Dynamic Drifting Control for General Path Tracking of Autonomous Vehicles

  • Guoying Chen
  • , Xuanming Zhao
  • , Zhenhai Gao*
  • , Min Hua
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Taking full advantage of tire saturation in high sideslip drifting maneuvers can substantially improve the handling limits of autonomous vehicles. However, most singular motion control methods in conventional drifting controllers have been conducted, which cannot meet general driving needs. In this article, a hierarchical dynamic drifting controller (HDDC) is designed under both drifting maneuvers and typical cornering maneuvers to uniformly track the general path within and beyond stability limits. Specifically, the HDDC includes the path tracking layer, vehicle motion control layer, and actuator regulating layer. The first layer is designed to achieve accurate path tracking and generate the desired states, and it is algorithmically adaptable and confirmed by MPC and LQR. The second layer is proposed to integrate drifting and typical cornering control by the dynamic drifting inverse model. The third layer can achieve the steering system and wheel speed control to satisfy corresponding commands. Ultimately, the real-time performance of the controller is verified by the ECU hardware-in-the-loop platform. The results with MPC-HDDC and LQR-HDDC show that the HDDC can achieve integrated control of drifting and typical cornering maneuvers and possess high tracking accuracy.

Original languageEnglish
Pages (from-to)2527-2537
Number of pages11
JournalIEEE Transactions on Intelligent Vehicles
Volume8
Issue number3
Early online date9 Jan 2023
DOIs
Publication statusPublished - 27 Apr 2023

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Autonomous vehicles
  • dynamic drifting control
  • path tracking
  • stability limits

ASJC Scopus subject areas

  • Automotive Engineering
  • Control and Optimization
  • Artificial Intelligence

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