中国民航大学学报 ›› 2025, Vol. 43 ›› Issue (2): 19-30.

• 空域融合安全运行 • 上一篇    下一篇

基于融合编码转移网络的空中交通流量波动演化研究

  

  1. 1. 中国民航大学空中交通管理学院,天津 300300; 2. 中国民航科学研究院民航发展规划研究院,北京 100028
  • 收稿日期:2024-03-10 修回日期:2024-05-05 出版日期:2025-05-14 发布日期:2025-05-14
  • 作者简介:张勰(1981— ), 男, 陕西咸阳人, 副研究员, 博士, 研究方向为空中交通系统建模、优化与控制.
  • 基金资助:
    国家自然科学基金项目(U1633112,U2133210)

Research on evolution of air traffic flow fluctuations based on integration
encoding transition network

  1.  1. College of Air Traffic Management, CAUC, Tianjin 300300, China; 2. Research Institute of Civil
    Aviation Development and Planning, China Academy of Civil Aviation Science and Technology, Beijing 100028, China 
  • Received:2024-03-10 Revised:2024-05-05 Online:2025-05-14 Published:2025-05-14

摘要:

为突破以往仅针对空中交通流量波动方向的研究局限,考虑在空中交通流动态演化研究中充分突出流量波
动状态与机场容量限制等实际运行信息,借助动态粗粒化编码方法将机场流容比及流量波动梯度进行符
号编码并融合为波动模态,提出了融合编码转移网络构建方法。 针对北京大兴国际机场(简称大兴机场)的
全天时段与协调时段,从复杂网络视角开展了空中交通流量波动演化规律与特征的定量分析与定性识别研
究。 研究结果表明:大兴机场两个时段的空中交通流量波动演化差异主要集中在宏观层面;流量波动模态
的演化具有显著的转移集聚与相继频现的特点,存在显著的频繁转移模式;强聚类模态和大枢纽模态有效
刻画了流量波动演化的轨迹性特征。 这些规律性特征为空中交通流量波动状态预测、流量管理预案构建提
供了理论基础,对提升机场容量使用效率、优化机场时刻资源配置具有现实意义。

关键词:

Abstract:

In order to break through the limitations of previous research that only focused on the direction of air traffic flow
fluctuations, and to fully highlight the actual operational information such as flow fluctuation status and airport capacity limitations in the study of air traffic flow dynamic evolution, a fusion encoding transition network construction method is proposed using dynamic coarse-grained encoding method to symbolically encode the airport flow
volume ratio and flow fluctuation gradient and merge into fluctuation modal. Quantitative analysis and qualitative
identification study are conducted on the evolution laws and characteristics of air traffic flow fluctuations from a
complex network perspective, focusing on the 24-hour and coordinated time periods of Beijing Daxing International Airport (Daxing Airport). The research results indicate that the differences in the evolution of air traffic flow
fluctuations between the two periods at Daxing Airport are mainly concentrated at the macro level. The evolution of
flow fluctuation modes has significant transfer aggregation and successive frequency, and there are significant frequent transfer modes. Strong clustering modes and large hub modes effectively characterize the trajectory characteristics of flow fluctuation evolution. These regular features provide a theoretical basis for predicting air traffic flow
fluctuations state and constructing flow management plans, which has practical significance for improving airport
capacity utilization efficiency and optimizing airport time resource allocation.

Key words:

中图分类号: