Aircraft Cruise Alternative Trajectories Generation

A Mixed RRG-Clustering Approach

Conference Paper (2024)
Authors

J. Lebegue (Ecole Nationale de L’Aviation Civile, Sopra Steria)

Andréas Guitart (Ecole Nationale de L’Aviation Civile)

Céline Demouge (Ecole Nationale de L’Aviation Civile)

Daniel Delahaye (Ecole Nationale de L’Aviation Civile)

J. Hoekstra (TU Delft - Control & Simulation)

Eric Feron (King Abdullah University of Science and Technology)

Research Group
Control & Simulation
Copyright
© 2024 J. Lebègue, Andréas Guitart, Céline Demouge, Daniel Delahaye, J.M. Hoekstra, Eric Feron
To reference this document use:
https://doi.org/10.1007/978-3-031-49379-9_2
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 J. Lebègue, Andréas Guitart, Céline Demouge, Daniel Delahaye, J.M. Hoekstra, Eric Feron
Research Group
Control & Simulation
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Pages (from-to)
34-50
ISBN (print)
9783031493782
DOI:
https://doi.org/10.1007/978-3-031-49379-9_2
Reuse Rights

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Abstract

Weather obstacles in the airspace can interfere with an aircraft’s flight plan. Pilots, assisted by air traffic controllers (ATCs), perform avoidance maneuvers that can be optimized. This paper addresses the generation of alternative aircraft trajectories to resolve unexpected events. The authors propose a solution based on the RRG algorithm, K-means clustering, and Dynamic Time Warping (DTW) similarity metric to address the problem. The mixed algorithm succeeds in generating a set of paths with diversity in an obstacle constrained airspace between Paris-Toulouse and London-Toulouse airports. This tool could help to reduce the workload of pilots and ATCs when such a situation arises.

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