How to Estimate Airport Taxi Time

April 26, 2024

Every day there are 5,000 to 10,000 commercial airplanes in the skies. After each flight, these airplanes land at airports, which only have limited runway space. Once airplanes finish landing, they must taxi the airport off the runway so other airplanes can take off. The taxiing process takes time, and it’s one of the leading causes of delays at airports. In the past year alone, 1.7 million extra minutes of taxiing were spent nationwide due to delays at O’Hare and other airports.

Airport surface traffic flow information can be gathered from several sources, including aircraft position data, air traffic control (ATC) radar, and ground surveillance cameras. The information gathered can be used to predict taxi times, optimize runway utilization, and improve aircraft pushback control.

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Several scholars have developed regression models to estimate surface taxi time. For example, in 2010, Gupta and colleagues used mixed-integer linear programming to generate flight routes that satisfy a specified timeline with minimum total delays and no conflicts. The resulting solution included the estimated taxi time for each section of the airport surface traffic operations network.

In addition, some scholars have applied heuristic improvements to the FAA APO method for estimating unimpeded tax-out time. For instance, in 2016, Zhao et al. replaced the number of departing aircraft on the departure queue with departure traffic characteristics to improve their model’s prediction accuracy. They also added the taxi distance to the estimation process. The results from this study showed that the model improved significantly.