Eye-tracking experimental study investigating the influence factors of construction safety hazard recognition

Article


Han, Y., Yin, Z., Zhang, J., Jin, R. and Yang, T. 2020. Eye-tracking experimental study investigating the influence factors of construction safety hazard recognition. Journal of Construction Engineering and Management. 146 (8). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001884
TypeArticle
TitleEye-tracking experimental study investigating the influence factors of construction safety hazard recognition
AuthorsHan, Y., Yin, Z., Zhang, J., Jin, R. and Yang, T.
Abstract

Construction site accidents can be reduced if hazards leading to accidents are correctly and promptly detected by employees. Proactive safety measures such as safety perception and safety detection capability of employees play an important role in improving the safety performance. This study was initiated by three research questions related to (1) the measurement indicators of employees’ cognitive load in recognizing safety hazards; (2) site condition factors (e.g., brightness) that can affect subjects’ cognitive load; and (3) the quantification of the effects of these site factors on cognitive load. An eye-tracking experimental approach was adopted by recruiting a total of 55 students from construction management or other civil engineering disciplines to visually search hazards in 20 given site scenes. These site scenes were defined by a combination of three different categories, namely distinctiveness of hazards, site brightness, and tidiness. Quantitative measurements of experimental participants’ visual search patterns were obtained from data captured by the eye-tracking apparatus. Based on metrics related to experimental participants’ fixation, visual search track, and attention map, these measurements were computed to evaluate participants’ cognitive load in detecting hazards. Descriptive statistical comparisons analyzed these metrics under predefined categories of site conditions, i.e., distinctness versus obscurity/blurriness, brightness versus darkness, and tidiness versus messiness. The findings revealed that distinct site conditions reduced participants’ time in saccades to search hazards but did not improve the accuracy rate of first fixation; messy sites with disorganized items increased participants’ cognitive load in detecting hazards in terms of all five measurement items (i.e., accuracy rate of first fixation, fixation count, intersection coefficient, fixation duration, and fixation count in the attention center); the effect of increased brightness on-site needs further studies to determine the optimal balance of brightness level and allocation. Recommendations based on the findings were provided to enhance safety education in terms of site hazard distinctiveness, brightness, and housekeeping best practice. This study extended a few prior studies of adopting eye-tracking technology for safety monitoring by evaluating the impacts of site conditions on participants’ cognitive load, which was linked to their hazard detection performance. The study provided insights for evaluating construction employees’ hazard detection capabilities to enhance safety education. Future work is proposed to evaluate employees’ safety hazard detection pattern under dynamic construction scenarios.

KeywordsEye-tracking; Construction safety; Safety education; Hazard detection; Cognitive load
PublisherAmerican Society of Civil Engineers (ASCE)
JournalJournal of Construction Engineering and Management
ISSN0733-9364
Electronic1943-7862
Publication dates
Online05 Jun 2020
Print31 Aug 2020
Publication process dates
Deposited15 Jun 2020
Accepted09 Mar 2020
Output statusPublished
Accepted author manuscript
Copyright Statement

This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at : https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001884 in the ASCE Library

Digital Object Identifier (DOI)https://doi.org/10.1061/(ASCE)CO.1943-7862.0001884
Web of Science identifierWOS:000542675500013
LanguageEnglish
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