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"Automated Conflict Resolution" Video Transcript

NASA is working on computer automation to improve the efficiency and capacity of the National Airspace System. The primary objectives are to save fuel and reduce delays for the users of the airspace system and to reduce workload for the air traffic controllers that ensure safe separation between all of the aircraft flying in the airspace system.

The display shows one of the busiest airspace regions in the country, with Chicago and other airports to the West and Boston, New York, Washington D.C., and Philadelphia to the East, as well as, the airports of Detroit, Cleveland, and Pittsburg in the middle of the screen.

The targets on the display show all of the commercial and general aviation traffic flying in this region at about 3:00 in the afternoon Eastern time. The green targets are arrivals to either Detroit, Cleveland, or Pittsburgh. The blue targets are departures from those airports and the white targets are everything else, many of them setting up for approach and landing at the busy East coast airports.

At the heart of the NASA system is the ability to predict an accurate flight trajectory for all aircraft 20 minutes or more into the future. Four key pieces of information are combined in order to generate a four-dimensional flight trajectory for all aircraft in the sky. Position and velocity information from radar or GPS, filed flight plan information and flight plan updates, wind information from the National Weather Service, and a database of aircraft performance models.

For example, the fuel-efficient descent trajectory for Southwest 199 approaching Cleveland is shown on the display. The flight trajectory for the aircraft departing Cleveland bound for New York's JFK is also shown.

Flight trajectory predictions for all aircraft are updated every 12 seconds with fresh radar updates or whenever a new flight plan amendment is received. All trajectories are compared against one another to detect potential traffic conflicts. A traffic conflict is a condition where two aircraft are on converging trajectories and one aircraft must be vectored slightly in order to maintain safe separation. The safe separation standard is 5 miles or 1000 feet.

An air traffic controller’s primary responsibility is to ensure safe separation in the airspace using conflict detection and conflict resolution. Conflict detection and resolution happens thousands of times every day in the airspace and most passengers don’t even know that it is happening.

NASA's trajectory automation is used to automatically detect traffic conflicts 15 or 20 minutes into the future and generate resolution trajectories that resolve the conflict without generating any other conflicts. An important element of NASA's research is to use trajectory-based automation to improve the performance of conflict detection and resolution in the airspace system, and thereby increase efficiency, reduce delays, and save fuel.

The example shows two aircraft level at 32,000 feet. They are predicted to pass within four miles of one another ten minutes downstream of their current position. The automatic resolution trajectory turns the westbound aircraft about 25 degrees to the right and has him rejoin his route downstream of the conflict.

Another example shows one aircraft departing Detroit, another aircraft departing Cleveland, both predicted to lose separation during their climb. Conflict predictions involving climbing and descending aircraft are one of the most challenging due to uncertainties in aircraft performance, aircraft weight, wind, and other factors.

A wide variety of airline flight plans and desired climb, cruise, and descent trajectories results in an almost infinite combination of conflict scenarios that must be robustly and safely handled by the automation. NASA's ultimate objective is to determine that combination of trajectory based automation and human-machine operating concepts that saves fuel, reduces emissions, and is safe and robust for operations in the National Airspace System.

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Last Updated: October 13, 2016

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