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Design of a VR Driving Training Interface Oriented Toward Optimizing Visual Attention Pathways: An Empirical Study Based on Multi-Metric Eye-Tracking.

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Bibliographic Details
Title: Design of a VR Driving Training Interface Oriented Toward Optimizing Visual Attention Pathways: An Empirical Study Based on Multi-Metric Eye-Tracking.
Authors: Cheng, Junhao (AUTHOR), Chen, Xiangpei (AUTHOR), Hu, Bin (AUTHOR), Yang, Xian (AUTHOR)
Source: International Journal of Human-Computer Interaction. Jun2026, Vol. 42 Issue 11, p8361-8387. 27p.
Subjects: Eye tracking, Head-up displays, Attention control, Virtual reality, User interfaces, Traffic safety, Cognitive psychology, Automobile driver education
Abstract: As rising traffic density heightens safety challenges, immersive and personalized defensive driving training has become essential. This study employs virtual reality (VR) with integrated eye-tracking to examine how interface variables—traffic light size, brightness, signage size, and information display mode—affect drivers' visual attention. Results show that enlarging lights and signs to 1.5 times their original size significantly reduced fixation durations and improved cognitive efficiency. Compared to center console displays (CCD), Head-Up Displays (HUD) yielded higher fixation time, more fixation points, and stronger attention stability. Brightness increases mainly influenced initial attention but showed diminishing returns for cognitive processing. The study introduces a Unity-based collider detection and automated eye-tracking script to enhance data accuracy and reproducibility. Theoretically, it integrates visual saliency modeling and user experience design to construct a pathway linking visual features, attention capture, and cognitive processing, offering design implications for VR driving systems. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
Description
Abstract:As rising traffic density heightens safety challenges, immersive and personalized defensive driving training has become essential. This study employs virtual reality (VR) with integrated eye-tracking to examine how interface variables—traffic light size, brightness, signage size, and information display mode—affect drivers' visual attention. Results show that enlarging lights and signs to 1.5 times their original size significantly reduced fixation durations and improved cognitive efficiency. Compared to center console displays (CCD), Head-Up Displays (HUD) yielded higher fixation time, more fixation points, and stronger attention stability. Brightness increases mainly influenced initial attention but showed diminishing returns for cognitive processing. The study introduces a Unity-based collider detection and automated eye-tracking script to enhance data accuracy and reproducibility. Theoretically, it integrates visual saliency modeling and user experience design to construct a pathway linking visual features, attention capture, and cognitive processing, offering design implications for VR driving systems. [ABSTRACT FROM AUTHOR]
ISSN:10447318
DOI:10.1080/10447318.2025.2565390