Stability Control of Autonomous Ground Vehicles Using Control-Dependent Barrier Functions

Yiwen Huang, Sze Zheng Yong, Yan Chen

Research output: Contribution to journalArticlepeer-review

Abstract

In the development of autonomous ground vehicles (AGVs), guaranteeing vehicle driving safety is a major concern. Among various aspects that need to be thoughtfully considered for driving safety, vehicle stability is one of the most fundamental and important factors. In this paper, to describe a guaranteed vehicle stability control problem, a new time-varying control-dependent invariant set is introduced. Correspondingly, the concept of a time-varying control-dependent barrier function (CDBF) is proposed. The proposed time-varying CDBF is more general than conventional control barrier functions (CBF), since we additionally consider invariant sets that can be time-varying and control-dependent, which will have broader applications. Then, using the proposed framework, we design a vehicle stability control algorithm, which guarantees that the vehicle states are always kept in the time-varying and control-dependent lateral stability regions. Finally, the correctness and effectiveness of the proposed theory and control method are verified and discussed through illustrative simulation results of high-speed J-turn and double lane change maneuvers for an AGV.

Original languageEnglish (US)
JournalIEEE Transactions on Intelligent Vehicles
DOIs
StateAccepted/In press - 2021

Keywords

  • Autonomous vehicles
  • Control-dependent barrier functions
  • Land vehicles
  • Safety
  • Stability criteria
  • Time-varying systems
  • Vehicle dynamics
  • Wheels
  • autonomous ground vehicles
  • four-wheel steering
  • safety control
  • vehicle stability control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Automotive Engineering
  • Control and Optimization

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