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交通流量增长下的空中管制安全风险预警及阈值确定
引用本文:罗帆,杨智.交通流量增长下的空中管制安全风险预警及阈值确定[J].科技导报(北京),2012,30(4):61-66.
作者姓名:罗帆  杨智
作者单位:武汉理工大学管理学院,武汉 430070
摘    要: 中国民用航空运输量逐年增长,交通管制面对的安全风险压力不断上升。由于空中交通流量持续增加下安全风险的产生是一个相互作用、协同耦合的过程,因而具有明显的非线性、开放及动态特征,为实现预警管理的动态性和直观反映风险变量的系统关联性,利用系统动力学在时变性及非线性建模上的优势,构建空管安全风险动态预警模型。模型以管制飞行器流量增长为始点,以管制风险为终端界定内部指标变量,在结合实际调研及访谈的基础上,运用Vensim软件进行仿真分析。仿真实例有效预测了空管安全风险的预警状态值,并直观显示了相关影响因素在系统中的变化情况,在此基础上确定了主要预警指标的风险阈值。结果表明,运用系统动力学(SD)构建空中交通管制安全风险预警模型,可满足预警的动态性和系统性要求。

关 键 词:空中交通流量  管制安全  风险预警  阈值界定  系统动力学  
收稿时间:2012-01-08

ATC Safety Risks Early Warning and Threshold Value Determination Under the Growth of Air Traffic Flow
LUO Fan,YANG Zhi.ATC Safety Risks Early Warning and Threshold Value Determination Under the Growth of Air Traffic Flow[J].Science & Technology Review,2012,30(4):61-66.
Authors:LUO Fan  YANG Zhi
Institution:School of Management, Wuhan University of Technology, Wuhan 430070, China
Abstract:Under the circumstance of China's civil aviation transportation volume increased year by year, a continuous increase in air traffic flow, so traffic control safety risks faced by rising and practical pressure. As the air traffic flow under increasing security risk is generated from an interaction and coupling process, it has obvious characteristics such as nonlinear, open and dynamic. To realize the dynamic early warning management and intuitionist, which reflects the system relevance of risk variables. This paper uses the dynamics system in the changeable and nonlinear model to build dynamic ATC safety risk early warning model. In order to reflect the dynamic nature of the monitoring indicators and systems association, this article constructs ATC safety risk dynamic early warning models on the basis of the system dynamics. The above model looks for the growth of air traffic flow as the starting point and the control risk to define internal indicator variables as terminal. Based on actual research and interviews, this paper uses the Vensim to simulate and analysis. As simulated examples can predict ATC safety risk warning status values effectively and visualize the changes of related factors in the system, it is reasonable to determine the risk threshold of the key early warning indicators. Results show that the use of SD to construct ATC safety risks warning model, which can meet the model of the dynamic and systemic.
Keywords:air traffic flow  control of safety risks  dynamic early warning  determine threshold value  system dynamics  
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