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ATM network modelling, uncertainty propagation with thunderstorm disruptions

Koyuncu, Emre und Aksoy, Muhammet und Munoz, Andres und Pons, Jordi und Delahaye, Daniel und Zopp, Raimund und Kuenz, Alexander und Soler, Manuel (2022) ATM network modelling, uncertainty propagation with thunderstorm disruptions. In: 12th EASN International Conference on Innovation in Aviation and Space for opening New Horizons, EASN 2022. 12th EASN International Conference on Innovation in Aviation and Space for opening New Horizons, EASN 2022, 18.-21. Okt. 2022, Barcelona, Spanien.

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Kurzfassung

In this work, as a part of START, we have developed an ATM network macro-model, allowing us to model the propagation of flight trajectory uncertainties and further assess the impact of disruptive events, i.e., thunderstorms. We utilized data-driven analytics models mimicking the dynamics of epidemic spreading, which is analogous to delay or uncertainty propagation over transport networks. The connections between the operational aspects of the air traffic flow management and the developed meta-model are given as the airports' traffic densities correlated with the infection rates among the individuals; and the capability to absorb the uncertainties of the airports associated with recovery rates. Uncertainties over individual flight trajectories, which are the functions of flight times, have been defined through probabilistic distributions where superposed on the arrival times. Deep learning models have been integrated to capture the nonlinear relationship between the recovery rates, uncertainty accumulation, and disruptive events' attributes. The model allowed us to simulate and analyze the behavior of the network under uncertainty accumulations coming from trajectory uncertainty. Finally, we have used Reinforcement Learning to explore the best actions to enhance the network resiliency, defined through stability theory. From the operational perspective, resiliency is associated with the managing balance between the intervention rate (depending on "the time for washing away the effect of the transition period) and costs. The problem, at this point, transformed into an optimization-based control problem to guarantee convergence over time, meaning the effect of disruptive events dies out eventually. Quick recovery is typically preferred, but it applies significant intervention measures impacting many flights in this case. RL provided us with pinpointing the OD pairs, and the flights require regulatory action such as flight cancelation and aircraft grounding. The case studies are analyzed for the selected time windows chosen in the interval of 1-10 June 2018, where thunderstorms affected large areas of North-West Europe with intense local convective activities.

elib-URL des Eintrags:https://elib.dlr.de/189572/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:ATM network modelling, uncertainty propagation with thunderstorm disruptions
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Koyuncu, Emreemre.koyuncu (at) itu.edu.trNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Aksoy, Muhammetmuhammet.aksoy (at) itu.edu.trNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Munoz, Andresandres.munozhernandez (at) boeing.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Pons, Jordijordi.pons-prats (at) upc.eduNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Delahaye, Danieldelahaye (at) recherche.enac.frNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Zopp, Raimundraimund (at) flightkeys.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Kuenz, AlexanderAlexander.Kuenz (at) dlr.dehttps://orcid.org/0000-0001-5192-8894NICHT SPEZIFIZIERT
Soler, Manuelmasolera (at) ing.uc3m.esNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:19 Oktober 2022
Erschienen in:12th EASN International Conference on Innovation in Aviation and Space for opening New Horizons, EASN 2022
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:uncertainty propagation, epidemic model, machine learning
Veranstaltungstitel:12th EASN International Conference on Innovation in Aviation and Space for opening New Horizons, EASN 2022
Veranstaltungsort:Barcelona, Spanien
Veranstaltungsart:internationale Konferenz
Veranstaltungsdatum:18.-21. Okt. 2022
Veranstalter :EASN
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 - Integrierte Flugführung
Standort: Braunschweig
Institute & Einrichtungen:Institut für Flugführung > Pilotenassistenz
Hinterlegt von: Kuenz, Dr. Alexander
Hinterlegt am:10 Nov 2022 12:01
Letzte Änderung:10 Nov 2022 12:01

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