空中交通拥挤的识别与预测方法研究

doi:10.7527/S1000-6893.2015.0123

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空中交通拥挤的识别与预测方法研究

徐肖豪, 李善梅

中国民航大学空中交通管理学院, 天津 300300

收稿日期:2015-04-24 修回日期:2015-05-09 出版日期:2015-08-15 发布日期:2015-05-12
通讯作者: 徐肖豪男, 博士, 教授, 博士生导师。《航空学报》第七、八届编委。主要研究方向: 空中交通规划与管理, 新一代空中交通管理系统关键技术。Tel: 022-24092433 E-mail: xuxhao2008@sina.com E-mail:xuxhao2008@sina.com
作者简介:李善梅女, 博士。主要研究方向: 空中交通规划、管理与仿真。Tel: 022-24092433 E-mail: amy820203@163.com
基金资助:
国家自然科学基金(61039001); 中国民航大学科研启动基金(2014QD01S)

Identification and prediction of air traffic congestion

XU Xiaohao, LI Shanmei

College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China

Received:2015-04-24 Revised:2015-05-09 Online:2015-08-15 Published:2015-05-12
Contact: 10.7527/S1000-6893.2015.0123 E-mail:xuxhao2008@sina.com
Supported by:
National Natural Science Foundation of China (61039001); Scientific Research Foundation of Civil Aviation University of China (2014QD01S)

摘要/Abstract

摘要：

随着航空运输业的迅猛发展,空中交通拥挤现象日益严重,空中交通拥挤研究已经成为国际民航界的一个研究热点。其中,空中交通拥挤的识别与预测是空中交通拥挤研究的主要内容之一,在此基础上综述了国内外有关空中交通拥挤识别与预测方法的研究状况。首先概述了基于不同拥挤形成因素和拥挤后果的空中交通拥挤概念的研究状况;接着依据所用交通数据时间尺度的不同,分别针对基于短期数据的阈值判别方法、基于长期数据的聚类识别方法以及基于混合数据的综合评价方法综述了空中交通拥挤的主要识别方法;然后分别基于数理算法(统计算法、交通流模型算法和智能算法)和计算机仿真模拟技术综述了空中交通拥挤的主要预测方法;最后指出了空中交通拥挤识别与预测问题的近年研究热点和未来的研究方向。

关键词: 空中交通拥挤, 复杂网络, 识别, 预测, 交通容量

Abstract:

With the rapid development of air transport industry, the phenomenon of air traffic congestion is becoming more and more serious. The research of air traffic congestion is a hot topic of the international civil aviation community, among which, the identification and prediction of air traffic congestion is the most important. The research on identification and prediction methods of air traffic congestion is generalized. Firstly, the research findings of the concept of air traffic congestion based on congestion formations and congestion aftereffects are summed up. Secondly, the important research methods of air traffic congestion identification based on different time scales of traffic data are reviewed. They are threshold identification based on short term data, clustering identification based on long term data and comprehensive evaluation based on mixed data. Thirdly, the air traffic congestion prediction methods based on mathematical algorithms (prediction based on mathematical statistics, traffic flow models and intelligent algorithms) and computer simulation techniques are summarized. Lastly, the recent research focus and the future research directions of identification and prediction of air traftic congestion are put forward.

Key words: air traffic congestion, complex network, identification, prediction, traffic capacity

中图分类号:

V355

徐肖豪, 李善梅. 空中交通拥挤的识别与预测方法研究[J]. 航空学报, 2015, 36(8): 2753-2763.

XU Xiaohao, LI Shanmei. Identification and prediction of air traffic congestion[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(8): 2753-2763.

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空中交通拥挤的识别与预测方法研究

Identification and prediction of air traffic congestion

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