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Influence of Multi-Modal Warning Interface on Takeover Efficiency of Autonomous High-Speed Train

Author

Listed:
  • Chunhui Jing

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China
    These authors contributed equally to this work.)

  • Haohong Dai

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China
    These authors contributed equally to this work.)

  • Xing Yao

    (School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Dandan Du

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China)

  • Kaidi Yu

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China)

  • Dongyu Yu

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China)

  • Jinyi Zhi

    (Department of Industrial Design, School of Design, Southwest Jiaotong University, Chengdu 610031, China)

Abstract

As a large-scale public transport mode, the driving safety of high-speed rail has a profound impact on public health. In this study, we determined the most efficient multi-modal warning interface for automatic driving of a high-speed train and put forward suggestions for optimization and improvement. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal–Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic–text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory–visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public.

Suggested Citation

  • Chunhui Jing & Haohong Dai & Xing Yao & Dandan Du & Kaidi Yu & Dongyu Yu & Jinyi Zhi, 2022. "Influence of Multi-Modal Warning Interface on Takeover Efficiency of Autonomous High-Speed Train," IJERPH, MDPI, vol. 20(1), pages 1-17, December.
  • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:322-:d:1014713
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