Autonomous Separation in U-Space: Assessing the Impact of Position Uncertainty

Abstract

With the rapid increase in the use of Unmanned Aerial Systems (UAS) for commercial applications such as medical and parcel delivery, the need for safe airborne separation in airspace has become critical. This paper examines the impact of position uncertainty on autonomous separation methods within U-Space, a European Union initiative for managing drone traffic. The study focuses on evaluating various conflict resolution algorithms—specifically, Modified Voltage Potential (MVP) and Velocity Obstacle (VO) variations—under conditions of navigational uncertainty. Through Monte Carlo simulations using the BlueSky ATM simulator, position uncertainty stemming from Global Navigation Satellite Systems (GNSS) errors is modelled and analysed. The research compares the effectiveness of different conflict resolution strategies in preventing conflicts between UAS, measuring intrusion prevention rates and the closest point of approach during encounters. The results indicate that MVP provides superior performance in handling positional uncertainty, offering more robust conflict resolution capabilities than VObased methods. These findings are critical for ensuring the safe integration of UAS into increasingly congested airspace environments, guiding future developments in U-Space operations.