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NASA NTRS · 20140008654

Using Historical Data to Automatically Identify Air-Traffic Control Behavior

Lauderdale, Todd A.·Wu, Yuefeng·Tretto, Celeste
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Abstract

This project seeks to develop statistical-based machine learning models to characterize the types of errors present when using current systems to predict future aircraft states. These models will be data-driven - based on large quantities of historical data. Once these models are developed, they will be used to infer situations in the historical data where an air-traffic controller intervened on an aircraft's route, even when there is no direct recording of this action.

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trajectory generationair traffic controldata mining

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BibTeXRIS

Lauderdale, Todd A., Wu, Yuefeng, Tretto, Celeste. 2014-02-25. Using Historical Data to Automatically Identify Air-Traffic Control Behavior. https://ntrs.nasa.gov/citations/20140008654

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