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Heterogeneous air traffic flow modeling and congestion mechanism clarification

Heterogeneous air traffic flow modeling and congestion mechanism clarification
异构空中交通流建模及拥堵机制阐明
批准号:
20K14855
负责人:
アンドレエバ森 アドリアナ
金额:
$2.5万
依托单位国家:
日本
项目类别:
Grant-in-Aid for Early-Career Scientists
财政年份:
2020
资助国家:
日本
项目状态:
已结题
起止时间:
2020-04-01 至 2024-03-31

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中文摘要
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英文摘要
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.
期刊论文(1)
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会议论文
Preliminary Parameter Investigation for Cellular Automata Air Traffic Flow Modelling
元胞自动机空中交通流建模的初步参数研究
DOI: --
发表时间: 2021
期刊:
影响因子: --
作者: [原宏江, Y.B.P.カハタガハワッタ, 詹静雅, 山口裕通, 本多了, 松浦哲久, 池本良子, 山村寛, 小宮涼,今井龍一,中村健二,塚田義典,梅原喜政, Adriana Andreeva-Mori]
通讯作者: Adriana Andreeva-Mori
Probabilistic arrival time prediction algorithm using a-priori knowledge and machine learning to enable sustainable air traffic management
  • 批准号:
    24K07723
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
  • 资助金额:
    $2.83万
  • 财政年份:
    2024
  • 负责人:
    アンドレエバ森 アドリアナ
  • 依托单位:
海外基金