Scalable Multidimensional Uncertainty Evaluation Approach to Strategic Air Traffic Flow Management
Scalable Multidimensional Uncertainty Evaluation Approach to Strategic Air Traffic Flow Management
复制标题
战略空中交通流量管理的可扩展多维不确定性评估方法
DOI：
10.2514/6.2015-2492
复制
发表时间：
2015
影响因子：
3.1
通讯作者：
Y. Wan
中科院分区：
文献类型：
--
作者：
Junfei Xie;Y. Wan
对流天气事件导致国家空域系统（NAS）的容量降低，并引发交通拥堵。为了缓解拥堵，空中交通流量战略管理在较长的前瞻时间（2 - 15小时）规划交通流量。由于天气事件的多种可能性以及实时管理的要求，在这个时间范围内进行规划具有挑战性。为了克服这些挑战，我们需要一种方法来快速评估预测的天气事件对空中交通系统性能的影响。在本文中，我们使用一种可扩展的多维不确定性评估方法，称为M - PCM - OFFD，来解决这个问题。模拟研究表明了这种方法对空中交通系统性能评估的有效性。此外，我们通过探索更高级别的OFFD来进一步研究M - PCM - OFFD的能力。最后，我们引入一个利用不确定性的框架，以便在天气不确定的情况下进行实时的空中交通战略管理。
Convective weather events cause capacity reduction in the National Airspace System (NAS), and lead to traffic congestion. To mitigate congestion, strategic air traffic flow management plans traffic flows at a long look-ahead time (2-15 hour). Planning at this timeframe is challenging, due to the wide possibility of weather events and requirement for real-time management. To conquer these challenges, we need an approach to quickly assess the impact of predicted weather events on the performance of air traffic system. In this paper, we use a scalable multidimensional uncertainty evaluation approach, called M-PCM-OFFD, to address this problem. Simulation studies show the effectiveness of this approach for the performance evaluation of air traffic system. In addition, we investigate further capability of M-PCM-OFFD through exploring higher-level OFFDs. Finally, we introduce an uncertainty-exploiting framework to enable real-time strategic air traffic management under weather uncertainty.