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2022 年度 実施状況報告書

Heterogeneous air traffic flow modeling and congestion mechanism clarification

研究課題

研究課題/領域番号 20K14855
研究機関国立研究開発法人宇宙航空研究開発機構

研究代表者

アンドレエバ森 アドリアナ  国立研究開発法人宇宙航空研究開発機構, 航空技術部門, 主任研究開発員 (30747499)

研究期間 (年度) 2020-04-01 – 2024-03-31
キーワードcellular automata / air traffic flow / model / radar data / route mapping / merge
研究実績の概要

Actual track data is used to investigate the potential of cellular automata (CA) in air traffic modeling. Flight trajectories are mapped on nominal flight routes. The cell sizes are determined based on the flight stage, with two groups- enroute and descent being modeled separately for better accuracy. Cell size is calculated based on non-vectored flight lateral trajectories, so that non-vectored flights proceed one cell per unit time. Comparison between vectored and non-vectored trajectories and their speed profiles when modeled in CA reveals that CA can be applied successfully to model both congested and non-congested arrival traffic. Furthermore, merging routes are also investigated and it is shown that air traffic controllers consider merging traffic past a certain threshold only.

現在までの達成度 (区分)
現在までの達成度 (区分)

4: 遅れている

理由

Other work obligations delayed the progress of the current research.

今後の研究の推進方策

CA has been shown to adequately model current air traffic. Future heterogeneous traffic, in particular very high-speed flights such as the supersonic ones are to be added to the model to simulate any disturbances and potential operational solutions.

次年度使用額が生じた理由

The research has been granted an extension to JFY2023, so the remaining funds will be used in 2023.

URL: 

公開日: 2023-12-25  

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