利用NASA ATD-2融合数据源预测夏洛特道格拉斯国际机场登机口冲突

William J. Coupe, Hanbong Lee, Andrew M. Churchill, Isaac J. Robeson
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引用次数: 1

摘要

NASA正在进行空域技术演示-2,以评估综合到达、离开和地面(IADS)交通管理系统。IADS系统由实时系统范围信息管理提供动力,提供飞行生命周期的准确和高保真视图。这些数据可以用来提高国家空域系统的效率。对于非安全关键应用,第三方服务提供商有机会提供这种数据驱动的近实时预测服务。本文将门冲突预测问题作为一个具体的用例来研究,这有助于提高效率。我们将门冲突建模为一个回归问题,并描述了模型构建、模型验证和评估的迭代过程,用于评估我们的方法的有效性。我们量化预测的准确性,并确定改进的途径。通过这个迭代过程,我们希望将我们的模型和方法发展到接近实时的预测服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Gate Conflicts at Charlotte Douglas International Airport Using NASA ATD-2 Fused Data Sources
NASA is conducting the Airspace Technology Demonstration-2 to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system. The IADS system is powered by real-time System Wide Information Management feeds which provide an accurate and high fidelity view of the lifecycle of a flight. This data can be leveraged to drive efficiencies in the National Airspace System. For non safety critical applications there is opportunity for third party service providers to offer this type of data-driven prediction service in near real-time. This paper investigates the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach. We quantify our predictive accuracy and identify paths for improvement. Through this iterative process we hope to evolve our models and methods to a near real-time prediction service.
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