基于相依网络的空中交通复杂度评估与关键要素识别
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1.中国民航大学空中交通管理学院;2.中国民航大学 空中交通管理学院

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V355

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国家自然科学基金(基金号62173332);天津市应用基础研究多元投入基金(基金号21JCYBJCO0700);中央高校自然科学重点项目(基金号3122023050)


Evaluation of air traffic complexity and identification of key elements based on interdependent network
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College of Air Traffic Management,Civil Aviation University of China

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    摘要:

    对终端空域运行复杂性态势量化难度大,评估维度单一的问题,根据飞机间运动和管制协调的依赖关系,提出一种基于相依网络的空中交通复杂度评估方法。依据管制、飞行网络层内节点间冲突关系和层间节点间的关联性,建立管制-飞行相依网络,提出空中交通网络复杂度模型。采用Pearson相关系数进行网络复杂度影响因素分析,确定影响网络复杂度的关键节点,最后,从管制调配角度,识别并验证影响交通复杂度的关键要素。使用北京终端历史ADS-B数据对评估模型进行验证,结果表明:考虑网络相依度的复杂度评估方法能够客观、及时反映空中交通的复杂态势并且更加有预见性;网络复杂度与关键节点复杂状态有极大相关性,其中节点速度变化是影响网络复杂度的关键要素;对关键节点速度进行速度干预,可以一定程度上控制网络复杂度态势的发展,保障空中交通运行安全。

    Abstract:

    Aiming at the high difficulty of quantifying the complexity of terminal airspace operational situations and the limitation of evaluation dimensions, a method for assessing air traffic complexity, which is based on network interdependence, has been proposed in this paper. It is done according to the relationships of relative motion and the dependencies of air traffic control coordination. Taking into account the conflicts between interlayer nodes of the control and flight networks, as well as the correlations among interlayer nodes, a control-flight interdependent network and an air traffic network complexity model have been established. The Pearson correlation coefficient is used to analyze the factors that influence network complexity, identifying the critical nodes that have a significant impact on network complexity. It also verifies the correlation between node flight parameters and network complexity. Finally, the key factors affecting traffic complexity are identified and validated from the perspective of regulation deployment. The evaluation model has been validated using historical ADS-B data from Beijing Terminal, showing that the complexity assessment method that considers network interdependence provides objective and timely indications of complex air traffic situations with enhanced predictability. It is found that network complexity is highly correlated with the complex state of critical flight nodes, and the rate of change in node speed is a key factor affecting network complexity. The speed intervention of critical nodes can control the development of network complexity to a certain extent, thus ensuring the safety of air traffic operations.

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齐雁楠,王新彤,王兴隆. 基于相依网络的空中交通复杂度评估与关键要素识别[J]. 科学技术与工程, , ():

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  • 收稿日期:2023-09-20
  • 最后修改日期:2024-05-25
  • 录用日期:2024-05-29
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