Assessing Mid-Air Collision Risk Between Commercial Aircraft and Small Uncrewed Aircraft Systems: A Functional Resonance Analysis Approach

Abstract

Unauthorized use of small drones is becoming a serious threat, raising new safety concerns in commercial aviation. Although collisions between drones and aircraft are still rare, near misses indicate potential risks of serious accidents. This study uses the Functional Resonance Analysis Method to assess systemic hazards from drone encounters in controlled airspace. Voluntary pilot safety reports and previous research on collision techniques and pilot responses were reviewed. The initial risk assessment was rated high, underscoring the need for targeted mitigation strategies. Recommended measures include stricter regulations, geofencing, training, improved reporting, and advanced detect-and-avoid systems. These actions could significantly lower the risk and enhance overall safety management. This study demonstrates that the Functional Resonance Analysis Method can be an effective tool for airline operators to help identify emerging hazards and proactively incorporate mitigation measures into safety systems.