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Optimal Control of Intelligent Vehicle Path Tracking

Wang, Enhao; Liu, Yingjie; Xie, Chenglian

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Authors

Profile image of Enhao Wang

Enhao Wang enhao.wang@durham.ac.uk
PGR Student Doctor of Philosophy

Yingjie Liu

Chenglian Xie



Abstract

Path tracking control is a core technology of intelligent vehicles, and the accuracy of tracking performance is a key element of this technology. In order to address the issue of low accuracy in traditional methods for solving intelligent vehicle path tracking problems, a fast and high-precision solution method was design. This method discretized the continuous optimal control problem at collocation points and approximated the state and control variables through global interpolation polynomials, thereby transforming the optimal control problem of intelligent vehicle path tracking into a nonlinear programming NLP problem for solution. Finally, the real vehicle test verified the effectiveness of the method. The simulation results and comparison with traditional methods show that this method can solve the intelligent vehicle path tracking problem with high accuracy and has good engineering application potential.

Citation

Wang, E., Liu, Y., & Xie, C. (2025). Optimal Control of Intelligent Vehicle Path Tracking. IEEE Access, 13, 60148-60157. https://doi.org/10.1109/ACCESS.2025.3557215

Journal Article Type Article
Acceptance Date Mar 31, 2025
Online Publication Date Apr 2, 2025
Publication Date Apr 2, 2025
Deposit Date May 29, 2025
Publicly Available Date May 29, 2025
Journal IEEE Access
Electronic ISSN 2169-3536
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 13
Pages 60148-60157
DOI https://doi.org/10.1109/ACCESS.2025.3557215
Public URL https://durham-repository.worktribe.com/output/3967141

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