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An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module....

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Detalles Bibliográficos
Autores principales: Bongiorno, Christian, Miccichè, Salvatore, Mantegna, Rosario N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395171/
https://www.ncbi.nlm.nih.gov/pubmed/28419160
http://dx.doi.org/10.1371/journal.pone.0175036
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author Bongiorno, Christian
Miccichè, Salvatore
Mantegna, Rosario N.
author_facet Bongiorno, Christian
Miccichè, Salvatore
Mantegna, Rosario N.
author_sort Bongiorno, Christian
collection PubMed
description We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.
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spelling pubmed-53951712017-05-04 An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management Bongiorno, Christian Miccichè, Salvatore Mantegna, Rosario N. PLoS One Research Article We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast. Public Library of Science 2017-04-18 /pmc/articles/PMC5395171/ /pubmed/28419160 http://dx.doi.org/10.1371/journal.pone.0175036 Text en © 2017 Bongiorno et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bongiorno, Christian
Miccichè, Salvatore
Mantegna, Rosario N.
An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title_full An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title_fullStr An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title_full_unstemmed An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title_short An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
title_sort empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395171/
https://www.ncbi.nlm.nih.gov/pubmed/28419160
http://dx.doi.org/10.1371/journal.pone.0175036
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