FlightAware has developed a means to provide accurately predicted taxi times that account for real-time variables such as stand/gate position, schedules, and anticipated arrival and departure rates. Folded into FlightAware Foresight, the Taxi-Out Duration feature addresses the issue of inaccurately predicted taxi times by using real-time factors through machine learning models, the flight-tracking specialist said.  

Traditionally, aircraft taxi times have not been well modeled because they rely on historical data and generic estimates. But using more accurate taxi time predictions can improve operational efficiency and increase sustainability, according to FlightAware.

Taxi-Out Duration can provide information at most airports, calculating the latest airline-reported gates and off-block estimates, aircraft type, time of day, transponder codes, airport position, schedules, and recent traffic rates.

Predictions begin hours before aircraft departures, helping crews better meet takeoff time commitments, as well as air traffic control slot times, FlightAware said. In addition, it helps crews identify when single-engine taxi procedures would be optimal for more sustainable operations.

“Taxi-Out Duration predictions are continually updated and provide significantly more accuracy in challenging dynamic conditions than anything else currently available, allowing operators to make smarter taxi decisions and reduce cost,” explained FlightAware president James Sulak.