# Airspace Geofencing and Flight Planning for Low-Altitude, Urban, Small Unmanned Aircraft Systems
###### Abstract  
Airspace geofencing is a key capability for low-altitude Unmanned Aircraft System (UAS) Traffic Management (UTM). Geoferenced airspace volumes can be allocated to safely contain compatible UAS flight operations within a fly-zone (keep-in geofence) and ensure the avoidance of no-fly zones (keep-out geofences). This paper presents the application of three-dimensional flight volumization algorithms to support airspace geofence management for UTM. Layered polygon geofence volumes enclose user-input waypoint-based 3-D flight trajectories, and a family of flight trajectory solutions designed to avoid keep-out geofence volumes is proposed using computational geometry. Geofencing and path planning solutions are analyzed in an accurately mapped urban environment. Urban map data processing algorithms are presented. Monte Carlo simulations statistically validate our algorithms, and runtime statistics are tabulated. Benchmark evaluation results in a Manhattan, New York City low-altitude environment compare our geofenced dynamic path planning solutions against a fixed airway corridor design. A case study with UAS route deconfiction is presented, illustrating how the proposed geofencing pipeline supports multi-vehicle deconfiction. This paper contributes to the nascent theory and the practice of dynamic airspace geofencing in support of UTM. Geofencing; unmanned aircraft systems; UAS traffic management; air traffic control; UAS; low-altitude airspace; computational geometry; path planning; route deconfiction; separation assurance; map processing +
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Researchers have previously investigated airspace geofencing systems for UTM. A two-dimensional keep-in/keep-out geofence construction algorithm was developed in [6]. Real-time geofence violation detection capabilities have been developed using Ray Casting [7] and Triangle Weight Characterization with Adjacency (TWCA) [8] methods. Potential intersections of 2-D geofences can be rapidly detected using a convex hull approach [9]. A constrained control scheme was developed using an Explicit Reference Governor (ERG) in [10]; this approach ensures a UAS does not violate geofence boundaries. This previous research primarily focused on geofence definition, boundary violation detection, and UAS avionics augmentation to support geofencing. Our work's focus on 3D path planning with geofence volumes in a realistically mapped urban environment is complementary. Cooperative UAS flight tests were also evaluated using \"separation by segregation\" geofencing features in [11]. To define a local geofence volume for applications such as crop inspection, the maximum flight distance a UAS can travel after flight termination was calculated using vehicle dynamics and position sensors in [12] to define geofence geometry. This research demonstrated that a UAS stays within its prescribed keep-in geofence in both nominal and off-nominal (e.g., flight termination) conditions. A three-dimensional dynamic geofencing volumization solution was proposed using \"operational\" and \"inverse\" volumization functions in [13]. Per [13], _airspace operational volumization_ is the process by which a requested flight plan is \"wrapped\" with a geofence reserved over an approved flight time window. _Inverse volumization_ is the opposite process in which a flight is planned to always remain within a designated airspace geofence volume. This paper extends our work in [13] in several ways. First, we integrate the individual airspace volumization algorithms into a geofencing pipeline described in Section 3. This geofencing pipeline is shown in Figure 2. We also construct simplified keep-in/keep-out 3-D geofencing boundaries based on buildings and UAS flight plans, as illustrated in Figure 1. This algorithm uses parameters such as vehicle speed, geofence boundary safety buffer size, and polygon simplification parameters to generate a flight plan that does not violate keep-in/keep-out geofences in the surrounding region.