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Characterization of delay propagation in the air traffic network

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  • Li, Qiang
  • Jing, Ranzhe

Abstract

We build a delay propagation network based on Bayesian Network approach to study the complex phenomenon of delay propagation within a large network consisting of the 100 busiest airports in the United States. Through topological analysis and probability analysis, we investigate the characterization of delay propagation among airports and the impact of different types of airports on delay propagation. Results indicate that the cumulative degree distribution of the delay propagation network follows an exponential function and flight delays take at most one transhipment to go from each airport to any other airports on average. For each individual airport, the effects of delay propagation are associated with airports size (traffic flow), small airports are easily affected by other airports while large airports are more affecting downstream airports but fewer affected by upstream airports. Finally, we show how the number of affected airports changes as a function of the delayed airports based on different simulation strategies.

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  • Li, Qiang & Jing, Ranzhe, 2021. "Characterization of delay propagation in the air traffic network," Journal of Air Transport Management, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:jaitra:v:94:y:2021:i:c:s0969699721000582
    DOI: 10.1016/j.jairtraman.2021.102075
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    1. Campanelli, Bruno & Fleurquin, Pablo & Arranz, Andrés & Etxebarria, Izaro & Ciruelos, Carla & Eguíluz, Víctor M. & Ramasco, José J., 2016. "Comparing the modeling of delay propagation in the US and European air traffic networks," Journal of Air Transport Management, Elsevier, vol. 56(PA), pages 12-18.
    2. Hao, Lu & Hansen, Mark & Zhang, Yu & Post, Joseph, 2014. "New York, New York: Two ways of estimating the delay impact of New York airports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 245-260.
    3. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    4. Du, Wen-Bo & Zhang, Ming-Yuan & Zhang, Yu & Cao, Xian-Bin & Zhang, Jun, 2018. "Delay causality network in air transport systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 466-476.
    5. Abdelghany, Khaled F. & S. Shah, Sharmila & Raina, Sidhartha & Abdelghany, Ahmed F., 2004. "A model for projecting flight delays during irregular operation conditions," Journal of Air Transport Management, Elsevier, vol. 10(6), pages 385-394.
    6. Bombelli, Alessandro & Santos, Bruno F. & Tavasszy, Lóránt, 2020. "Analysis of the air cargo transport network using a complex network theory perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    7. Zanin, Massimiliano, 2015. "Can we neglect the multi-layer structure of functional networks?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 184-192.
    8. Kafle, Nabin & Zou, Bo, 2016. "Modeling flight delay propagation: A new analytical-econometric approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 520-542.
    9. Vlachos, Ilias & Lin, Zhibin, 2014. "Drivers of airline loyalty: Evidence from the business travelers in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 1-17.
    10. Wong, Jinn-Tsai & Tsai, Shy-Chang, 2012. "A survival model for flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 23(C), pages 5-11.
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    Cited by:

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    4. Tang, Zhixing & Huang, Shan & Zhu, Xinping & Pan, Weijun & Han, Songchen & Gong, Tingyu, 2023. "Research on the multilayer structure of flight delay in China air traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    5. Guo, Zhen & Hao, Mengyan & Yu, Bin & Yao, Baozhen, 2022. "Detecting delay propagation in regional air transport systems using convergent cross mapping and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    6. Chen, Shenwen & Du, Wenbo & Liu, Runran & Cao, Xianbin, 2023. "Finding spatial and temporal features of delay propagation via multi-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    7. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    8. Ziming Wang & Chaohao Liao & Xu Hang & Lishuai Li & Daniel Delahaye & Mark Hansen, 2022. "Distribution Prediction of Strategic Flight Delays via Machine Learning Methods," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    9. Hongyong Wang & Ping Xu & Fengwei Zhong, 2022. "Modeling and Feature Analysis of Air Traffic Complexity Propagation," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    10. Li, Qiang & Wu, Lu & Guan, Xinjia & Tian, Ze-jin, 2024. "Interplay of network topologies in aviation delay propagation: A complex network and machine learning analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
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