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空中交通拥挤的识别与预测方法研究
引用本文: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.
作者姓名:徐肖豪  李善梅
作者单位:中国民航大学 空中交通管理学院, 天津 300300
基金项目:国家自然科学基金(61039001); 中国民航大学科研启动基金(2014QD01S)
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  
收稿时间:2015-04-24
修稿时间:2015-05-09

Identification and prediction of air traffic congestion
XU Xiaohao,LI Shanmei.Identification and prediction of air traffic congestion[J].Acta Aeronautica et Astronautica Sinica,2015,36(8):2753-2763.
Authors:XU Xiaohao  LI Shanmei
Institution:College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
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.
Keywords:air traffic congestion  complex network  identification  prediction  traffic capacity  
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