Collaborative Research: Measuring, Predicting, and Improving Construction Safety by Improving Hazard Signal Detection with Augmented Virtual Environments

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Each year the construction industry has a disproportionate injury rate compared to other industries. One of the main causes of these injuries is human error, which could be exacerbated by skill deficiency associated with signal detection (defined as the ability of an individual to detect visual stimuli that indicate the existence of a safety hazard). From psychological and engineering standpoints little is known about signal detection or if this skill can be accurately measured, predicted, or improved with emerging technologies. This award supports interdisciplinary research that investigates if signal detection can be reliably improved through exposure to and feedback from an augmented virtual construction environment. Additionally, the research explores if an individual's signal detection skill in a virtual environment can predict their skill in real construction environments. As new knowledge is gained, it will be shared with industry practitioners through presentations to national communities of practice, integrated into multiple levels of civil engineering and psychology curricula, and embedded in the final version of the virtual system that will disseminated broadly for education and safety training.The main objective of this research is to test hypotheses that augmented virtual environments can be used to improve signal detection skill by over 30% and that over half of the variability in signal detection skill in field environments can be predicted by one's performance in an augmented virtual system. These hypotheses will be tested using a multiple baseline design that has been adapted from pharmaceutical research to address the dynamic nature of the construction industry. The experimental results will be statistically verified using interrupted time-series regression models. If successful, the adaptation of multiple baseline design and statistical verification would serve as a new approach of experimental research for construction. Additionally, a strong relationship between performance in virtual and field environments would indicate that high-fidelity augmented virtual environments provide a risk-free proxy for measuring signal detection skill, potentially transforming the way that construction safety is studied.