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Exploring the Visual Attention Mechanism of Long-Distance Driving in an Underground Construction Cavern: Eye-Tracking and Simulated Driving

Author

Listed:
  • Qin Zeng

    (Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang 443002, China
    College of Economics & Management, China Three Gorges University, Yichang 443002, China
    College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Yun Chen

    (Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang 443002, China
    College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Xiazhong Zheng

    (Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang 443002, China
    College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Meng Zhang

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Donghui Li

    (Building Decoration Supervision Station, Yichang Municipal Housing and Urban-Rural Development Bureau, Yichang 443000, China)

  • Qilin Hu

    (Sinohydro Bureau 5 Co., Ltd., Power Construction Corporation of China, Chengdu 610066, China)

Abstract

Prolonged driving is necessary in underground construction caverns to transport materials, muck, and personnel, exposing drivers to high-risk and complex environments. Despite previous studies on attention and gaze prediction at tunnel exit-inlet areas, a significant gap remains due to the neglect of dual influences of long-distance driving and complex cues. To address this gap, this study establishes an experimental scenario in a construction environment, utilizing eye-tracking and simulated driving to collect drivers’ eye movement data. An analysis method is proposed to explore the visual change trend by examining the evolution of attention and calculating the possibility of visual cues being perceived at different driving stages to identify the attentional selection mechanism. The findings reveal that as driving time increases, fixation time decreases, saccade amplitude increases, and some fixations transform into unconscious saccades. Moreover, a phenomenon of “visual adaptation” occurs over time, reducing visual sensitivity to environmental information. At the start of driving, colorful stimuli and safety-related information compete for visual resources, while safety-related signs, particularly warning signs, always attract drivers’ attention. However, signs around intense light are often ignored. This study provides a scientific basis for transport safety in the construction environment of underground caverns.

Suggested Citation

  • Qin Zeng & Yun Chen & Xiazhong Zheng & Meng Zhang & Donghui Li & Qilin Hu, 2023. "Exploring the Visual Attention Mechanism of Long-Distance Driving in an Underground Construction Cavern: Eye-Tracking and Simulated Driving," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9140-:d:1164550
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    References listed on IDEAS

    as
    1. Ting Shang & Hao Lu & Peng Wu & Yi Wei, 2021. "Eye-Tracking Evaluation of Exit Advance Guide Signs in Highway Tunnels in Familiar and Unfamiliar Drivers," IJERPH, MDPI, vol. 18(13), pages 1-14, June.
    2. Qian Xu & Tang-yi Guo & Fei Shao & Xue-jiao Jiang, 2017. "Division of Area of Fixation Interest for Real Vehicle Driving Tests," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, May.
    3. Amin Azimian & Carlos Alberto Catalina Ortega & Juan Maria Espinosa & Miguel Ángel Mariscal & Susana García-Herrero, 2021. "Analysis of Drivers’ Eye Movements on Roundabouts: A Driving Simulator Study," Sustainability, MDPI, vol. 13(13), pages 1-10, July.
    4. Sónia Soares & Carlos Campos & João Miguel Leitão & António Lobo & António Couto & Sara Ferreira, 2021. "Distractive Tasks and the Influence of Driver Attributes," Sustainability, MDPI, vol. 13(9), pages 1-20, May.
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