Leveraging UAV Autonomy for Minimum 4D Flight Authorization Volumes

Abstract

The increasing UAV traffic in urban areas has prompted the creation of U-space, an EASA framework for safe and efficient unmanned aerial vehicle (UAV) operations. Within this context, this work presents a flight authorization framework that leverages autonomous UAVs, using their motion models and control characteristics to improve authorization efficiency. In the proposed framework, probabilistic spatial-temporal envelopes are generated to predict future UAV locations within a desired confidence level, and this information is then used to determine the minimum 4D operational volumes that form a valid authorization request for the mission. By reserving only the necessary airspace, the approach enhances capacity and supports simultaneous UAV operations. Simulations comparing the proposed method with a conventional rule-based strategy demonstrate consistently more compact and efficient airspace reservations across a range of mission types.