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Using Historical Data to Automatically Identify Air-Traffic Control Behavior.
| 题名： | Using Historical Data to Automatically Identify Air-Traffic Control Behavior. |
| 作者： | Lauderdale, T. A.; Tretto, C.; Wu, Y. |
| 关键词： | Air Traffic; Air Traffic Control; Amount; Controllers; Errors; Histories; Machine Learning; Mathematical Models; Routes |
| 摘要： | This project seeks to develop statistical-based machine learning models to characterize the types of errors present when using current systems to predict future aircraft states. These models will be data-driven - based on large quantities of historical data. Once these models are developed, they will be used to infer situations in the historical data where an air-traffic controller intervened on an aircraft's route, even when there is no direct recording of this action. |
| 报告类型： | 科技报告 |
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