Exploitation of Machine Learning to predict airport Runway Utilisation relative to known precursors and abnormality

Doctoral Thesis (2020)
Author(s)

Floris Herrema (TU Delft - Air Transport & Operations)

Contributor(s)

R. Curran – Promotor (TU Delft - Air Transport & Operations)

Bruno Filipe F Santos – Copromotor (TU Delft - Air Transport & Operations)

Research Group
Air Transport & Operations
Copyright
© 2020 Floris Friso Herrema
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Publication Year
2020
Language
English
Copyright
© 2020 Floris Friso Herrema
Research Group
Air Transport & Operations
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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.

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