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Robust Analytics awarded three new NASA research contracts!


Our Flight and Airport-Airspace Monitor (FAAM) will provide airline dispatchers and airline operations center managers a real-time tool to estimate the safety margin of a terminal airspace and flights operating in that airspace. Our concept divides the safety monitoring architecture into two components: an Airspace/Airport Monitoring component, and a Flight Monitoring system. The Airspace Monitor combines data on weather, infrastructure state, traffic density, and aircraft positions and planned trajectories with predictive analytics on aircraft separations and conflict rates to infer the (hidden) risk state of the airspace. The Flight Monitor uses airline and aircraft-based data to evaluate potential aircraft risks from equipment state and certification, and the potential for pilot fatigue based on elapsed crew duty time and time of day. Our architecture can readily add real-time crew monitoring in future instantiations.


Trajectory-based operations (TBO) offer a major change in air traffic management with the potential for substantial performance and safety benefits. Considering the scope of the changes, TBO concepts must pass stringent hurdles for demonstrating technical feasibility, operational benefits, and safety. A successful TBO concept should provide benefits in the near term by using existing airline and FAA systems, while offering the pathway to greatly enhanced TBO capabilities in the mid-to-far terms.

The analytical and data exchange framework proposed by Robust Analytics to develop and evaluate TBO alternatives builds from the understanding that different participants will possess superior information in selected areas. The FAA ground domain has the most complete understanding of total system traffic, weather, and constraints. Individual aircraft have superior, real-time information on flight performance capabilities, the airline operations center (AOC) acts as the information nerve center for the airline and possesses the most comprehensive understanding of the airline network and each flight’s role in that network, and is responsible for achieving the airline’s business objectives. One of the challenges for implementing TBO is facilitating the timely negotiations to determine trajectories that simultaneously meet airline business objectives and tight required time of arrival (RTA) for traffic management purposes. With multiple sources of uncertainty in flight operations, TBO concepts must be able to negotiate trajectory changes to satisfy multiple objectives while responding to uncertainties and constraints in the NAS.

For Phase I, Robust Analytics will describe a detailed TBO negotiation process and use case; develop an architecture for exchanging the required data among the AOC, aircraft, and traffic flow management to facilitate TBO negotiations; and conduct a proof of concept demonstration.


Robust Analytics proposes a suite of near-term technologies that can support managing multiple autonomous or semi-autonomous aircraft including Unmanned Aerial Systems (UAS) and Urban Air Mobility (UAM) vehicles simultaneously. Our approach builds on the existing knowledge base of airline operations, leveraging emerging technologies that enable autonomous flight.

Our approach enables monitoring of vehicles systems and data, coupled with auto-upload of dynamic flight data required to support safe and efficient flight operation (e.g., change in flight plan, evolutionary new destinations, etc.). We build on our expertise in airline dispatch and software applications for air-ground integration.

Our system adds to existing tools and software, providing an evolutionary pathway for the monitoring and control of multiple semi-autonomous and autonomous flights by a single operator. We propose and develop new functionality to accelerate this transition. Our vision aims to extend and enhance our current expertise to transition the functions of today’s airline dispatchers to future airspace and vehicle concepts.

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