Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

Journal article (2020)

Authors

Miguel Lambelho Student
M.A. Mitici Air Transport & Operations - Aerospace Engineering
Simon Pickup London Heathrow Airport
Alan Marsden EUROCONTROL
Research Group
Air Transport & Operations (Aerospace Engineering) (TU Delft)
Copyright: © 2020 Miguel Lambelho, M.A. Mitici, Simon Pickup, Alan Marsden
DOI: https://doi.org/10.1016/j.jairtraman.2019.101737
Machine learning Cancellation prediction Delay prediction Schedule ranking Strategic flight schedule
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Published Date

2020

Language

English

Faculty

Aerospace Engineering

Department

Control & Operations

Research Group

Air Transport & Operations

Abstract

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.