Airbus Central Research & Technology.
Chair of Cognitive Modelling in Dynamic Systems, TU Berlin.
Top Cogn Sci. 2020 Jul;12(3):1012-1029. doi: 10.1111/tops.12515. Epub 2020 Jul 14.
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.
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。基于与飞行甲板交互和 EEG 记录的模型跟踪，该模型能够代表飞行员对飞行甲板警报的反应的个体行为。作为该概念的首次应用，使用关于错过声警报的神经生理信号的实证飞行模拟器研究的数据，创建了一个 ACT-R 认知模型。结果表明，通过将认知建模与 EEG 数据相结合，可以显著降低个体行为表示的不确定性。讨论了在航空中的认知辅助的意义。
