Visual Saliency Design for AR-HUD Navigation in Extreme Weather: Reducing Inattentional Blindness

Background: Current research on AR-HUD visual icons focuses primarily on interface, color, and motion trajectory design. However, when displayed in complex environments, AR-HUD might cause inattentional blindness, particularly during extreme weather conditions where occurrence rates increase significantly. Methods: This study employed a two-factor within-subjects design to examine how dynamic saliency and contour saliency in AR-HUD navigation graphics affect inattentional blindness and user experience. Eye-tracking metrics with total fixation time and first fixation time, driver reaction time, and user experience scores were analyzed. Results: Objective measures revealed significant interaction effects between saliency types, though user experience feedback showed no significance. Both contour and dynamic saliency effectively reduced inattentional blindness and improved information-seeking efficiency. Conclusions: The combination of dynamic and contour saliency produced the lowest inattentional blindness rates, fastest reaction times, and highest user satisfaction. We recommend: 1) adding distinct contours to prevent environmental visual fusion, 2) implementing temporary icon enlargement during critical moments to enhance attentional capture. These findings provide actionable design principles for improving AR-HUD safety in adverse weather conditions.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3588576
Citations
3
Primary Topic
Diverse Topics in Contemporary Research
Type
article
Field-Weighted Citation Impact
49.47
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article

Visual Saliency Design for AR-HUD Navigation in Extreme Weather: Reducing Inattentional Blindness

Jordan Li, Y Liu, Qi Zhu
3 citations
IEEE Access
Diverse Topics in Contemporary Research
49.47
article

Visual Saliency Design for AR-HUD Navigation in Extreme Weather: Reducing Inattentional Blindness

Jordan Li, Y Liu, Qi Zhu
article en
3 citations

Abstract

Background: Current research on AR-HUD visual icons focuses primarily on interface, color, and motion trajectory design. However, when displayed in complex environments, AR-HUD might cause inattentional blindness, particularly during extreme weather conditions where occurrence rates increase significantly. Methods: This study employed a two-factor within-subjects design to examine how dynamic saliency and contour saliency in AR-HUD navigation graphics affect inattentional blindness and user experience. Eye-tracking metrics with total fixation time and first fixation time, driver reaction time, and user experience scores were analyzed. Results: Objective measures revealed significant interaction effects between saliency types, though user experience feedback showed no significance. Both contour and dynamic saliency effectively reduced inattentional blindness and improved information-seeking efficiency. Conclusions: The combination of dynamic and contour saliency produced the lowest inattentional blindness rates, fastest reaction times, and highest user satisfaction. We recommend: 1) adding distinct contours to prevent environmental visual fusion, 2) implementing temporary icon enlargement during critical moments to enhance attentional capture. These findings provide actionable design principles for improving AR-HUD safety in adverse weather conditions.

IEEE AccessVol. 13
Qingdao Binhai University (CN), University of Malaya (MY), Hanyang University (KR), Anyang University (KR)
Climate action
Openalex Percentile: Top 0%
Diverse Topics in Contemporary Research
49.47
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Visual Saliency Design for AR-HUD Navigation in Extreme Weather: Reducing Inattentional Blindness — Jordan Li, Y Liu, et al. · IEEE Access (2025) | TGRS Research Map | TGRS