A Framework for Autonomous Trajectory-Based Operations

The innovation proposed is a framework for autonomous Traffic Flow Management (TFM) under Trajectory Based Operations (TBO) for Unmanned Aerial Systems (UAS). The concept, called DRIFT-UAS (Distributed Resilient Framework for Trajectory Management of Unmanned Aerial Systems), is a cloud-based system that consists of algorithms and an information-sharing framework that would enable autonomous trajectory planning and strategic deconflicting of trajectories of manned and unmanned aircraft, while optimizing system-wide objectives such as safety, efficiency, and equity. DRIFT-UAS envisions four information signals that are exchanged in a cloud-based environment. The signals are (a) trajectory intent from an aircraft to DRIFT-UAS, (b) trajectory feedback (e.g., level of congestion on the proposed route as well as nearby routes in time and space) from DRIFT-UAS to the aircraft (c) loading projections from DRIFT-UAS to NAS ATC resources, and (d) capacity signals derived from weather forecasts, dynamic airspace restrictions, or acceptable loading levels at various NAS resources. The signals are processed by a centralized MDM (Master De-conflicting Module) to generate a trajectory feedback signal, and ATGMs (Autonomous Trajectory Generation Modules) autonomously generate trajectories for aircraft based on the feedback signal. DRIFT-UAS is based on a new class of algorithms for solving large-scale TFM problems by separating TFM optimization into two problems---a master problem, equivalent to the MDM that checks for capacity violations and allocates resources to competing aircraft, and a sub-problem, equivalent to the ATGM solved by each individual aircraft that generates 4-d trajectories for each flight. The master problem exchanges dual prices that signal congestion across ATC resources to guide the sub-problems to an optimal solution.

The core application of the work in this project will be to further NASA's and the FAA's goals to enable safe and efficient Trajectory Based Operations for UASs. If successful, it is envisioned that DRIFT-UAS will provide the platform though which all aircraft (unmanned or otherwise) would strategically interact with the ATC system to signal trajectory intent and receive feedback on delays and congestion. DRIFT-UAS would also serve as a centralized repository for trajectory intent and ATC capacity. In the short to medium term, the platform could be integrated within a simulation environment such as SMART-NAS to help simulate the behavior of a large number of UAS systems to test various TBO concepts.

Outside of achieving NASA's and the FAA's goals for NextGen, DRIFT-UAS's algorithms provide a platform for similar large-scale optimization of autonomous entities in a distributed environment. Examples of such environments include robotic pickers at warehouses, in which large groups of robots autonomously perform missions in the presence of system-wide costs and capacity constraints.

This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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