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The Effect of Multifactor Interaction on the Quality of Human–Machine Co-Driving Vehicle Take-Over

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  • Yaxi Han

    (Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China)

  • Tao Wang

    (Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China)

  • Dong Shi

    (Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin 541004, China)

  • Xiaofei Ye

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Quan Yuan

    (State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China)

Abstract

This paper investigates the effects of non-driving related tasks, take-over request time, and take-over mode interactions on take-over performance in human–machine cooperative driving in a highway environment. Based on the driving simulation platform, a human–machine collaborative driving simulation experiment was designed with various take-over quality influencing factors. The non-driving related tasks included no task, listening to the radio, watching videos, playing games, and listening to the radio and playing games; the take-over request time was set to 6, 5, 4, and 3 s, and the take-over methods include passive and active take-over. Take-over test data were collected from 65 drivers. The results showed that different take-over request times had significant effects on driver take-over performance and vehicle take-over steady state ( p < 0.05). Driver reaction time and minimum TTC decreased with decreasing take-over request time, maximum synthetic acceleration increased with decreasing take-over request time, accident rate increased significantly at 3 s take-over request time, and take-over safety was basically ensured at 4 s request time. Different non-driving related tasks have a significant effect on driver take-over performance ( p < 0.05). Compared with no task, non-driving related tasks significantly increase driver reaction time, but they only have a small effect on vehicle take-over steady state. Vehicle take-over mode has a significant effect on human–machine cooperative driving take-over quality; compared with passive take-over mode, the take-over quality under active take-over mode is significantly lower.

Suggested Citation

  • Yaxi Han & Tao Wang & Dong Shi & Xiaofei Ye & Quan Yuan, 2023. "The Effect of Multifactor Interaction on the Quality of Human–Machine Co-Driving Vehicle Take-Over," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5131-:d:1096795
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    References listed on IDEAS

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    1. Robertson, Robyn D. & Meister, Shawna R. & Vanlaar, Ward G.M. & Mainegra Hing, Marisela, 2017. "Automated vehicles and behavioural adaptation in Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 50-57.
    2. Qiuhong Wang & Haolin Chen & Jianguo Gong & Xiaohua Zhao & Zhenlong Li, 2022. "Studying Driver’s Perception Arousal and Takeover Performance in Autonomous Driving," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    3. Nielsen, Thomas Alexander Sick & Haustein, Sonja, 2018. "On sceptics and enthusiasts: What are the expectations towards self-driving cars?," Transport Policy, Elsevier, vol. 66(C), pages 49-55.
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