空中交通网络中航空器群的实证分析  

Research on Aircraft Clusters of Air Traffic Network

作　　者：王红勇[1,2] 徐肖豪[2] 温瑞英[2] WANG Hong-yong XU Xiao-hao WEN Rui-ying(College of Civil Aviation, Nanjing University of Aeronautics ＆ AstronauticsI , Nanjing 210016, P. R. China Tianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, Civil Aviation University of China2, Tianjin 300300, P. R. China)

机构地区：[1]南京航空航天大学民航学院,南京210016 [2]中国民航大学天津市空管运行规划与安全技术重点实验室,天津300300

出　　处：《科学技术与工程》2016年第31期290-295,300,共7页Science Technology and Engineering

基　　金：国家自然科学基金委员会;中国民用航空局联合资助项目(U1333108);天津市应用基础与前沿技术研究计划(14JCQNJC04500)资助

摘　　要：现有的空中交通复杂性研究忽略了空中交通流结构影响,难以反映航空器空间密度分布不均匀的复杂性特征。利用复杂网络中社团结构的思想,对空中交通流结构特征进行研究。建立了航空器群模型,提出了基于深度优先遍历算法的航空器群发现方法,避免了传统社团划分方法需事先指定社团个数的缺点;并从模块度、内聚度、灵敏度几个角度形成了群性能指数,用于综合反映航空器群划分质量。采用实际航班数据对群划分结果进行评价分析,选取60 km为最佳阈值对航空器群的统计特征进行了进一步分析。结果表明,扇区内航空器间的平均水平间隔约为群内航空器间平均水平间隔的6倍;航空器群规模一般都比较小,一半以上的群规模小于6架;航空器群的生命期最长为9 min,但57%以上群的生命期为2 min。In the current research on air traffic complexity, there is lack of investigation on the character of air traffic flow structure, fail to reflect non-uniform distribution of the aircraft spatial density. The model of aircraft cluster and presented a methodology for identification of aircraft cluster based on depth-first searching algorithm in graph theory were established, which does not require any prior knowledge about the number of the clusters. The performance index consists of the module, cohesive degrees, the sensitivity, which can evaluate the results of air- craft cluster division. The empirical study conducted on the real flight data indicates that the optimal threshold was 60 km. Further research suggest, the average horizontal separation between aircrafts in sector is about 6 times clus- ters. The size of aircraft clusters are generally small, more than half of the clusters size is less than six. The longest life of aircraft cluster is 9 minutes, more than 57 percent of the cluster＇ s life is 2 minutes.

关 键 词：空中交通 复杂网络 社团结构 航空器群 交通复杂性 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]