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Derivation of representative air traffic peaks as standard input for airport related simulation

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  • Öttl, Gerald
  • Böck, Philipp
  • Werpup, Nadja
  • Schwarze, Malte

Abstract

The high diversity in air traffic situations at airports worldwide complicates the selection of an appropriate set of operational cases for a general technology and procedure evaluation in airport related simulation. In this research, representative airport peak hour traffic situations are determined. Flight data from multiple airports is analyzed and traffic peaks are automatically detected and parameterized, taking into account arrival and departure movement shares for ten aircraft weight groups. A subsequent clustering process results in an optimal number of 16 characteristic peak types. These are representative peaks that provide a limited set of typical peak traffic situations of relevance for a large number of airports worldwide, which can be directly used as input for air traffic simulation, providing standardized traffic situations to ensure comparability and clarity.

Suggested Citation

  • Öttl, Gerald & Böck, Philipp & Werpup, Nadja & Schwarze, Malte, 2013. "Derivation of representative air traffic peaks as standard input for airport related simulation," Journal of Air Transport Management, Elsevier, vol. 28(C), pages 31-39.
    • Handle: RePEc:eee:jaitra:v:28:y:2013:i:c:p:31-39
    DOI: 10.1016/j.jairtraman.2012.12.008
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    References listed on IDEAS

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    Cited by:

    1. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    2. Huang, PoTsang B. & Yu, Tsung-Ying & Chou, Yuan-ju & Lin, Yi-Ching, 2016. "Simulation method for dispatching national border security manpower to mitigate manpower shortage," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 43-51.
    3. Arnaldo Scarpel, Rodrigo & Pelicioni, Luciele Cristina, 2018. "A data analytics approach for anticipating congested days at the São Paulo International Airport," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 1-10.

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