-mail: myu@ustb.edu.cn
Received Date: 2020-11-12
Publish Date: 2021-04-26

Abstract

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.
- unmanned driving,
- vehicle,
- path tracking,
- system constraint,
- tracking accuracy,
- driving stability

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References(81)

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