41 This is creating a complex system with many engineering tradeoffs, and not just for the delivery of UAVs. The coming rollout of autonomous electric vertical take-off and landing (eVTOL) ‘air taxi’ platforms will require the UTM systems to integrate with traditional air traffic control (ATC) systems, and run vertiports where the eVTOLs can land and charge. Data gathering Beyond, a programme by the US Federal Aviation Administration (FAA), has been running for the last four years and is due to finish in October. It is focused on working towards operating under established rules rather than waivers, gathering data to develop performance-based standards, collecting and addressing community feedback and streamlining the approval processes for UAVs with UTM systems. This will face even more challenges in future as artificial intelligence (AI) and machine learning (ML) are increasingly integrated into UTM systems. The US aeronautics agency, NASA, has been at the forefront of developments of UTM projects that take data from multiple sources to build a real-time airspace picture, coupled with collision avoidance technologies on the UAV and on the ground. This is key to detecting non-cooperative aircraft that might enter the airspace. One of the key sensors is a network of on-the-ground radar systems that provides data on the sky several times a second. These can be fixed or portable, backpack-type sensors, and new ones can be added into the network. This information is combined with data from sensors on the UAV, which can include ADS-B transceivers and airborne radars on larger UAVs, plus any communications data with the GPS position and input from the inertial measurement system via the autopilot. All of this is used to create an airspace visualisation that runs on a laptop, a secure server or a server in the cloud. One key innovation is to limit the number of real-time sensors required, such as using just two radar sensors, an ADS-B transceiver or a remote ID broadcast in the latest ACAS-X system from a crewed aircraft (mentioned below). Data from the airspace can be used to create autopilot waypoints, if allowed, to reroute a UAV around an exclusion area that appears for a blue light mission, for example. Collision countering Avoiding a collision is usually achieved by changing the altitude of the UAV, either up or down. The UTM can monitor an intruder, and predict its trajectory and intersection with a UAV. An instruction to descend can be sent to the operator, or it can generate a waypoint that can be sent to the autopilot to override the Uncrewed Systems Technology | August/September 2024 NASA has been at the heart of the development of UAS Traffic Management systems in the US (Image courtesy of NASA) Airspace allocations in the US (Image courtesy of FAA) Uncrewed Aircraft System Traffic Management | Technology focus
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