A model‐based approach for cognitive assistance is proposed to keep track of pilots' changing demands in dynamic situations. Based on model‐tracing with flight deck interactions and EEG recordings, the model is able to represent individual pilots' behavior in response to flight deck alerts. As a first application of the concept, an ACT‐R cognitive model is created using data from an empirical flight simulator study on neurophysiological signals of missed acoustic alerts. Results show that uncertainty of individual behavior representation can be significantly reduced by combining cognitive modeling with EEG data. Implications for cognitive assistance in aviation are discussed.

中文翻译：

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用于跟踪飞行员认知状态不确定性的神经适应认知模型。

提出了一种基于模型的认知辅助方法，以跟踪飞行员在动态情况下不断变化的需求。基于具有驾驶舱交互作用和EEG记录的模型跟踪，该模型能够表示飞行员对驾驶舱警报的反应。作为该概念的第一个应用，使用来自经验性飞行模拟器研究的数据来创建ACT‐R认知模型，该研究针对错过的声音警报的神经生理信号。结果表明，通过将认知模型与EEG数据相结合，可以显着降低个人行为表示的不确定性。讨论了航空中认知辅助的含义。