A Probability Collision Risk Assessment and Decision Support Framework for UAV Intrusion in Airport Terminal Airspace

UAV intrusion events pose significant safety risks to airport operation due to their high uncertainty, limited observability and potential operational disruptions. This paper proposes an integrated trajectory uncertainty prediction and collision risk assessment framework for UAV intrusion scenarios in airport terminal airspace. A probabilistic trajectory prediction model is developed to estimate both UAVs and manned aircraft future positions and their associated uncertainties. Based on these heterogeneous trajectory predictions, a collision risk assessment method is established to derive the lower bound of time-to-collision and upper bound of collision probability in both nominal and worst-case intrusion scenarios. Quantitative risk indicators are also provided to support maneuvering and countermeasure decisions during critical flight phases. Results demonstrate that the proposed framework can provide accurate collision risk estimates, supporting timely decision-making under representative UAV intrusion events.