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首页> 外文期刊>Journal of guidance, control, and dynamics >Short-Term National Airspace System Delay Prediction Using Weather Impacted Traffic Index
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Short-Term National Airspace System Delay Prediction Using Weather Impacted Traffic Index

机译：使用受天气影响的交通指数进行的短期国家空域系统延误预测

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摘要

This paper presents a method to develop short-term delay prediction models for time intervals of up to 2 h. Various linear autoregressive model structures were implemented to perform the delay prediction with WITI, predicted-WITI, and reference trafficrnvolume as exogenous inputs. The refined methodology for generating the WITI and predicted-WITl, together with the high-update-rate CIWS weather product is well suited for short-term delay prediction. An adaptive method was implemented to provide both weather-related and nonweather-related delay predictions depending on the weather and air traffic condition. The models are compared using traffic and weather data for the summer months of 2007. The results show that WITI provides the most useful information for the 1-h prediction, whereas the best 2-h predictions rely on both WITI and predicted-WITI. The reference air traffic volume provides nonweather-related information, which is useful on nonconvective weather days. This paper is the first to study short-term real-time air traffic delay prediction using WITI and predicted-WITI. The study should help traffic flow management in guiding flow control decisions and in identifying the strategies to reduce delays, cancellations, and costs during the day of operations in various weather conditions.
机译：本文提出了一种开发时间间隔最长为2 h的短期延迟预测模型的方法。实现了各种线性自回归模型结构，以使用WITI，预测的WITI和参考流量作为外部输入来执行延迟预测。用于生成WITI和WIT1预测的改进方法以及高更新率CIWS天气产品非常适合于短期延迟预测。实施了一种自适应方法，可根据天气和空中交通状况提供与天气有关和与非天气有关的延迟预测。使用2007年夏季的交通和天气数据对模型进行了比较。结果表明，WITI为1小时预报提供了最有用的信息，而最佳2小时预报依赖于WITI和预测的WITI。参考空中交通流量提供了与天气无关的信息，这在非对流天气日非常有用。本文是首次研究使用WITI和预测的WITI进行的实时实时空中交通延误预测。该研究应有助于交通流量管理，以指导流量控制决策并确定减少在各种天气条件下运营期间的延误，取消和成本的策略。

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  • 来源
    《Journal of guidance, control, and dynamics》 |2009年第2期|657-662|共6页
  • 作者

    Banavar Sridhar; Neil Y. Chen;

  • 作者单位

    NASA Ames Research Center,Moffett Field, California 94035-1000 Air Transportation Systems, Aviation Systems Division.Fellow AIAA.;

    NASA Ames Research Center,Moffett Field, California 94035-1000 University of California Santa Cruz, Mail Stop 210-8;

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