Human Systems Integration Division @ NASA Ames

The National Aeronautics and Space Administration (NASA) 2022 Strategic Plan included the goal to catalyze economic growth and drive innovation in the aviation industry, and to address challenges in air transportation and airspace management within the National Airspace System (NAS). The Aeronautics Research Mission Directorate (ARMD) specifically was tasked with leading aviation innovation to enable safe and sustainable air transportation through revolutionary vehicle advances and efficient flight operations. As a part of meeting these objectives and advancing air mobility concepts, NASA initiated the National Campaign (NC) in the Advanced Air Mobility (AAM) Project within the Airspace Operations and Safety Program (AOSP). The NC was designed to support operational demonstrations with industry as well as needed research and development to support NASA-led research flight demonstrations.

Within the NC, the Integration of Automated Systems (IAS), an NC activity, tested and evaluated flight deck automation and airspace operations management functions needed to enable Urban Air Mobility (UAM) operations. These tests were accomplished through a partnership with Sikorsky Aircraft (specifically, Sikorsky Innovations, Stratford, Connecticut), a Lockheed Martin company, and DARPA (the Defense Advanced Research Projects Agency (DARPA), Arlington County, Virginia) by leveraging two automation-enabled helicopters equipped with unique capabilities that enabled NASA to develop and test two-ship conflict encounters to demonstrate flight path management and hazard avoidance technologies. The enabler in this testing was the NASA-developed "middleware" (MW) software (also known as Expandable Variable Autonomy Architecture (EVAA)), which, among other things, allowed multiple algorithms to be incorporated into one software build that was hosted on the dissimilar-type Sikorsky helicopters.

The IAS test campaign period of performance was from March 2022 to October 2023 and was structured as a phased (or spiral) approach that ultimately led to the first-ever demonstration of two-ship UAM/AAM operations designed to safely choreograph specific conflict encounters and mission scenarios to test the research algorithms for strategic and tactical aircraft deconfliction. Lessons learned are included in the body of the report. Data collected will be used to inform the Federal Aviation Administration (FAA) and industry standards groups on the increasingly automated systems needed for future AAM operations. The test encounters developed for these flight tests were proven to be highly predictable, repeatable, and were safely exercised for flight path planning and Detect and Avoid (DAA) algorithms. These same test encounters should be leveraged by future flight-test campaigns to verify that operational safety is not compromised as the AAM architecture matures. Next steps include repeating similar encounters using unmanned aircraft carrying DAA sensors in the National Airspace.