Description: NASA researchers have been studying ground-based conflict detection and resolution for at least ten years. Under the tool proposed herein, these researchers will be able to evaluate both the performance impact and the environmental impact. The environmental impact is important for obtaining approval to move the ground-based conflict detection and resolutions algorithms to higher Technology Readiness Levels (TRLs). Besides helping advance the AAC and tAAC algorithms, NASA researchers can experiment with autonomous operations in the NAS under a variety of different traffic loads (including UAS traffic), weather patterns, and even degrees of autonomy—from full autonomy to autonomous operations that are restricted to certain classes of airspace (such as class A). Insights gained by these experiments in the virtual world will help the community understand the benefits—and potential limits—of future autonomous operations in the NAS. Some of the research questions that can be answered by such a tool include the following. To what extent does the noise footprint of an automated separation assurance algorithm hinder its acceptance by the public? To what extent is fuel burn reduced by using automated separation assurance? How great a flight density can an automated separation assurance function allow? Under what conditions might an automated separation assurance algorithm require manual intervention?

Benefits: Aviation consultants, the FAA itself, and other professionals can use this tool to gain a better understanding of the role of autonomous operations in the NAS. Suppose, for example, a UAS manufacturer is considering a particular autonomous algorithm that they want to include in their design. Using this tool, the manufacturer can determine whether the vehicle will fly correctly in the presence of a future autonomous NAS, and therefore whether the investment in building the aircraft will yield a positive net return. The FAA can use this tool to become acquainted with a partially or fully autonomous NAS operation, to determine to what extent autonomy should be introduced, and on what timetable and what the expected benefits will be. This information is important for producing an autonomy roadmap that will allow FAA program managers to specify the steps, and timetable, needed to further transform the NAS.

Air Transportation and Safety, Analytical Methods, Algorithms/Control Software and Systems, Simulation and Modeling