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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.

Suggested Citation

  • 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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    Cited by:

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    3. 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).
    4. Bombelli, Alessandro & Sallan, Jose Maria, 2023. "Analysis of the effect of extreme weather on the US domestic air network. A delay and cancellation propagation network approach," Journal of Transport Geography, Elsevier, vol. 107(C).
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    6. 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.
    7. 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.
    8. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    9. 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).
    10. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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