Title
Extracting train driver's perception strategies using Interpretive Structural Modeling
Abstract
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.
Year
DOI
Venue
2014
10.1109/SCIS-ISIS.2014.7044709
SCIS&ISIS
Keywords
Field
DocType
behavioural sciences computing,gaze tracking,human factors,ism,attention distribution,complex eye-gaze movement pattern extraction,dominant transition patterns,experienced train drivers,external environment,interpretive structural modeling,limited-attentional resources,multilevel structural model generation,operational requirements,perception strategy,structural model extraction,train driver perception strategy extraction,visual attentive behavior,younger drivers
Computer vision,Gaze,Computer science,Vigilance (psychology),Human–computer interaction,Operational requirements,Artificial intelligence,Perception,Machine learning
Conference
ISSN
Citations 
PageRank 
2377-6870
0
0.34
References 
Authors
4
8