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驾驶人跟车风险接受水平对其接管绩效的影响

Effect of Drivers’ Acceptance Level of Car-following Risk on the Takeover Performance

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【作者】 鲁光泉陈发城李鹏辉翟俊达谭海天赵鹏云

【Author】 Lu Guangquan;Chen Facheng;Li Penghui;Zhai Junda;Tan Haitian;Zhao Pengyun;School of Transportation Science and Engineering,Beihang University,Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control;Beijing Advanced Innovation Center for Big Data and Brain Computing,Beihang University;School of Vehicle and Mobility,Tsinghua University,State Key Laboratory of Automotive Safety & Energy;School of Public Security and Traffic Management,People’s Public Security University of China;

【通讯作者】 李鹏辉;

【机构】 北京航空航天大学交通科学与工程学院车路协同与安全控制北京市重点实验室北京航空航天大学大数据科学与脑机智能高精尖创新中心清华大学车辆与运载学院汽车安全与节能国家重点实验室中国人民公安大学治安与交通管理学院

【摘要】 自动驾驶接管是一种安全性要求很高的手动驾驶操作,可能会受到驾驶人手动驾驶安全习惯的影响。本文基于驾驶模拟器分别设计了手动驾驶跟车和自动驾驶接管实验,研究了驾驶人的手动跟车风险接受水平对其接管绩效的影响,同时考虑了接管时间预算和视觉非驾驶任务的影响。结果表明:在日常驾驶中具有低跟车风险接受水平的驾驶人接管反应时间更短,并且在监控自动驾驶条件下,接管后表现出更低的纵向碰撞风险。此外,当驾驶人处于视觉分心状态时,5 s的接管时间预算会导致驾驶人接管后出现较差的横纵向稳定性和极高的纵向碰撞风险。本研究的结果可为个性化自动驾驶系统的设计提供理论依据。

【Abstract】 Takeover in automated driving is a kind of manual driving operation with high safety requirements,which may be affected by the driver’s manual driving safety habits. Based on a driving simulator,the manual car-following and an automated driving takeover experiments are designed in this paper to study the influence of the driver’acceptance level of car-following risk on the takeover performance. Meanwhile,the impact of takeover time budget and visual non-driving related task is also investigated. The results indicate that drivers with a low acceptable level of car-following risk in daily driving have shorter takeover reaction time,and show lower longitudinal collision risk after taking over from the condition of monitoring automated driving. In addition,when drivers are in the state of visual distraction,the 5 s takeover time budget leads to poor lateral and longitudinal stability and high longitudinal collision risk. The results of this study can provide a theoretical basis for the design of personalized automated driving system.

【基金】 国家自然科学基金委-中国汽车产业创新发展联合基金(U1664262);中国人民公安大学公共安全行为科学实验室开放课题基金(2021SYS01)资助
  • 【文献出处】 汽车工程 ,Automotive Engineering , 编辑部邮箱 ,2021年06期
  • 【分类号】U463.6
  • 【被引频次】1
  • 【下载频次】519
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