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首页> 外文期刊>Journal of guidance, control, and dynamics >Link Transmission Model for Air Traffic Flow Management
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Link Transmission Model for Air Traffic Flow Management

机译：空中交通流量管理的链路传输模型

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摘要

Optimization of air traffic flow in the National Airspace System is, by nature, a large-scale problem, the solving of which usually requires intensive computation. This paper presents a mixed integer linear programming method to solve a nationwide air traffic flow management problem based on an aggregate air traffic model. A dual decomposition method is applied to solve the large-scale traffic management problem, where the nationwide problem is decomposed path by path into 1000s of subproblems that are solved independently. It is shown in this paper that the solution with the dual decomposition method converges to the global optimum. The major contribution of the proposed modeling and optimization framework is that it is about 6 times faster than a previously developed large-capacity cell transmission model. It is also shown that the proposed optimization method obtains an equally optimal solution as the large-capacity cell transmission model. In the meantime, the proposed model is capable of including both ground delay and airborne delay, while the large-capacity cell transmission model includes airborne delay only. The traffic forecasting capability of the new model is also examined statistically at the sector level and the national level. It is shown that the sector counts are predicted with relative errors of less than 20 % for over 80 % of the high-altitude sectors in the United States. Further analysis also suggests that the accuracy of the proposed model is comparable with the other two aggregate models in the literature.
机译：本质上，国家空域系统中空中交通流量的优化是一个大规模的问题，要解决该问题通常需要大量的计算。本文提出一种混合整数线性规划方法，以解决基于集合空中交通模型的全国空中交通流量管理问题。应用双重分解方法来解决大规模交通管理问题，该问题将全国性问题逐条路径分解为数千个独立解决的子问题。本文表明用对偶分解法的解收敛于全局最优。所提出的建模和优化框架的主要贡献是它比以前开发的大容量小区传输模型快约6倍。还表明，所提出的优化方法获得了与大容量小区传输模型相同的最优解。同时，提出的模型能够同时包括地面延迟和空中延迟，而大容量小区传输模型仅包括空中延迟。新模型的流量预测能力也在部门级别和国家级别进行了统计检验。结果表明，对于美国超过80％的高海拔扇区，扇区计数的相对误差小于20％。进一步的分析还表明，所提出模型的准确性可与文献中的其他两种聚合模型相媲美。

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