As originally reported on Forbes, engineers at MIT created a model to prevent costly delays and airport congestion. As everyone knows that there are a number of factors that cause planes to get backed up on the runway–weather, runway traffic, landing and departure schedules. But with the use of this prediction model air traffic controllers could direct departures to minimize runway congestion by predicting each plane’s takeoff time given the existing parameters. In the event that a plane would be projected to sit on the runway for an extended period of time, the controller could instead have the plane remain at the gate. In the case of a 30 to 40 minute delay, this could save up to 20 gallons of fuel per plane, which when considering the high volume of air traffic—is a significant number.
The MIT team, led by Hamsa Balakrishnan, developed the equation model to predict taxiing time and used FAA data from 2011 at Newark’s Liberty International Airport to adjust the model. The FAA’s database includes pushback and takeoff times for every flight departing the nation’s major airports along with runway configurations and local weather conditions. The model has been shown to work quite well, predicting the lengths of runway queues within two aircraft, plus or minus.
This would give air traffic controllers the ability to get accurate predictions of what happens to runway traffic, depending on which actions they would like to take. If continuous gate pushback doesn’t cause problems, then they may feel free to do so, but if it does lead to delays they can hold some planes at their gates to avoid congestion.
The model has also been tested at other airports, such as Boston’s Logan Airport, NYC’s LaGuardia, and Charlotte, NC’s Douglas Airport. The preliminary results suggest that the model will be relatively easy to implement in new locations.
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