Student: Connor Born, Undergraduate Student in Aerospace Engineering, Iowa State University
Research Mentor: Peng Wei
Low Altitude UAS Traffic Coordination with Dynamic Geofencing
The future of drone operations in low altitude airspace and integration into the national airspace depends, in part, on the efficient utilization of airspace resources and the safe operation and restriction of certain flight plans. Current methods for reserving airspace depend on the static reservation of three-dimensional space for the flight time of the drone, known as static geofencing. This ensures that the drone has ample room for errors in position information, weather conditions and system failures to enable safe flight for both drone operators and the ground. This research is focused on fixing the inefficiencies that setting static geofencing as a precedent could create. Instead, the idea of dynamic geofencing is proposed. Dynamic geofencing draws information from flight plan filing data to create probabilistic positions of drones at specific times in flight. Using the fact that, given a maximum speed, a drone must reach certain waypoints in its flight plan before a certain time to arrive by its filed arrival time, a region can be created that describes where a drone must be for it to adhere to its filed route. This means that you can drastically reduce the volume of reserved airspace required for a drone at any given time while maintaining the same level of safety as static geofencing. Only two simple assumptions must be made, a maximum speed is set and the drone must arrive by a specific time. Given the various kinds of missions a drone may be assigned, the utility of this type of airspace reservation becomes readily apparent especially in delivery/round-trip missions.
Currently planned work is to construct a test vehicle to better understand the dynamics of quadrotor flight. Wind and other factors can play a large role in determining the size and shapes of geofences which means that filed flight plans may deviate from true flights depending on external factors. It is hoped that by building a test bed from which we can analyze how various factors may affect flight, we can better understand how to build geofences more effectively.