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author:

Lin, X. (Lin, X..) [1] | Wang, T. (Wang, T..) [2] | Zeng, S. (Zeng, S..) [3] | Chen, Z. (Chen, Z..) [4] | Xie, L. (Xie, L..) [5]

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Scopus

Abstract:

Automatic lane-changing is a complex and common task for autonomous vehicle control. In this study, a hierarchical decoupled path and velocity planning model for lane changing is proposed to enhance driving safety, comfort, and traffic efficiency. First, a parametric trajectory model is established based on the vehicle kinematic model, and the initial trajectory is solved quickly by the Sequential Quadratic Programming algorithm; in addition, the path optimization function is designed to optimize the trajectory curvature, and the distance-based velocity optimization method is used to improve the trajectory transverse, longitudinal acceleration, and jerk. To ensure the accuracy of path tracking, a comprehensive online trajectory optimization function is proposed according to tracking error fitting and vehicle reachability domain. The validation results demonstrate that the optimized path transverse velocity, acceleration, and jerk change curve are smoother, which meets the safety and comfort requirements of trajectory planning. Finally, the feasibility of the proposed trajectory planning is verified in a prototype vehicle real-world test. © 2024 IEEE.

Keyword:

Autonomous vehicles lane change online trajectory planning path re-optimization speed re-optimization

Community:

  • [ 1 ] [Lin X.]Fuzhou University, College of Mechanical Engineering and Automation, Fuzhou, 350108, China
  • [ 2 ] [Wang T.]Fuzhou University, College of Mechanical Engineering and Automation, Fuzhou, 350108, China
  • [ 3 ] [Zeng S.]Fuzhou University, College of Mechanical Engineering and Automation, Fuzhou, 350108, China
  • [ 4 ] [Chen Z.]Fuzhou University, College of Mechanical Engineering and Automation, Fuzhou, 350108, China
  • [ 5 ] [Xie L.]Fuzhou University, College of Mechanical Engineering and Automation, Fuzhou, 350108, China

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Source :

IEEE Transactions on Intelligent Transportation Systems

ISSN: 1524-9050

Year: 2024

Issue: 12

Volume: 25

Page: 20741-20752

7 . 9 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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