Qu, Zhan und Yuan, Shuzhou und Färber, Michael und Brennfleck, Marius und Wartha, Niklas Louis und Stephan, Anton (2025) Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence. In: ACM KDD 2025, Seiten 2504-2513. ACM KDD 2025, 2025-08-03 - 2025-08-07, Toronto, Canada. doi: 10.1145/3690624.3709436. ISBN 979-8-4007-1245-6/25/08.
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Offizielle URL: https://dx.doi.org/10.1145/3690624.3709436
Kurzfassung
Wake vortices - strong, coherent air turbulences created by aircrafts-pose a significant risk to aviation safety and therefore require accurate and reliable detection methods. In this paper, we present an advanced, explainable machine learning method that utilizes Light Detection and Ranging (LiDAR) data for effective wake vortex detection. Our method leverages a dynamic graph CNN (DGCNN) with semantic segmentation to partition a 3D LiDAR point cloud into meaningful segments. Further refinement is achieved through clustering techniques. A novel feature of our research is the use of a perturbation-based explanation technique, which clarifies the model’s decision-making processes for air traffic regulators and controllers, increasing transparency and building trust. Our experimental results, based on measured and simulated LiDAR scans compared against four baseline methods, underscore the effectiveness and reliability of our approach. This combination of semantic segmentation and clustering for real-time wake vortex tracking significantly advances aviation safety measures, ensuring that these are both effective and comprehensible.
elib-URL des Eintrags: | https://elib.dlr.de/215725/ | ||||||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||||||
Zusätzliche Informationen: | Funding: German Federal Ministry for Digital and Transport (mFUND project “KIWI”); Deutsches Zentrum für Luft- und Raumfahrt (Wetter und Disruptive Ereignisse). | ||||||||||||||||||||||||||||
Titel: | Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence | ||||||||||||||||||||||||||||
Autoren: |
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Datum: | 2025 | ||||||||||||||||||||||||||||
Erschienen in: | ACM KDD 2025 | ||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||||||
DOI: | 10.1145/3690624.3709436 | ||||||||||||||||||||||||||||
Seitenbereich: | Seiten 2504-2513 | ||||||||||||||||||||||||||||
ISBN: | 979-8-4007-1245-6/25/08 | ||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||
Stichwörter: | Wake Vortex Detection, LiDAR scan, 3D Point Cloud Segmentation, Explainability | ||||||||||||||||||||||||||||
Veranstaltungstitel: | ACM KDD 2025 | ||||||||||||||||||||||||||||
Veranstaltungsort: | Toronto, Canada | ||||||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||||||
Veranstaltungsbeginn: | 3 August 2025 | ||||||||||||||||||||||||||||
Veranstaltungsende: | 7 August 2025 | ||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||
HGF - Programm: | Luftfahrt | ||||||||||||||||||||||||||||
HGF - Programmthema: | Luftverkehr und Auswirkungen | ||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Luftfahrt | ||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | L AI - Luftverkehr und Auswirkungen | ||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | L - Klima, Wetter und Umwelt | ||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Physik der Atmosphäre > Angewandte Meteorologie | ||||||||||||||||||||||||||||
Hinterlegt von: | Wartha, Niklas Louis | ||||||||||||||||||||||||||||
Hinterlegt am: | 11 Aug 2025 07:23 | ||||||||||||||||||||||||||||
Letzte Änderung: | 11 Aug 2025 07:23 |
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