A data-based lane-keeping steering control for autonomous vehicles: A Human-in-the-loop approach

Mengzhe Huang, Weinan Gao, Zhong Ping Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study the design of a lane-keeping control assistance system, by taking the interaction between the driver and the vehicle into account. A Human-in-the-loop controller design approach is proposed to assist the driver to maintain in the central position of a lane. A sampled-data adaptive dynamic programming (ADP) method is introduced to develop online adaptive optimal controllers to achieve zero steady-state lane-keeping error while the road curvature condition and the vehicle dynamics are unknown. The effectiveness of this steering control assistance system is supported by rigorous analysis and validated by simulation results. Furthermore, as opposed to previous Human-in-the-loop controllers, the proposed controller is capable of adapting to different road curvature conditions.

Original languageEnglish (US)
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages8974-8979
Number of pages6
ISBN (Electronic)9789881563910
DOIs
StatePublished - Aug 26 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: Jul 27 2016Jul 29 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Other

Other35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period7/27/167/29/16

Keywords

  • Adaptive dynamic programming (ADP)
  • Human in the loop
  • Lane keeping
  • Vehicle control

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modeling and Simulation

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