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Optimal aircraft arrival scheduling with continuous descent operations in busy terminal maneuvering areas

Author

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  • Gui, Dongdong
  • Le, Meilong
  • Huang, Zhouchun
  • Zhang, Junfeng
  • D’Ariano, Andrea

Abstract

Continuous Descent Operation (CDO), an aircraft arrival procedure in which an aircraft descends from an optimal position with minimum engine thrust, can significantly reduce aircraft noise, fuel burn and emissions. The implementation of CDOs, however, requires more separation buffers among flights than traditional stepwise descents, resulting in loss of airspace and runway capacity. It is therefore challenging to maximize the number of aircraft performing CDOs for an airport, especially in busy terminal maneuvering areas. In this paper, we tackle the difficulty by developing an aircraft arrival scheduling model to sequence arrival aircraft before their merge point and generate conflict-free trajectories by means of a lateral path stretching method. The contributions of our study to the research community are twofold: firstly, we investigate a new aircraft arrival scheduling problem that incorporates both the CDO trajectory optimization and aircraft scheduling, and develop the first model simultaneously considering these two procedures; secondly, we conduct extensive computational experiments based on historical data in Guangzhou Baiyun International Airport, which would provide an important reference for future research in the area. Our numerical results demonstrate the benefit of the proposed CDO-based aircraft arrival scheduling approach in terms of reducing total flight time and saving fuel consumption when applied in this congested airport.

Suggested Citation

  • Gui, Dongdong & Le, Meilong & Huang, Zhouchun & Zhang, Junfeng & D’Ariano, Andrea, 2023. "Optimal aircraft arrival scheduling with continuous descent operations in busy terminal maneuvering areas," Journal of Air Transport Management, Elsevier, vol. 107(C).
  • Handle: RePEc:eee:jaitra:v:107:y:2023:i:c:s0969699722001636
    DOI: 10.1016/j.jairtraman.2022.102344
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    References listed on IDEAS

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