中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (3): 204-211.doi: 10.16265/j.cnki.issn1003-3033.2023.03.0512

• 职业卫生 • 上一篇    下一篇

人机共驾环境下驾驶疲劳研究综述

张晖1(), 倪定安1, 曾科1,2, 丁乃侃1, 吴超仲1,**()   

  1. 1 武汉理工大学 智能交通系统研究中心,湖北 武汉 430063
    2 武汉智安交通科技有限公司,湖北 武汉 430014
  • 收稿日期:2022-10-19 修回日期:2023-01-14 出版日期:2023-03-28 发布日期:2023-11-28
  • 通讯作者: **吴超仲(1972—),男,湖北天门人,博士,教授,主要从事智能交通、车辆协同等方面的研究。E-mail: wucz@whut.edu.cn
  • 作者简介:

    张 晖 (1984—),男,安徽铜陵人,博士,副研究员,主要从事道路交通安全、驾驶行为及车路协同等方面的研究。E-mail:,

    丁乃侃 副研究员

  • 基金资助:
    国家自然科学基金资助(52072289)

A review of driving fatigue research in human-machine co-driving environment

ZHANG Hui1(), NI Dingan1, ZENG Ke1,2, DING Naikan1, WU Chaozhong1,**()   

  1. 1 Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan Hubei 430063, China
    2 Wuhan Zhian Transportation Technology Co., Ltd., Wuhan Hubei 430014, China
  • Received:2022-10-19 Revised:2023-01-14 Online:2023-03-28 Published:2023-11-28

摘要:

为减少自动驾驶过程中驾驶疲劳对驾驶人状态的影响,综合分析人机共驾环境下驾驶人的疲劳研究发展现状,系统梳理人机共驾模式下驾驶疲劳的研究成果,探索未来发展方向。首先,通过文献检索与关联性分析,明确人机共驾过程中疲劳累积研究现状;然后,从手动驾驶和人机共驾下的驾驶疲劳致因分析、驾驶时长和非驾驶相关任务对疲劳的影响、人机共驾环境下驾驶疲劳对驾驶行为的影响3个维度,讨论分析研究成果;最后,提出人机共驾环境下驾驶人疲劳研究的不足与发展方向。研究结果表明:人机共驾模式导致驾驶人被动疲劳增加,接管绩效受损,弹性设置非驾驶相关任务与自动驾驶时间可有效缓解被动疲劳;人机共驾过程中驾驶疲劳的演化规律与检测模型尚不明确,结合人机共驾场景特征探索驾驶人疲劳调控策略是未来研究重点。

关键词: 人机共驾环境, 驾驶疲劳, 自动驾驶, 非驾驶相关任务, 驾驶时长

Abstract:

In order to reduce the influence of driving fatigue on driver's state in the process of automatic driving, the development status of driver fatigue was analyzed under the environment of human-machine co-driving, the existing studies were systematically sorted out and future development of driver fatigue were put forward, too. Firstly, through literature retrieval and correlation analysis, the research status of fatigue accumulation in the process of human-machine co-driving was clarified. Then, the research results were analyzed from three dimensions: the cause analysis of driving fatigue under manual driving and human-machine co-driving, the influence of driving duration and non-driving related tasks on fatigue, and the influence of driving fatigue on driving behavior under human-machine co-driving environment. Finally, the shortcomings and development direction of driver fatigue research in human-machine co-driving environment were proposed. The results show that the human-machine co-driving mode leads to an increase in passive fatigue of the driver and the takeover performance is impaired. The flexible setting of non-driving related tasks and automatic driving time can effectively alleviate passive fatigue. The evolution law and detection model of driving fatigue in the process of human-machine co-driving are still unclear. Exploring the driver fatigue control strategy based on the characteristics of human-machine co-driving scenarios is focus of future research.

Key words: human-machine co-driving environment, driving fatigue, automatic driving, non-driving related tasks, duration of driving