Statistical characterization of airplane delays.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
12 04 2021
12 04 2021
Historique:
received:
21
12
2020
accepted:
22
03
2021
entrez:
13
4
2021
pubmed:
14
4
2021
medline:
14
4
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33846509
doi: 10.1038/s41598-021-87279-8
pii: 10.1038/s41598-021-87279-8
pmc: PMC8041857
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7855Subventions
Organisme : H2020 Marie Sklodowska-Curie Actions
ID : 840825
Références
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Nov;72(5 Pt 2):056133
pubmed: 16383714
Sci Rep. 2013;3:1159
pubmed: 23362459
Sci Rep. 2014 Jul 09;4:5638
pubmed: 25005934
Phys Rev Lett. 2014 Aug 29;113(9):098302
pubmed: 25216011
J R Soc Interface. 2021 Mar;18(176):20200927
pubmed: 33653112
Sci Rep. 2019 Dec 27;9(1):19971
pubmed: 31882778
Proc Natl Acad Sci U S A. 2005 May 31;102(22):7794-9
pubmed: 15911778
J Transp Geogr. 2020 Jun;86:102749
pubmed: 32834670