Statistical characterization of airplane delays

Abstract The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airlin...

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Autores principales:	Evangelos Mitsokapas, Benjamin Schäfer, Rosemary J. Harris, Christian Beck
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6a33f71cd1fa4df48cbde85505fc5b40
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spelling	oai:doaj.org-article:6a33f71cd1fa4df48cbde85505fc5b402021-12-02T15:51:13ZStatistical characterization of airplane delays10.1038/s41598-021-87279-82045-2322https://doaj.org/article/6a33f71cd1fa4df48cbde85505fc5b402021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87279-8https://doaj.org/toc/2045-2322Abstract The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.Evangelos MitsokapasBenjamin SchäferRosemary J. HarrisChristian BeckNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Evangelos Mitsokapas Benjamin Schäfer Rosemary J. Harris Christian Beck Statistical characterization of airplane delays
description	Abstract The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.
format	article
author	Evangelos Mitsokapas Benjamin Schäfer Rosemary J. Harris Christian Beck
author_facet	Evangelos Mitsokapas Benjamin Schäfer Rosemary J. Harris Christian Beck
author_sort	Evangelos Mitsokapas
title	Statistical characterization of airplane delays
title_short	Statistical characterization of airplane delays
title_full	Statistical characterization of airplane delays
title_fullStr	Statistical characterization of airplane delays
title_full_unstemmed	Statistical characterization of airplane delays
title_sort	statistical characterization of airplane delays
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6a33f71cd1fa4df48cbde85505fc5b40
work_keys_str_mv	AT evangelosmitsokapas statisticalcharacterizationofairplanedelays AT benjaminschafer statisticalcharacterizationofairplanedelays AT rosemaryjharris statisticalcharacterizationofairplanedelays AT christianbeck statisticalcharacterizationofairplanedelays
_version_	1718385636996546560

Statistical characterization of airplane delays

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