A Stochastic Modeling and Analysis Approach to Strategic Traffic Flow Management under Weather Uncertainty
A Stochastic Modeling and Analysis Approach to Strategic Traffic Flow Management under Weather Uncertainty
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天气不确定性下战略交通流管理的随机建模和分析方法
DOI：
10.2514/6.2011-6514
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发表时间：
2011
影响因子：
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通讯作者：
C. Wanke
中科院分区：
文献类型：
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作者：
Yi Zhou;Y. Wan;Sandip Roy;C. Taylor;C. Wanke
在这篇文章中，我们介绍了一个很有希望的框架，用于表示在天气不确定情况下运行的空中交通流(流)和流管理操作。我们建议使用网状排队和马尔可夫链模型来捕获不确定环境中的交通管理。具体而言，该模型的服务速率由描述天气影响演化的潜在马尔可夫链来调制。开发了两种使用该模型来表征流管理性能的技术，即1)主马尔可夫链表示技术，其产生准确的结果，但计算代价相对较高；2)基于跳跃线性系统的近似，具有良好的可扩展性。通过大量的实例说明了模型的建立和两种分析方法。基于这项初步研究，我们相信，这里分析的天气影响和交通流相互作用的模型有望为下一代的战略流量应急管理提供信息。
In this article, we introduce a promising framework for representing an air traffic flow (stream) and flow-management action operating under weather uncertainty. We propose to use a meshed queuing and Markov-chain model—specifically, a queuing model whose service-rates are modulated by an underlying Markov chain describing weather-impact evolution—to capture traffic management in an uncertain environment. Two techniques for characterizing flow-management performance using the model are developed, namely 1) a master-Markov-chain representation technique that yields accurate results but at relatively high computational cost, and 2) a jump-linear system-based approximation that has promising scalability. The model formulation and two analysis techniques are illustrated with numerous examples. Based on this initial study, we believe that the interfaced weather-impact and traffic-flow model analyzed here holds promise to inform strategic flow contingency management in NextGen.