Construction Research Congress 2020
Exploring the Relationship between Visual Search Patterns and Hazard Recognition Abilities
Publication: Construction Research Congress 2020: Safety, Workforce, and Education
ABSTRACT
Safety inspection on construction sites is critical for safety management, and understanding the hazard recognition strategies caters for inspection training and construction safety management. Scanpaths generated from the eye movement data of the inspectors reveal information on hazard searching strategy. However, few studies have investigated scan patterns of hazard recognition in the construction industry. This paper aims to explore visual searching strategies through eye-tracking scan patterns for construction safety inspection. An experimental study with 47 participants was designed to identify hazards in a pseudo construction site, and the scanning data were collected with a portable eye-tracking device. Artificial intelligence was then used to quantitatively define areas of interest (AOIs) based on the extracted fixation data of all participants. Finally, the searching strategies of the participants who successfully recognized hazards were compared to the strategies of those who failed. The results show that the successful participants follow similar hazard searching patterns, which are different from those of the participants who failed. This paper reports on a conceptual study of hazard searching patterns based on visual scanpaths, contributing to research of the searching strategies for hazard recognition as well as providing practical implications for hazard inspection strategies in construction projects.
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Published In
Construction Research Congress 2020: Safety, Workforce, and Education
Pages: 599 - 607
Editors: Mounir El Asmar, Ph.D., Arizona State University, David Grau, Ph.D., Arizona State University, and Pingbo Tang, Ph.D., Arizona State University
ISBN (Online): 978-0-7844-8287-2
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Nov 9, 2020
Published in print: Nov 9, 2020
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