Paper Info
Title
Extraction and Investigation of Dominant Eye-Gaze Pattern in Train Driver's Visual Behavior Using Markov Cluster Algorithm.
Abstract
In the present study, dominant eye-gaze patterns in professional train drivers' visual behavior are investigated using the Markov Cluster (MCL) algorithm. Applying the MCL algorithm results in a common gaze pattern showing a sort of perception tactic the drivers usually follow. The drivers repetitively move their gaze ahead soon after looking at somewhere else, independently of their years of experience. They are, however, found different in that experienced drivers can consistently follow the tactic while inexperienced drivers cannot. Time variation in the number of attentive pattern deviations demonstrates that, as well as the inexperienced drivers made higher frequency and larger fluctuations of pattern deviation, there were several particular segments in the route in which intensive pattern deviations arose in common. Inexperienced drivers would make intensive pattern deviations in such route segments that may have higher requirements of their cognitive resources.
Year
DOI
Venue
2016
10.1109/SCIS&ISIS.2016.116
Joint International Conference on Soft Computing and Intelligent Systems SCIS and International Symposium on Advanced Intelligent Systems ISIS
Field
DocType
ISSN
Cognitive resource theory,Gaze,Ocular dominance,Computer science,sort,Markov chain,Algorithm,Artificial intelligence,Perception,Machine learning
Conference
2377-6870
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Yukio Horiguchi11711.89
Takaya Suzuki201.01
Tetsuo Sawaragi312134.49
Nakanishi, H.434.15
Tomoharu Takimoto500.34