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Investigating the Impact of Human Risk Taking Tendency on the Likelihood of Struck-By Accidents in Construction Using Agent-Based Simulation

Cited 2 time in Web of Science Cited 2 time in Scopus
Authors

Sun, Cenfei; Ahn, Seungjun; Ahn, Changbum

Issue Date
2017
Publisher
American Society of Civil Engineers (ASCE)
Citation
Congress on Computing in Civil Engineering, Proceedings, Vol.2017-June, pp.306-314
Abstract
Struck-by accidents are a major type of accidents which can occur on construction sites. Researchers have developed several methods for reducing the chance of struck-by accidents in construction, such as spatial conflict assessment and workspace analysis. However, scarce attention has been paid to the impact individual risk taking tendencies have on the occurrence of struck-by accidents. Findings in psychology clearly suggest that individuals have different risk-taking tendencies (e.g., risk takers vs. risk avoiders) in various situations, and that behavioral patterns affect the occurrence of certain types of accidents. Individual differences in risk taking tendency manifest under dangerous situations, and consequently affect the probability that an individual experiences a struck-by accident. Against this background, it is proposed that an agent-based simulation can be used to predict potential collisions between equipment and workers and to investigate the impact of different risk-taking tendencies on the occurrence of stuck-by accidents on construction sites. In this research, different risk taking tendencies are modeled into agent behavior rules, this simulation model generates moving trajectories of workers and equipment, which can be used to predict potential collisions and the consequences of different individual risk-taking tendencies under collision-possible situations. This paper demonstrates research opportunities associated with the proposed approach using an illustrative example.
URI
https://hdl.handle.net/10371/203272
DOI
https://doi.org/10.1061/9780784480830.038
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  • College of Engineering
  • Department of Architecture & Architectural Engineering
Research Area Computing in Construction, Management in Construction

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