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Cited by 211Vehicle Dynamics and Control SystemsControl and Dynamics of Mobile RobotsAutonomous Vehicle Technology and Safety

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Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

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Yao, Qiangqiang, Tian, Ying, Wang, Qun, Wang, Shengyuan·2020·IEEE Access
DOI 10.1109/access.2020.3020075
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Abstract

Autonomous vehicle technology aims to improve driving safety, driving comfort, and its economy, as well as reduce traffic accident rate. As the basic part of autonomous vehicle motion control module, path tracking aims to follow the reference path accurately, ensure vehicle stability and satisfy the robust performance of the control system. This article introduces the representative control strategies, robust control strategies and parameter observation-based control strategies on path tracking for autonomous vehicle. Furthermore, the implementations and disadvantages are summarized. Most importantly, the critical review in this article provides a list and discussion of the remaining challenges and unsolved problems on path tracking control.

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  • Yao et al. employed robust control strategies, integrating sliding mode control (SMC), H-Control, and robust model predictive control (MPC), to address vehicle parameter uncertainties and external disturbances.

    “To address vehicle parameter uncertainties and external disturbances, Yao et al. [37] employed robust control strategies, integrating sliding mode control (SMC), H-Control, and robust model predictive control (MPC).”

    From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [37]

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References 125 · Cited by 211

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Metadata

Authors
Yao, Q., Tian, Y., Wang, Q., & Wang, S.
Affiliations
Beijing Jiaotong University (CN)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020
Volume
8
Pages
161211-161222
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2020.3020075
OpenAlex
W3081870136
Cited by
211
References
125
Citations by year
2026: 35 · 2025: 45 · 2024: 50 · 2023: 41 · 2022: 26 · 2021: 13 · 2020: 1
FWCI
7.49
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Foundation of Key Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology, Ministry of Education, Beijing Jiaotong University, China (014062522006)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Control and Dynamics of Mobile Robots
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
Keywords
autonomous vehicles, trajectory tracking, vehicle motion control, robust control, vehicle stability, control strategy comparison

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