Exploitation of Machine Learning to predict airport Runway Utilisation relative to known precursors and abnormality
F.F. Herrema (TU Delft - Aerospace Engineering)
Richard Curran – Promotor (TU Delft - Aerospace Engineering)
Bruno F. Santos – Copromotor (TU Delft - Aerospace Engineering)
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Abstract
There is currently no supplementary operational system that assists the Air Traffic Control Officer (ATCO) in attaining accurate, fast, intuitive and interpretable predictions of Aircraft Safety Performance (ASP) enablers through suitable visualisation on the runway or on final approach. Thus, this study intends to develop an arrival ATCO support decision tool named the Runway Utilisation (RU) support tool.