Toward an Intelligent Low-Altitude UAS Traffic Management System


The future of UAS operations in low-altitude airspace depends in part on the efficient utilization of airspace resources and the safe operation and restriction of the flight plans. Current methods for reserving low-altitude airspace depend on static reservation of 3D space for the entire planned flight time of UAS, a method known as static geofencing. This method ensures that UAS have ample room to adjust for errors in position information, weather conditions, and system failures, in order to ensure safe flight, but it also generates inefficiencies. Dynamic geofencing has been proposed by Dr. Wei’s group as a way to overcome the limitations of static geofencing. Dynamic geofencing draws information from flight plan filing data to create the probabilistic positions of UAS at specific flight times, which reduces the volume of reserved airspace required for UAS at any given time while maintaining the same level of safety as static geofencing. This method will greatly improve the ability to increase the duration of safe autonomous operations.

Student Participation:

A primary focus of this research includes comparing the benefits of increased air traffic efficiency with the more computationally complex construction of small moving geofences. LAUNCH students will analyze the theoretical maximum utilization of a perfect geofence system and a practical application of simulated flight paths and times based on hypothetical numbers for realistic UAS characteristics. They will also analyze the concept of a hybrid system based on both static and dynamic geofences to determine how far geofencing can be simplified without losing its benefits of a geofence system. The ultimate goal of this research is to help design and implement the UAS traffic management system that civil aviation authorities have called for in the near future to enable safe and efficient low-altitude operation.

Project Mentor: Dr. Peng Wei


Application Due:

February 15, 2019

Program Dates:

May 26-Aug 2, 2019