Quantifying specific operation airborne collision risk through Monte Carlo simulation

Pilko, Aliaksei, Ferraro, Mario and Scanlan, James (2023) Quantifying specific operation airborne collision risk through Monte Carlo simulation. Aerospace, 10 (7), [593]. (doi:10.3390/aerospace10070593).

Record type: Article

Abstract

Integration of Uncrewed Aircraft into unsegregated airspace requires robust and objective risk assessment in order to prevent exposure of existing airspace users to additional risk. A probabilistic Mid-Air Collision risk model is developed based on surveillance traffic data for the intended operational area. Simulated probable traffic scenarios are superimposed on a desired Uncrewed Aircraft operation and then sampled using Monte Carlo methods. The results are used to estimate the operation-specific collision probability with known uncertainty in the output. The methodology is demonstrated for an example medical logistics operation in the United Kingdom, and a Target Level of Safety is used as a benchmark to decide whether the operation should be permitted.

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Accepted/In Press date: 26 June 2023

Published date: 29 June 2023

Additional Information: Funding Information: This research was funded by the Engineering and Physical Sciences Research Council grant numbers EP/V002619/1 and EP/R009953/1. Publisher Copyright: © 2023 by the authors.

Keywords: collision probability, risk quantification, unsegregated airspace