A quantitative input for evaluating human error of visual Neglection: Prediction of Operator's detection time spent on perceiving critical visual signal

Human error of neglecting critical visual signal could be a trigger of serious accident, especially for those scenarios in which urgent operator intervention is required. Conventional human reliability analyses (HRAs) suffer from data collecting challenges and imprecision problems when evaluating such human error. This paper proposes a new method specialized for predicting operator's detection time spent on perceiving critical visual signal, which is not limited by data collecting challenges and effectively integrates human-visual-scanning processes and detailed characteristics of human-machine interface. Specifically, a novel method of creating visual scan paths is developed to model the “Scanning†part of detection time, and the emerging uncertainty theory is introduced to evaluate the “Noticing†part of it. Further, a new Monte Carlo method is established for combining the “Scanning†and “Noticing†parts, whose outcome is a chance distribution of detection time of interest. From the perspective of practical applications, a conversion of the detection time to uncertainty of human error of visual neglection is clearly explained. A validation from real test demonstrates the effectiveness of proposed method, which also indicates that compared to several common HRAs, the method is more accurate in analyzing the scenarios in which available time for operator's action is short.