Open AccessGazing as actual parameter for drowsiness assessment in driving simulators
Author(s) -
Arthur M. Rumagit,
Izzat Aulia Akbar,
Mitaku Utsunomiya,
Takamasa Morie,
Tomohiko Igasaki
Publication year - 2019
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v13.i1.pp170-178
Subject(s) - gaze , driving simulator , eye tracking , simulation , driving simulation , computer vision , artificial intelligence , computer science
Many traffic accidents are due to drowsy driving. However, to date, only a few studies have been conducted on the gazing properties related to drowsiness. This study was conducted with the objective of estimating the relationship between gazing properties and drowsiness in three facial expression evaluation (FEE) categories: alert (FEE = 0), lightly drowsy (FEE = 1−2), heavily drowsy (FEE = 3−4). Drowsiness was investigated based on these eye-gazing properties by analyzing the gazing signal utilizing an eye gaze tracker and FEE in a driving simulator environment. The results obtained indicate that gazing properties have significant differences among the three drowsiness conditions, with p < 0.001 in a Kruskal–Wallis test. Furthermore, the overall classification accuracy of the three drowsiness conditions based on gazing properties using a support vector machine was 76.3%. This indicates that our proposed gazing properties can be used to quantitatively assess drowsiness.