Aerospace (Jun 2023)

Quantifying Specific Operation Airborne Collision Risk through Monte Carlo Simulation

  • Aliaksei Pilko,
  • Mario Ferraro,
  • James Scanlan

DOI
https://doi.org/10.3390/aerospace10070593
Journal volume & issue
Vol. 10, no. 7
p. 593

Abstract

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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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