Navigation Performance Derivation for Safe Separation of UAVs for Local-area UAS Traffic Management Based on Ground Risk Map

Abstract

Recently the small unmanned aircraft systems (UAS) are widely used in various applications and consequently there is an increasing demand for airspace utilization of UASs. To support safe operation of multiple UAS operationsin the national airspace, many countries are developing UAS traffic management (UTM) system for their airspace management. In South Korea, the prototype of UTM system for small UAS operation under 150m is studied since April 2017. The local area based demonstrationwill be conducted until 2022. It is anticipated that the UAS traffic management will be conducted mainly by each local area because of the limited performance, for example battery capacity, and characteristics of application area of small UAVs. Based on this concept of UAS operation, this paper studied the navigation performance requirement for safe separation of UAVs in the interested local area based on the ground risk map of that region. Ground risk is atwo-dimensional location-based map that quantifies the risk to the population on the ground of flight operations over a specified area [1]. If the UAV want to fly over the region having high ground risk, the improved performance of the UAV is required to conducttheir mission to ensure the safety of the people on the ground [2, 3, 4]. In the previous study related to ground risk map, Primatesta suggested the ground risk map generation method for the UAV operation based on the population density on the ground [1]. Considering the safe separation distance of UAVs, the UAVs could be fall to the ground if the UAVs in the interested region can’t satisfy the required separation distance and conflict with eachother. And the safe separation distance could be the function of the target level of safety, ground risk of the region, navigation system error (NSE), flight technical error (FTE), etc. In the previous study related to safe separation distance, Kim derivethe safe separation distance considering Local-Area Differential GNSS (LADGNSS) based on NSE from LADGNSS and FTE calculated from flight experiment [5]. In this study, ground risk based required navigation performance for multiple UAV operations in the local area is studied. Firstly, we develop the ground risk map of interested area by using population density database,and car traffic database considering ballistic fall of two conflicted UAVs. In the previous study [1], they only consider the population density on the ground. However, the risk of the personnel inside the car on the road caused by UAV crash can’tbe negligible. So, in this study the ground risk map is generated both considering population density and car traffic. Secondly, we derive the probability of collision given the safe separation distance, the Reich model is used for the derivation as shownin the previous study [6]. According to the previous study [6], the probability of collision given the safe separation distance is affected by the separation distance, NSE, FTE, air traffic of UAVs, relative velocity of UAVs, etc. Finally, by combining theresults of ground risk map and the probability of collision given the safe separation distance, we can derive the required navigation performance of UAVs in the interested local area ensuring the target level of safety. In this study, the FTE is modeled byusing the experimental data of drones. And the velocity of UAVs are assumed by using characteristics of commercial drones. Also, we conduct the sensitivity analysis by using the derived formulation. As a result, in this study we propose the methodology to calculate the required navigation performance for safe operation of multiple UAVs in the local area especially considering traffic management of UAS. [1] Primatesta, Stefano, Alessandro Rizzo, and Anders la Cour-Harbo. "Ground risk map for unmanned aircraft in urban environments." Journal of Intelligent & Robotic Systems (2019): 1-21. [2] JARUS, "JARUS Guidelines on Specific Operations Risk Assessment (SORA)", edition 2.0, (2019). [3] EASA, "UAS ATM Airspace Assessment", edition 1.2, (2018). [4] ASTN International, "Standard Practice for Operational Risk Assessment of Small Unmanned Aircraft Systems (sUAS)", (2017). [5] Kim, Minchan, et al. "High integrity GNSS navigation and safe separation distance to support local-area UAV networks." ION GNSS 2014. Institute of Navigation (ION), 2014. [6] Hong, Giseon. "Safe Separation Distance Determination for Unmanned Aerial System Traffic Management", Master Thesis, KAIST, (2019).