Modeling situation awareness on alarm displays in nuclear power plants

Abstract

Human factors engineering is important and has been brought into the regulations for the operation of nuclear power plants. However, there is still a discrepancy between the regulations and the practices. In this study, the SEEV model was used as a framework to construct an analytical model for predicting situation awareness in terms of the gaze distribution percentage on alarm displays in nuclear power plants. Two similar multiple linear regression models were constructed and validated based on the data of eye-tracking from 40 participants. Results showed that these two models were consistent with the SEEV framework. The values of R-square for these two models were 0.78 and 0.83, whereas the values of predicted R-square were 0.77 and 0.72. The analytical model developed in this study should be a necessary complement to current practice of situation awareness measurement. In addition, through the model, the improvement of alarm display design can be achieved in a resource effective manner.