# Method to Characterize Potential UAS Encounters Using Open Source Data
## 5 Conclusions  
We demonstrated an analytical method to characterize potential UAS encounters. By characterizing encounters, we can develop and evaluate systems that mitigate airborne collision risk. These system could be obstacle aware, like ACAS sXu [10], such that when maneuvering to avoid another aircraft, the system will attempt to not inadvertently maneuver into an obstacle. Representing obstacles as part of the simulation would be beneficial for system development, evaluation and deployment. The systems could also be cooperative in that aircraft exchange information via an airborne vehicle to vehicle link; and this link would need to be considered as part of DAA Monte Carlo simulations. However, ASTM [9; 19] nor RTCA have published standards that provide requirements on how to represent obstacles or performance requirements on a V2V system, as part of a DAA system for smaller UAS. These DAA capabilities are currently being drafted and developed by the standards developing organizations and civil aviation authorities. The presented research supports these standard activities by determining which obstacles should be prioritized for inclusion in DAA simulations; assessing if specific encounter scenarios are suitable to assess a given V2V technology; and characterizing encounter scenarios that are likely rare, regardless of UAS flight hours. For example, wind turbines were consistently many miles away from the other features. Except for when considering FAA obstacles and wind turbines, the 5 th percentile distance between a wind turbine and another feature was at least three nautical miles. In comparison, the 25 th percentile distance between electrical power transmission lines and other features was less than one nautical mile. Since wind turbines are often much farther away from other features, it is less likely that any potential encounter between smaller UAS would occur near a wind turbine, whereas, simply due to the geospatial distribution of features, encounters are more likely to occur near electrical power transmission lines. This example suggests that there is a greater need to represent electrical power lines in DAA simulations than wind turbines. Additionally, if an obstacle database was stored onboard a UAS and given a specific concept of operations, storing locations of wind turbines may not be an efficient use of limited storage resources. Likewise, the results can inform if a given V2V link would support different encounter scenarios. While there are many other factors when characterizing a V2V link, such probability of reception, update rate, available spectrum, and transit power, we can illustrate how the presented results can be leveraged with respect to expected transmit range. Specifically, the ASTM RemoteID standard [9] discusses that Bluetooth 4 would have a range of about 1300 feet or less in a rural environment, Bluetooth 5 Long Range could have a range of 3280 feet or less, and Wi-Fi Aware could have a range of 6561 feet or less. Given that wind turbines are often miles away from other features, regardless of flight hours, the results suggest that a UAS, with a DAA communication range of one nautical mile, inspecting a wind turbine would often not be within range to communicate with other UASs. Accordingly, wind turbine inspections may not be a good use case to drive development of a V2V link for DAA. Conversely, since electric power lines are often closer to other potential UAS operations, a V2V link with a maximum transmit range of one nautical mile maybe enough. These example analyses are potential future contributions to the aviation safety community and are enabled by our research to quantitatively define a close encounter between UASs. Once UAS operations become more routine or concepts of operations are better established, this research could be extended to consider the frequency of specific encounter scenarios.