Volume 38, Number 2, April 2020
|Page(s)||279 - 287|
|Published online||17 July 2020|
Identification of Key Flight Conflict Nodes Based on Complex Network Theory
Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China
2 Troops 32211 of the PLA, Yulin 719006, China
The air traffic density in the terminal area is high and the traffic situation is relatively complex by the development of aviation, which brings great challenges to controller. In order to understand the flight situation and provide decision basis for controllers, this paper proposes a key flight conflict nodes identification method based on complex network theory and Analytic Hierarchy Process (AHP)-entropy weight method. Firstly, an aircraft state network is established with aircraft as nodes and Airborne Collision Avoidance System (ACAS) communication relations as connecting edges. On this basis, four parameters, node degree, node weight, clustering coefficient and betweenness, are selected as evaluation indexes of node importance, and the weight of each index is determined by using AHP. And entropy weight method is introduced to revise the results. Node importance is calculated through multi-attribute decision-making method to determine key conflict aircrafts. The simulation and experiment on the artificial network and the aircraft state network of a certain day in the terminal area of Kunming Changshui Airport show that the method proposed in this paper can identify the key flight conflict nodes in the aircraft state network, allocate the selected node deployment can effectively reduce the complexity of the aircraft state network, can provide reference for air traffic control services (ATCS), and reduce the allocation difficulty of controller.
随着航空事业的发展，终端区内空中交通密度大，交通态势相对复杂，给管制人员带来巨大的挑战。为充分理解空中飞行态势，给管制人员提供决策依据，提出了一种基于复杂网络理论和层次分析-熵权法的关键冲突飞机识别方法。首先以飞机为节点，机载防相撞系统（airborne collision avoidance system，ACAS）建立通信关系为连边构建飞行状态网络；在此基础上，选取节点度、点强、加权聚类系数和介数4个参数作为评估节点重要度指标，利用层次分析法确定各指标权重，并引入熵权法的思想，对结果进行修正，通过多属性决策的方法计算出节点重要度，确定关键冲突飞机。在人造网络和昆明长水机场终端区内的飞行状态网络上的仿真和实验结果：提出的方法能够确识别飞行状态网络中的关键冲突点，对选出的节点进行调配能够有效降低飞行状态网络的复杂性，可以为空中交通管制服务提供参考，降低管制人员的调配难度。
Key words: complex network / aircraft states network / key nodes / multi-attribute decision-making
关键字 : 复杂网络 / 飞行状态网络 / 关键节点 / 多属性决策
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
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