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How Does Approaching a Lead Vehicle and Monitoring Request Affect Drivers’ Takeover Performance? A Simulated Driving Study with Functional MRI

Author

Listed:
  • Chimou Li

    (CCCC Wenshan Highway Construction & Development Co., Ltd., Wenshan 663000, China)

  • Xiaonan Li

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Jiading, Shanghai 201804, China)

  • Ming Lv

    (CCCC Wenshan Highway Construction & Development Co., Ltd., Wenshan 663000, China)

  • Feng Chen

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Jiading, Shanghai 201804, China)

  • Xiaoxiang Ma

    (School of Transportation and Logistics Southwest Jiaotong University, Chengdu 611756, China)

  • Lin Zhang

    (Shanghai Municipal Engineering Design Institute (Group) Co., Ltd., Shanghai 200437, China)

Abstract

With the popularization and application of conditionally automated driving systems, takeover requirements are becoming more and more frequent, and the subsequent takeover safety problems have attracted attention. The present study used functional magnetic resonance imaging (fMRI) technology, combined with driving simulation experiments, to study in depth the effects of critical degree and monitor request (MR) 30 s in advance on drivers’ visual behavior, takeover performance and brain activation. Results showed that MR can effectively improve the driver’s visual and takeover performance, including visual reaction times, fixation frequency and duration, takeover time, and takeover mode. The length of the reserved safety distance can significantly affect the distribution of longitudinal acceleration. Critical or non-critical takeover has a significant impact on the change of pupil diameter and the standard deviation of lateral displacement. Five brain regions, including the middle occipital gyrus (MOG), fusiform gyrus (FG), middle temporal gyrus (MTG), precuneus and precentral, are activated under the stimulation of a critical takeover scenario, and are related to cognitive behaviors such as visual cognition, distance perception, memory search and movement association.

Suggested Citation

  • Chimou Li & Xiaonan Li & Ming Lv & Feng Chen & Xiaoxiang Ma & Lin Zhang, 2021. "How Does Approaching a Lead Vehicle and Monitoring Request Affect Drivers’ Takeover Performance? A Simulated Driving Study with Functional MRI," IJERPH, MDPI, vol. 19(1), pages 1-20, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:412-:d:715093
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    References listed on IDEAS

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    1. Ioannis Politis & Stephen Brewster & Frank Pollick, 2017. "Using Multimodal Displays to Signify Critical Handovers of Control to Distracted Autonomous Car Drivers," International Journal of Mobile Human Computer Interaction (IJMHCI), IGI Global, vol. 9(3), pages 1-16, July.
    2. Arakawa, Toshiya & Hibi, Ryosuke & Fujishiro, Taka-aki, 2019. "Psychophysical assessment of a driver’s mental state in autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 587-610.
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    Cited by:

    1. Haorong Peng & Feng Chen & Peiyan Chen, 2022. "Examining the Effects of Visibility and Time Headway on the Takeover Risk during Conditionally Automated Driving," IJERPH, MDPI, vol. 19(21), pages 1-17, October.

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