UAS Air-Risk Assessment In and Around Airports

The operation of Uncrewed Aircraft Systems (UAS) at airports is becoming more common. The increased use of small and inexpensive drones pose various challenges associated with integrating UAS operations in the national airspace system. For non-military applications, Uncrewed Aircraft (UA)s are allowed to fly below 400ft which helps to segregate UAS operations from crewed aircraft. This however does not negate the challenges and additional risk in low altitude scenarios such as in and around airports when UASs are used for commercial and security applications. Flying the UASs in such controlled airspace needs permission from authorities such as Air Traffic Control (ATC) and other controlling agencies. For such scenarios where UAS operations need to be integrated along with controlled airspace, it is important to understand and estimate the associated risk. An unintentional malfunction resulting in uncontrolled UASs poses multiple risks, particularly when operated in a busy airport environment. This includes infrastructure, ground, and air risk. When left unmitigated, such scenarios will lead to the disruption of regular operations and cause loss to the economy and sometimes human life. The paper focuses on developing an assessment tool for UAS collision risk with crewed aircraft in an airport scenario. The study focuses on the UAS risk associated with crewed aircraft flying below 1000 ft altitude within a 5 mile radius of an airport. High volume airport operations combined with low-altitude flights results in an increased risk of collision within an airport environment. The trajectory of aircraft in three-dimensional space is determined using actual historical Automatic Dependent Surveillance-Broadcast (ADS-B) data. Simulations are conducted to model various fail-safe scenarios of UASs. A probabilistic approach is used to model UA paths that assign Gaussian distributions to the mean values of the UAS’s velocity, heading, and altitude. The framework developed can be further expanded to include specific waypoints or routes other than ADS-B data. The study aims to calculate the probabilities of Mid-Air Collisions (MAC), Near Mid-Air Collisions (NMAC), and Well Clear (WC) violations entering these protected volumes between uncrewed and crewed aircraft. Initially, the study modeled the Grand Forks International Airport, which has a high volume of airport operations. Historical ADS-B data is analyzed statistically to identify the highest volume of traffic for a given day. Flight trajectories from that time interval are then extracted for analysis. The UAS-flight risk assessments are carried out for various scenarios that include the velocity of the aircraft, traffic volume, and the probability distributions of the UAS’s trajectory.