Universal patterns in passenger flight departure delays

Departure delays are a major cause of economic loss and inefficiency in the growing industry of passenger flights. A departure delay of a current flight is inevitably affected by the late arrival of the flight immediately preceding it with the same aircraft. We seek to understand the mechanisms of s...

Full description

Saved in:
Bibliographic Details
Main Authors: Wang, Yanjun, Cao, Yakun, Zhu, Chenping, Wu, Fan, Hu, Minghua, Duong, Vu, Watkins, Michael, Barzel, Baruch, Stanley, H. Eugene
Other Authors: Air Traffic Management Research Institute
Format: Article
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10356/146108
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-146108
record_format dspace
spelling sg-ntu-dr.10356-1461082021-01-30T20:10:26Z Universal patterns in passenger flight departure delays Wang, Yanjun Cao, Yakun Zhu, Chenping Wu, Fan Hu, Minghua Duong, Vu Watkins, Michael Barzel, Baruch Stanley, H. Eugene Air Traffic Management Research Institute Engineering::Civil engineering Civil Engineering Statistical Physics, Thermodynamics and Nonlinear Dynamics Departure delays are a major cause of economic loss and inefficiency in the growing industry of passenger flights. A departure delay of a current flight is inevitably affected by the late arrival of the flight immediately preceding it with the same aircraft. We seek to understand the mechanisms of such propagated delays, and to obtain universal metrics by which to evaluate an airline’s operational effectiveness in delay alleviation. Here we use big data collected by the American Bureau of Transportation Statistics to design models of flight delays. Offering two dynamic models of delay propagation, we divided all carriers into two groups exhibiting a shifted power law or an exponentially truncated shifted power law delay distribution, revealing two universal delay propagation classes. Three model parameters, extracted directly from dual data mining, help characterize each airline’s operational efficiency in delay mitigation. Therefore, our modeling framework provides the crucially lacking evaluation indicators for airlines, potentially contributing to the mitigation of future departure delays. Published version 2021-01-26T09:06:28Z 2021-01-26T09:06:28Z 2020 Journal Article Wang, Y., Cao, Y., Zhu, C., Wu, F., Hu, M., Duong, V., . . . Stanley, H. E. (2020). Universal patterns in passenger flight departure delays. Scientific Reports, 10(1), 6890-. doi:10.1038/s41598-020-62871-6 2045-2322 0000-0001-8862-4384 https://hdl.handle.net/10356/146108 10.1038/s41598-020-62871-6 32327671 2-s2.0-85083858791 1 10 en Scientific Reports © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Civil Engineering
Statistical Physics, Thermodynamics and Nonlinear Dynamics
spellingShingle Engineering::Civil engineering
Civil Engineering
Statistical Physics, Thermodynamics and Nonlinear Dynamics
Wang, Yanjun
Cao, Yakun
Zhu, Chenping
Wu, Fan
Hu, Minghua
Duong, Vu
Watkins, Michael
Barzel, Baruch
Stanley, H. Eugene
Universal patterns in passenger flight departure delays
description Departure delays are a major cause of economic loss and inefficiency in the growing industry of passenger flights. A departure delay of a current flight is inevitably affected by the late arrival of the flight immediately preceding it with the same aircraft. We seek to understand the mechanisms of such propagated delays, and to obtain universal metrics by which to evaluate an airline’s operational effectiveness in delay alleviation. Here we use big data collected by the American Bureau of Transportation Statistics to design models of flight delays. Offering two dynamic models of delay propagation, we divided all carriers into two groups exhibiting a shifted power law or an exponentially truncated shifted power law delay distribution, revealing two universal delay propagation classes. Three model parameters, extracted directly from dual data mining, help characterize each airline’s operational efficiency in delay mitigation. Therefore, our modeling framework provides the crucially lacking evaluation indicators for airlines, potentially contributing to the mitigation of future departure delays.
author2 Air Traffic Management Research Institute
author_facet Air Traffic Management Research Institute
Wang, Yanjun
Cao, Yakun
Zhu, Chenping
Wu, Fan
Hu, Minghua
Duong, Vu
Watkins, Michael
Barzel, Baruch
Stanley, H. Eugene
format Article
author Wang, Yanjun
Cao, Yakun
Zhu, Chenping
Wu, Fan
Hu, Minghua
Duong, Vu
Watkins, Michael
Barzel, Baruch
Stanley, H. Eugene
author_sort Wang, Yanjun
title Universal patterns in passenger flight departure delays
title_short Universal patterns in passenger flight departure delays
title_full Universal patterns in passenger flight departure delays
title_fullStr Universal patterns in passenger flight departure delays
title_full_unstemmed Universal patterns in passenger flight departure delays
title_sort universal patterns in passenger flight departure delays
publishDate 2021
url https://hdl.handle.net/10356/146108
_version_ 1692012947889455104