日本国内航空运输网络的延误传播模式

Kashin Sugishita, Kazuki Arisawa, Shinya Hanaoka
{"title":"日本国内航空运输网络的延误传播模式","authors":"Kashin Sugishita,&nbsp;Kazuki Arisawa,&nbsp;Shinya Hanaoka","doi":"10.1016/j.trip.2024.101235","DOIUrl":null,"url":null,"abstract":"<div><div>We experience air traffic delays every day, but are there any recurrent patterns in these delays? In this study, we investigate the recurrence of delay propagation patterns in Japan’s domestic air transport network in 2019 by integrating delay causality networks and temporal network analysis. Additionally, we examine characteristics unique to delay propagation by comparing delay causality networks with corresponding randomized networks generated by a directed configuration model. As a result, we found that the structure of the delay propagation patterns can be classified into several groups. The identified groups exhibit statistically significant differences in total delay time and average out-degree, with different airports playing central roles in spreading delays. The results also suggest that some delay propagation patterns are particularly prominent during specific times of the year, which could be influenced by Japan’s seasonal and geographical factors. Moreover, we discovered that specific network motifs appear significantly more (or less) frequently in delay causality networks than their corresponding randomized counterparts. This characteristic is particularly pronounced in groups with more significant delays. These results suggest that delays propagate following specific directional patterns, which could significantly contribute to predicting air traffic delays. We expect the present study to trigger further research on recurrent and non-recurrent natures of air traffic delay propagation.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"27 ","pages":"Article 101235"},"PeriodicalIF":3.9000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Delay propagation patterns in Japan’s domestic air transport network\",\"authors\":\"Kashin Sugishita,&nbsp;Kazuki Arisawa,&nbsp;Shinya Hanaoka\",\"doi\":\"10.1016/j.trip.2024.101235\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We experience air traffic delays every day, but are there any recurrent patterns in these delays? In this study, we investigate the recurrence of delay propagation patterns in Japan’s domestic air transport network in 2019 by integrating delay causality networks and temporal network analysis. Additionally, we examine characteristics unique to delay propagation by comparing delay causality networks with corresponding randomized networks generated by a directed configuration model. As a result, we found that the structure of the delay propagation patterns can be classified into several groups. The identified groups exhibit statistically significant differences in total delay time and average out-degree, with different airports playing central roles in spreading delays. The results also suggest that some delay propagation patterns are particularly prominent during specific times of the year, which could be influenced by Japan’s seasonal and geographical factors. Moreover, we discovered that specific network motifs appear significantly more (or less) frequently in delay causality networks than their corresponding randomized counterparts. This characteristic is particularly pronounced in groups with more significant delays. These results suggest that delays propagate following specific directional patterns, which could significantly contribute to predicting air traffic delays. We expect the present study to trigger further research on recurrent and non-recurrent natures of air traffic delay propagation.</div></div>\",\"PeriodicalId\":36621,\"journal\":{\"name\":\"Transportation Research Interdisciplinary Perspectives\",\"volume\":\"27 \",\"pages\":\"Article 101235\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Interdisciplinary Perspectives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590198224002215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Interdisciplinary Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590198224002215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0

摘要

我们每天都会遇到空中交通延误,但这些延误是否有重复发生的规律?在本研究中,我们通过整合延迟因果关系网络和时间网络分析,研究了 2019 年日本国内航空运输网络延迟传播模式的反复性。此外,我们还通过比较延迟因果网络和有向配置模型生成的相应随机网络,研究了延迟传播的独特特征。结果,我们发现延迟传播模式的结构可分为几组。这些组在总延迟时间和平均外度方面存在显著的统计学差异,不同的机场在延迟传播中发挥着核心作用。研究结果还表明,一些延误传播模式在一年中的特定时段尤为突出,这可能受到日本季节和地理因素的影响。此外,我们还发现,在延误因果关系网络中,特定网络主题出现的频率明显高于(或低于)其相应的随机对应物。这一特征在延迟较严重的组中尤为明显。这些结果表明,延误是按照特定的方向模式传播的,这对预测空中交通延误有很大帮助。我们希望本研究能引发对空中交通延误传播的经常性和非经常性的进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Delay propagation patterns in Japan’s domestic air transport network
We experience air traffic delays every day, but are there any recurrent patterns in these delays? In this study, we investigate the recurrence of delay propagation patterns in Japan’s domestic air transport network in 2019 by integrating delay causality networks and temporal network analysis. Additionally, we examine characteristics unique to delay propagation by comparing delay causality networks with corresponding randomized networks generated by a directed configuration model. As a result, we found that the structure of the delay propagation patterns can be classified into several groups. The identified groups exhibit statistically significant differences in total delay time and average out-degree, with different airports playing central roles in spreading delays. The results also suggest that some delay propagation patterns are particularly prominent during specific times of the year, which could be influenced by Japan’s seasonal and geographical factors. Moreover, we discovered that specific network motifs appear significantly more (or less) frequently in delay causality networks than their corresponding randomized counterparts. This characteristic is particularly pronounced in groups with more significant delays. These results suggest that delays propagate following specific directional patterns, which could significantly contribute to predicting air traffic delays. We expect the present study to trigger further research on recurrent and non-recurrent natures of air traffic delay propagation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
期刊最新文献
Electric mobility investment in the power and transport sector coupling context: Lessons from Argentina, the Philippines, Poland and Romania Comparative Analysis of barriers to Battery electric vehicle adoption between BEV and ICE Users: A case study of Thailand Disparities in ridehailing travel times for accessing non-work destinations Optimal bus reassignment considering in-vehicle overcrowding Drones for automated parcel delivery: Use case identification and derivation of technical requirements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1