Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (2): 419-433.doi: 10.13229/j.cnki.jdxbgxb.20231033

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Review of drivers' takeover behavior in conditional automated driving

Fa-cheng CHEN1(),Guang-quan LU2,Qing-feng LIN2,Hao-dong ZHANG3,She-qiang MA1(),De-zhi LIU4,Hui-jun SONG4   

  1. 1.School of Traffic Management,People's Public Security University of China,Beijing 100038,China
    2.School of Transportation Science and Engineering,Beihang University,Beijing 100191,China
    3.School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China
    4.ENN Energy Logistics Limited,Langfang 065000,China
  • Received:2023-09-27 Online:2025-02-01 Published:2025-04-16
  • Contact: She-qiang MA E-mail:chenfchengzc@126.com;masheqiang@163.com

Abstract:

The current research status in the field of takeover behavior was summarized from two aspects: impact mechanism and improvement methods. In terms of the influence mechanism of takeover behavior, the influence factors were systematically divided into automated driving system factors, traffic factors and driver factors, and more carefully summarizes the influence mechanism of driver factors. With respect to the methods for improving takeover behavior, based on the conclusions on the impact mechanism of takeover behavior, a series of methods were summarized from aspects such as optimization design for human-machine interaction, takeover behavior modeling and prediction, and driver training for takeover. Finally, the current problems and future research directions were proposed from the perspectives of influence mechanisms and improvement methods.

Key words: engineering of communications and transportation system, conditional automated driving, takeover behavior, influence mechanism, improvement methods

CLC Number: 

  • U491

Table 1

Classification of influence factors of drivers' takeover behavior"

系统因素交通因素驾驶人因素
接管时间预算交通状况驾驶人个体特性
非驾驶任务类别道路条件驾驶人状态
接管请求预警方式天气状况驾驶人习惯

Table 2

Influence of drivers' individual characteristics on takeover behavior"

驾驶人个体特性作者结论
年龄Clark和Feng20、 K?rber等39、Wu等47年龄对驾驶人接管时间无显著影响
Li等48、So等49老年驾驶人的接管时间更长
K?rber等39老年驾驶人的接管安全性更好
Li等48老年驾驶人的接管安全性更差
Clark和Feng20、 K?rber等39老年驾驶人的纵向接管稳定性更差
性别赵晓华等50男性驾驶人对自动驾驶更加适应
So等49男性驾驶人的接管时间更短
Loeb等51男性驾驶人的接管碰撞率略小
手动驾驶经验Wright等36新手驾驶人接管时对潜在风险的识别能力较弱
Lu等27新手驾驶人接管时对车速和距离的估计较差
Chen等3、王琳岩等53新手驾驶人接管操纵稳定性较差
自动化使用经验Jin等54、Hergeth等34自动化使用经验会延长驾驶人的接管时间,但对接管质量无显著影响
创伤应激障碍症状Weigl等55严重道路交通事故产生的创伤应激障碍症状对驾驶人接管行为影响较弱
手动驾驶习惯鲁光泉等46具有低跟车风险接受习惯的驾驶人在监控自动驾驶条件下,接管后的纵向碰撞风险更小
Chen等56具有激进操纵习惯的驾驶人接管操纵反而更加稳定

Table 3

Influence of drivers' state on takeover behavior"

驾驶人状态作者结论
信任度Jin等54、Payre等57信任度升高会导致驾驶人的接管时间增加
K?rber等17信任度升高会导致驾驶人的接管稳定性和安全性下降
Jin等54信任度对驾驶人的接管质量无显著影响
困倦或精神疲劳Vogelpohl等60、Jarosch等62困倦或精神疲劳会延长驾驶人的接管时间和反应时间
Gon?alves等63困倦或精神疲劳会损害驾驶人的横向接管操纵稳定性
睡眠W?rle等66睡眠后,驾驶人的接管时间延长
W?rle等67睡眠后,驾驶人的接管质量变差
情绪Sanghavi等70愤怒情绪对驾驶人的接管时间无显著影响
Du等71情绪平静的驾驶人接管安全性和稳定性更好
饮酒Wiedemann等72饮酒会显著延长驾驶人的接管时间,并恶化其接管稳定性

Fig.1

Example of human-machine interaction optimization design"

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