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Volume 43 Issue 3
Mar.  2021
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Article Contents
QIN Zeng-ke, GUO Lie, MA Yue, YUE Ming. Overview of lane-keeping assist system based on human–machine cooperative control[J]. Chinese Journal of Engineering, 2021, 43(3): 355-364. doi: 10.13374/j.issn2095-9389.2020.10.13.001
Citation: QIN Zeng-ke, GUO Lie, MA Yue, YUE Ming. Overview of lane-keeping assist system based on human–machine cooperative control[J]. Chinese Journal of Engineering, 2021, 43(3): 355-364. doi: 10.13374/j.issn2095-9389.2020.10.13.001

Overview of lane-keeping assist system based on human–machine cooperative control

doi: 10.13374/j.issn2095-9389.2020.10.13.001
More Information
  • Corresponding author: E-mail: guo_lie@dlut.edu.cn
  • Received Date: 2020-10-13
  • Publish Date: 2021-03-26
  • As the final stage of intelligent vehicle, traffic accidents can be effectively reduced by automatic driving. However, neither the technology nor the regulations are mature for autonomous driving. The lane-keeping assist system is one of the important components of the advanced driver-assistance system. When driver fatigue or inattention is detected, the system can effectively prevent the vehicle departure from the lane. Information such as vehicle status, driver status, and external environment can be used by the lane-keeping assist system based on human–machine dynamic cooperative control, thereby smoothly changing the driving rights between the driver and the automatic controller. The system can keep the vehicle in the lane while complying with the driver's intention, thereby ensuring vehicle safety and driver comfort. The research status and future development suggestions on lane-departure decision models, dynamic allocation of driving rights, and performance evaluation were analyzed in this paper. Regarding lane-departure decision models, different decision models considering the driver's state should be developed. The decision model can be established as an adaptive adjustment model and also should allow the manual adjustment of the preset parameters according to the driver’s preferences and the external driving environment. Concerning the allocation of driving rights, a more reasonable dynamic allocation of driving rights should be explored, and intelligent optimization algorithms or control models should be designed. Regarding performance evaluation indicators, evaluation indicators related to the reduction of human–machine conflict and the amount of control effort should be added. A scientific and complete subjective evaluation system should be developed. Future studies on lane-keeping assist system based on human–machine cooperative control should deeply integrate driver factors, issue real-time warnings and active intervention, and perform complete testing and evaluation of the system.

     

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