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A combined statistical approach and ground movement model for improving taxi time estimations at airports

Author

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  • S Ravizza

    (University of Nottingham, Jubilee Campus, Nottingham, UK)

  • J A D Atkin

    (University of Nottingham, Jubilee Campus, Nottingham, UK)

  • M H Maathuis

    (ETH Zurich, Zurich, Switzerland)

  • E K Burke

    (University of Stirling, Cottrell Building, Stirling, UK)

Abstract

With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. Improved on-stand time predictions (for improved resource allocation at the stands) and take-off time predictions (for improved airport-airspace coordination) both require more accurate taxi time predictions, as do the increasingly sophisticated ground movement models which are being developed. Calibrating such models requires historic data showing how long aircraft will actually take to move around the airport, but recorded data usually includes significant delays due to contention between aircraft. This research was motivated by the need to both predict taxi times and to quantify and eliminate the effects of airport load from historic taxi time data, since delays and re-routing are usually explicitly considered in ground movement models. A prediction model is presented here that combines both airport layout and historic taxi time information within a multiple linear regression analysis, identifying the most relevant factors affecting the variability of taxi times for both arrivals and departures. The promising results for two different European hub airports are compared against previous results for US airports.

Suggested Citation

  • S Ravizza & J A D Atkin & M H Maathuis & E K Burke, 2013. "A combined statistical approach and ground movement model for improving taxi time estimations at airports," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(9), pages 1347-1360, September.
  • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:9:p:1347-1360
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    Cited by:

    1. Yin, Suwan & Han, Ke & Ochieng, Washington Yotto & Sanchez, Daniel Regueiro, 2022. "Joint apron-runway assignment for airport surface operations," Transportation Research Part B: Methodological, Elsevier, vol. 156(C), pages 76-100.
    2. Xinhua Zhu & Nan Li & Yu Sun & Hongfei Zhang & Kai Wang & Sang-Bing Tsai, 2018. "A Study on the Strategy for Departure Aircraft Pushback Control from the Perspective of Reducing Carbon Emissions," Energies, MDPI, vol. 11(9), pages 1-15, September.

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