Conflict probability estimation using a riskbased dynamic anisotropic operational safety bound for UAV traffic management

The safety and efficiency of rotary-wing UAV traffic management require an operational safety bound and fast conflict prediction. A novel method to determine probabilistic riskbased operational safety bound for rotary-wing UAV traffic management is proposed. The key idea is to include probabilistic uncertainty quantification of the safety bound. The unique design for the operational safety bound results in a dynamic and anisotropic shape of the bound which considers the vectorized velocity of the UAV and wind. Operational safety bound is used to identify a virtual geographic boundary to protect aircraft and to ensure airspace safety. The proposed operational safety bound is calculated as a function of vehicle performance characteristics, state of vehicle, wind, and other probabilistic parameters that affect the real position of vehicle, such as the position error from the Global Positioning System (GPS). This paper presents an efficient method to estimate the probability that a conflict will occur between a UAV pair in confined airspace using the proposed risk-based dynamic anisotropic operational safety bounds. Conflict probability is critical to evaluate airspace capacity and to determine the optimal time to initiate conflict resolution maneuver. Several conclusions and suggestions of further research directions are given.