查看文章

With the growing volume and complexity of air traffic, air traffic controllers (ATCOs) encounter heavier burden nowadays. Therefore, human factors study in air traffic control (ATC) is increasingly essential, paving the way to a safer air transportation system. In this paper, we conducted an ATC experiment, where Electroencephalogram (EEG) data were collected throughout the experiment. Compared to traditional questionnaires and psychological tests used in human factors study, the proposed novel EEG approach provides monitoring of situation awareness (SA) in a non-invasive and non-interruptive fashion. SA was represented as the response latency in situation-present assessment method (SPAM), which was predicted from EEG signals using three machine learning algorithms. Support vector regression obtained the lowest prediction error of 1.5 seconds, which is lower than 10% of the range of actual response …