Quantitative Assessment of Proximity Risks Associated with Unmanned Aerial Vehicles in Construction
Hashem Izadi Moud, Ian Flood, Xun Zhang, Behzad Abbasnejad, Peyman Rahgozar, Michelle McIntyre
Abstract
While unmanned aerial vehicles (UAVs) are extensively used for data collection in the construction industry, currently, no comprehensive quantitative method measures the indirect risks workers face from flying UAVs on jobsites. Augmenting past work addressing the direct risks of UAV flights, namely, crashes and collisions, this paper assesses the indirect UAV flight risks triggered by the proximity of UAVs with humans. Risk assessment is simple in theory: any risk may be quantified by knowing the probability of a risky event, the probability of impact, and/or the severity of the event. This paper (1) discusses the nature of the probability of a risky event, the probability of impact, and the probability of severity of UAV flight indirect risks and (2) presents a model for measuring the indirect risks of UAV flights when associated with the proximity of construction workers and UAVs. The proposed model is applied to a case study using Monte Carlo Simulation, and the results show the applicability of the model to a construction jobsite environment.