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

Doctoral thesis (2020)

Authors

Floris Friso Herrema Air Transport & Operations - Aerospace Engineering
Research Group
Air Transport & Operations (Aerospace Engineering) (TU Delft)
Copyright: © 2020 Floris Friso Herrema
DOI: https://doi.org/10.4233/uuid:e96d5b2c-f0ce-4cbe-b1c4-bf5c408ad546
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Published Date

2020

Language

English

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Faculty

Aerospace Engineering

Department

Control & Operations

Research Group

Air Transport & Operations

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.