基于灰色聚类的交叉航路拥挤识别方法  

Congestion Identification of Crossing Air Routes Based on Gray Clustering Method

作　　者：李善梅[1] 徐肖豪[1] 王超[1] 王飞[1] 

机构地区：[1]中国民航大学空中交通管理研究基地,天津300300

出　　处：《西南交通大学学报》2015年第1期189-197,共9页Journal of Southwest Jiaotong University

基　　金：国家自然科学基金委与中国民用航空局联合资助项目(61039001;U1333108);国家科技支撑计划资助项目(2011BAH24B10);中央高校基本科研业务费专项资金资助项目(ZXH2011A002;3122014D036;ZXH2009D012)

摘　　要：为了减轻空管人员对交叉航路拥挤态势的认知负荷,针对现有空中交通拥挤识别方法的局限,根据交通拥挤的形成过程,提出了基于飞入、飞出交通量的交叉航路拥挤定义;在此基础上,提出了交叉航路拥挤度量指标,即滞留度指标、汇聚度指标和当量交通量指标,建立了交叉航路汇聚度模型,以及基于灰色聚类的交叉航路拥挤识别方法.交叉航路仿真运行数据的验证结果表明:交叉航路拥挤态势是其宏观动态特征和微观复杂特征相互作用的结果,本文方法识别的准确率达到90%,且计算过程简单可行.In order to reduce the cognitive load of air traffic managers for congestion of crossing air routes, the limitations of the congestion identification measurements was analyzed. According to the formation process of traffic congestion, a definition of crossing air routes congestion based on flying inflow and flying outflow rates was established. On this basis, indexes for measuring traffic congestion of crossing air routes, including retention degree, aggregation degree, and equivalent traffic volume, was proposed to establish an aggregation model of crossing air routes. Then, a congestion identification method of crossing air routes was built by gray clustering theory, and verified by numerical simulation. The results show that the congestion status is the result of interaction between macroscopic dynamic features and complicated microscopic features; the proposed method has an identification precision of 90% and a simple and feasible calculation orocess.

关 键 词：航路 拥挤 识别 灰色聚类 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]