A Spatial-Temporal Analysis of Brain Activation to Explain the Take-Over Failure in Conditionally Automated Driving

被引:1
|
作者
Yin, Weiru [1 ]
Chai, Chen [2 ,3 ]
Weng, Shixuan [2 ,3 ]
Shi, Xiupeng [4 ]
机构
[1] Huawei Technol Co Ltd, Shanghai, Peoples R China
[2] Minist Educ, Key Lab Rd & Traff Engn, Shanghai, Peoples R China
[3] Tongji Univ, Shanghai, Peoples R China
[4] Shanghai Univ, Shanghai, Peoples R China
基金
国家重点研发计划; 美国国家科学基金会;
关键词
conditionally automated driving; take-over failure; brain activation; spatial-temporal analysis; functional near-infrared spectroscopy; NEAR-INFRARED SPECTROSCOPY; PREFRONTAL CORTEX; TIME; PERFORMANCE; BEHAVIOR; DRIVERS; SITUATIONS; VEHICLES;
D O I
10.1177/00187208241283606
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Objective This study aims to investigate the causes of take-over failures in conditional automated driving with spatial-temporal analysis of brain zone activation.Background Take-over requires a human driver to resume the control of the vehicle when its automation system disengages. Existing studies have found that take-over failures occur frequently on some drivers, but the causes have not been thoroughly studied.Method In a driving simulator experiment, 40 drivers took over in critical freeway cut-in situations. Functional near-infrared spectroscopy (fNIRS) data were collected before and during the take-over process to evaluate brain zone activation. Successful and failed take-overs were compared with changes in fNIRS data based on spatial-temporal comparisons and cluster analysis.Results The results suggested a significant difference in temporal brain activation between take-over failure and success conditions. Take-over failure conditions are mostly related to earlier and longer brain activation in most brain zones and repeated activation of the cognition brain zones. Drivers' attention switches, steering, and braking patterns are also related to different brain zone activation orders.Conclusion The results indicate the need to reduce the mental workload caused by the sudden system disengagement to prevent take-over failure.Application Future research and implementation should focus on earlier warnings of upcoming hazards and driver education in dealing with sudden system disengagement.
引用
收藏
页码:445 / 463
页数:19
相关论文
共 42 条
  • [1] Take-Over Intention during Conditionally Automated Driving in China: Current Situation and Influencing Factors
    Feng, Zhongxiang
    Li, Jingyu
    Xu, Xiaoqin
    Guo, Amy
    Huang, Congjun
    Jiang, Xu
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (21)
  • [2] Assisted Partial Take-Over in Conditionally Automated Driving: A User Study
    Gruden, Timotej
    Sodnik, Jaka
    Jakus, Grega
    IEEE ACCESS, 2023, 11 : 107940 - 107957
  • [3] Wake Up and Take Over! The Effect of Fatigue on the Take-over Performance in Conditionally Automated Driving
    Feldhuetter, Anna
    Kroll, Dominik
    Bengler, Klaus
    2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2018, : 2080 - 2085
  • [4] How to identify the take-over criticality in conditionally automated driving? An examination using drivers' physiological parameters and situational factors
    Yi, Binlin
    Cao, Haotian
    Song, Xiaolin
    Zhao, Song
    Guo, Wenfeng
    Li, Mingjun
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2022, 85 : 161 - 178
  • [5] Take-Over Performance and Safety Analysis Under Different Scenarios and Secondary Tasks in Conditionally Automated Driving
    Wu, Chaozhong
    Wu, Haoran
    Lyu, Nengchao
    Zheng, Mengfan
    IEEE ACCESS, 2019, 7 : 136924 - 136933
  • [6] Take-Over Time: A Cross-Cultural Study of Take-Over Responses in Highly Automated Driving
    Strle, Gregor
    Xing, Yilun
    Miller, Erika E.
    Boyle, Linda Ng
    Sodnik, Jaka
    APPLIED SCIENCES-BASEL, 2021, 11 (17):
  • [7] Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving
    Zeeb, Kathrin
    Buchner, Axel
    Schrauf, Michael
    ACCIDENT ANALYSIS AND PREVENTION, 2016, 92 : 230 - 239
  • [8] Understanding Take-Over in Automated Driving: A Human Error Analysis
    Li, Jue
    Liu, Long
    Gu, Liwen
    HCI IN MOBILITY, TRANSPORT, AND AUTOMOTIVE SYSTEMS, MOBITAS 2021, 2021, 12791 : 281 - 295
  • [9] Understanding take-over performance of high crash risk drivers during conditionally automated driving
    Lin, Qingfeng
    Li, Shiqi
    Ma, Xiaowei
    Lu, Guangquan
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 143
  • [10] Long automated driving phase affects take-over performance
    Bourrelly, Aurore
    de Naurois, Charlotte Jacobe
    Zran, Asmae
    Rampillon, Felicie
    Vercher, Jean-Louis
    Bourdin, Christophe
    IET INTELLIGENT TRANSPORT SYSTEMS, 2019, 13 (08) : 1249 - 1255