Robust vehicle driver assistance control for handover scenarios considering driving performances

Yimin Chen, Xinjie Zhang, Junmin Wang

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Handover scenarios referred as the transitions between a human driver and an automated driving system are challenging because some human drivers are not adapted to the vehicle steering characteristics in a handover process and thus may exhibit deteriorative driving performances. This paper proposes a robust controller to assist human drivers in the handover scenarios. A driver-vehicle model including the driver steering input is developed to enhance the cooperation between a human driver and an automated driving controller. The driver parametric uncertainties are explicitly modeled to consider different human driving performances. Then a robust controller is designed to assist the driver considering his/her steering input and parametric uncertainties. The effectiveness of the designed controller is validated through several driver-in-the-loop tests on a driving simulator. The handover test results show that the driver steering loads and the vehicle lateral deviations can be reduced by the designed controller, thereby improving the driving safety in the handover processes.

Original languageEnglish
Article number8798999
Pages (from-to)4160-4170
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number7
DOIs
StatePublished - Jul 2021
Externally publishedYes

Keywords

  • Automated driving
  • driver assistance controller
  • driver parametric uncertainty
  • Hrobust control
  • handover scenarios

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