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Exploring Supervised Learning to Predict Air Traffic Delay in ATM Network Resiliency

Sanaei, Rasoul (2019) Exploring Supervised Learning to Predict Air Traffic Delay in ATM Network Resiliency. WAW Machine Learning 5, 03-05. Dec. 2019, Wessling, Germany.

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Abstract

Tactical Air Traffic Flow Management (ATFM) highly relies on situational awareness at European ATM Network (EATMN). The study is establishing the link between ATFM and system resiliency. A basic model for EATMN with the purpose of understanding network resiliency is described. Also the data flow and key role of Large-scale capacity regulations (also known as ATFCM regulations) as a feedback loop is demonstrated. Then the complexity of EATMN and available data is reviewed to declare the advantages of Machine Learning (ML) to predict Network delay. additionally the literature on ML approaches in delay prediction is addressed to explain the contribution of our methodology. Furthermore the study explores different ML classes in a two step approach. First the applicability of ML for delay prediction is checked and secondly, in search of a baseline for prediction quality, different supervised learning methods are applied.

Item URL in elib:https://elib.dlr.de/132762/
Document Type:Conference or Workshop Item (Speech)
Title:Exploring Supervised Learning to Predict Air Traffic Delay in ATM Network Resiliency
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sanaei, RasoulRasoul.Sanaei (at) dlr.deUNSPECIFIED
Date:5 December 2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:ATFM, Resilience, Supervised Learning, Delay Prediction
Event Title:WAW Machine Learning 5
Event Location:Wessling, Germany
Event Type:Workshop
Event Dates:03-05. Dec. 2019
Organizer:Deutsche Zentrum für Luft- und Raumfahrt (DLR)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Air Traffic Concepts and Operation
Location: Hamburg
Institutes and Institutions:Air Transport Operations > Air Transport Infrastructures & Processes
Deposited By: Sanaei, Rasoul
Deposited On:09 Jan 2020 08:52
Last Modified:09 Jan 2020 08:52

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