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Combining ATC Subjective Cognitive Complexity Evaluation Metrics in a Single Indicator

机译:在单个指标中结合ATC主观认知复杂性评估指标

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This paper describes an Air Traffic Control (ATC) cognitive complexity indicator yielded from a human-in-the-loop simulation. The analysis used to this end employs factor analysis for the identification of the correlation between cognitive complexity and several cognitive complexity and workload metrics. Thereby, a single complexity indicator has been developed. It has proved to be more responsive to the overall complexity than any of the other subjective metrics alone. Nonetheless, there is indication that the proposed complexity indicator must not be taken alone, but analyzed together with other metrics. The paper also tackles the impacts of traffic history, automation and optimized schedules on the perceived complexity and how these impacts should be taken into consideration on the design of future concepts of ATC operations. This is done through the application of the proposed indicator into several ATC scenarios.
机译:本文介绍了通过在环仿真得出的空中交通管制(ATC)认知复杂性指标。为此目的进行的分析采用因素分析来识别认知复杂性与若干认知复杂性和工作量指标之间的相关性。从而,已经开发了单个复杂性指标。与单独的任何其他主观指标相比,它被证明对整体复杂性的响应更快。但是,有迹象表明,建议的复杂性指标不能单独考虑,而应与其他指标一起进行分析。本文还讨论了交通历史,自动化和优化时间表对感知的复杂性的影响,以及在设计ATC运营的未来概念时应如何考虑这些影响。这是通过将拟议指标应用于几种空中交通管制情景来完成的。

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