Extracting train driver's perception strategies using Interpretive Structural Modeling

In this study, we applied the methodology of Interpretive Structural Modeling (ISM) in order to extract eye-gaze movement patterns characteristic of experienced train drivers in their visual attentive behavior. Application of ISM to eye-gaze data generates multilevel structural models that represent dominant transition patterns hidden in complex eye-gaze movements. The extracted structural models demonstrate that, as a basic perception strategy, the drivers repetitively moved their gaze ahead soon after looking at some other specific area. What differentiates the experienced and younger drivers is that the former group of drivers can consistently follow this basic perception strategy during driving while the latter can not. The experienced drivers can balance their limited attentional resources between vigilance to the external environment and other operational requirements, distributing their attention effectively and efficiently among various areas of interest.