Airspace Advisory Service: Towards Detect and Avoid for UAS Operators Utilizing the Traffic Information Service

In this paper, we propose a concept design for an Airspace Advisory Service (AAS), assisting Unmanned Aerial System (UAS) operators with Detect and Avoid capabilities during flight operations. The AAS utilizes the traffic information service from the U-space service providers. Based on adjacent air traffic, two risk indexes are introduced for each aircraft near the operating Unmanned Aerial Vehicle (UAV); 1) a Collision Risk Index, assessing the probability of the aircraft entering the UAV's Remain Well Clear volume, and; 2) Intruder Risk Index, assessing the probability of the aircraft breaching the UAV's Operational Volume. Both risk indexes are fuzzy logic-based, and the calculation of them is presented using real flight data for two different flight scenarios. Moreover, the Traffic Advisory and Resolution Advisory principles from the TCAS concept are applied for each aircraft by calculating dynamic elliptical models based on their horizontal velocity and expected angular change of heading. A recommended advisory is determined for each aircraft and provided to the UAS operator for maintaining a safe operation. The proposed concept design has been integrated into an existing ground control station software, named QGroundControl, as a proof of concept. Input from experienced UAS operators, eg. how to visually display relevant information for decision-making, have been included in the integration process. The comparison between QGroundControl with/without the AAS integrated shows the enhancement of situational awareness. Simulated air traffic has been used for validating the behavior of the AAS and for testing its CPU usage when processing up to 15 aircraft simultaneously. A higher CPU usage was observed but is not considered to have a significant influence on the overall CPU performance.