Authors:
Hyeokmin Lee
1
;
Hosang Moon
1
;
Jaehoon Kim
1
;
Jaeheui Lee
1
;
Eunghyuk Lee
2
and
Sungtaek Chung
3
Affiliations:
1
Department of IT Semiconductor Convergence Engineering, Tech University of Korea, 237, Sangidaehak-ro, Siheung-si, Gyeonggi-do, Republic of Korea
;
2
Department of Electronic Engineering, Tech University of Korea, 237, Sangidaehak-ro, Siheung-si, Gyeonggi-do, Republic of Korea
;
3
Department of Computer Engineering, Tech University of Korea, 237, Sangidaehak-ro, Siheung-si, Gyeonggi-do, Republic of Korea
Keyword(s):
Driving Behaviors, Driving Style, Latent Dirichlet Allocation, Topic Model.
Abstract:
The present study aims to analyze driving style and latent driving behavior typically at intersections where various driving habits show up. To this end, 6 different scenarios were simulated and data on the gaze of the drivers were analyzed using topic modeling. Their driving styles (topics) latent in the driver’s driving behaviors (words) following a driving scenario (document) were analyzed by using the latent dirichlet allocation of topic modeling, the most frequently used in discovering latent topics in documents generally made up of words. For the study, six participants in their twenties were selected whose driver licenses were more than a year old. They were asked to drive in a virtual reality simulator, while wearing a head mounted display capable of tracking their gazes. The experimental results showed that the less experienced the drivers were, the more frequently and longer they gazed at the navigation and the speed instrument panel and repeated the start and stop. On the
other hand, the more experienced the drivers were, the more they gazed briefly at the objects within the car, maintained speed after glancing at the most distant objects, and applied braking only when necessary.
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