中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (4): 41-48.doi: 10.16265/j.cnki.issn1003-3033.2021.04.006

• 安全社会科学与安全管理 • 上一篇    下一篇

基于SD模型的跑道侵入风控网络脆弱性分析

吴维 讲师, 罗欣然, 魏明 副教授   

  1. 中国民航大学 空中交通管理学院,天津 300300
  • 收稿日期:2021-01-04 修回日期:2021-03-08 出版日期:2021-04-28 发布日期:2021-12-20
  • 作者简介:吴 维 (1982—),男,河北承德人,硕士,讲师,主要从事空中交通系统优化与管理方面的研究。E-mail:wuwei8209@163.com。
  • 基金资助:
    教育部人文社科项目(20YJCZH176);中央高校基本科研业务费中国民航大学专项(3122013D023, 3122019126)。

Vulnerability assessment of runway intrusion risk control network based on SD model

WU Wei, LUO Xinran, WEI Ming   

  1. College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
  • Received:2021-01-04 Revised:2021-03-08 Online:2021-04-28 Published:2021-12-20

摘要: 为量化评估跑道侵入风险水平,分析核心致因要素在风控网络中的脆弱性特征,首先根据跑道侵入案例及专家经验,系统识别跑道侵入风险致因,利用灰色关联理论分析影响致因关联度,确定核心控制要素;然后分析各要素间相互作用机制,建立系统动力学(SD)模型,引入贝叶斯网络和综合权重确定方法设计SD方程;最后脆弱性仿真与分析跑道侵入风控网络,确定其脆弱性,并通过组合策略分析提升风控网络韧性。结果表明:结合历史数据使用贝叶斯网络和综合权重确定方法能够提升SD模型的客观性和精度;管制员指令不及时、通信中断概率上升、流量增长快和监管投入降低为网络脆弱点;加大培训与增加经验、增加人员与加速设备更新等风控策略对提升网络韧性具有明显替代性,在大流量场景下加强监管策略作用效果被平抑。

关键词: 系统动力学(SD), 跑道侵入, 风控网络, 脆弱性分析, 模糊综合评价, 贝叶斯网络

Abstract: In order to quantify risks of runway intrusion, and to evaluate vulnerability characteristics of core factors in risk control network, a SD model was constructed to systematically study runway intrusion by using vulnerability theory. Firstly, according to incursion cases and expert experience, causal factors were identified, their relevancy degree was analyzed by adopting grey correlation theory, and core control elements were determined. Secondly, interaction mechanism between elements was analyzed, a SD model was established, and dynamic equations were designed by utilizing Bayes theory and comprehensive weight determination method. Finally, vulnerability of runway intrusion risk control network was defined through simulation and analysis, and its resilience was improved through combination strategy analysis. The results show that Bayesian theory and comprehensive weight determination method, combined with historical data, can effectively improve objectivity and accuracy of SD model. Controller's un-timely instructions, increasing rate of communication breaking, fast growth of traffic and reduced regulatory investment are vulnerable points of the network. And risk control strategies, such as intensified training and experience and increasing personnel allocation and equipment update, have obvious substitution on improving network resilience, yet effect of strengthening supervision strategy will be suppressed under large traffic condition.

Key words: system dynamics (SD), runway incursion, risk control network, vulnerability analysis, fuzzy comprehensive appraisal, Bayes theory

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