Abstract
Visual attention of construction workers is closely related to their safety performance. Identifying and understanding safety signs on workplace effectively is beneficial to improve visual attention. This study focuses on exploring the influencing mechanism of construction safety sign features on visual attention of construction workers using the eye-tracking technology, in order to improve visual attention and workplace safety performance through optimizing the construction safety signs. A theoretical model of influencing mechanism of safety sign features on visual attention was constructed based on visual information processing theory. To verify the theoretical model, an experiment was conducted as follows: 28 pictures of safety signs including visual and cognitive features were shown on the computer screen, then eye movement data from 41 subjects was obtained using EyeLink1000 Plus. Statistical test methods were employed to analyze the relationship between safety sign features and eye-tracking metrics. The statistical results of theoretical model indicate that, among visual features, red and rectangular safety signs can reduce cognitive load of first fixation, green signs can reduce cognitive difficulties, however visual attention is not closely related to auxiliary words. Among the cognitive features, unfamiliar signs require more cognitive effort, while no significant difference exists in visual attention of different levels of concreteness and sematic closeness. This study provides theoretical and practical basis for improving construction workers’ visual attention through optimizing visual and cognitive features of construction safety signs.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities of China
Graduate Innovation Program of China University of Mining and Technology
Postgraduate Research & Practice Innovation Program of Jiangsu Province
Subject
Building and Construction,Civil and Structural Engineering,Architecture
Cited by
3 articles.
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