TITLE:
Driver State Detection Based on Cardiovascular System and Driver Reaction Information Using a Graphical Model
AUTHORS:
Thanh Tung Nguyen, Hirofumi Aoki, Anh Son Le, Hirano Akio, Kunimoto Aoki, Makoto Inagami, Tatsuya Suzuki
KEYWORDS:
Human Engineering, Driver Behavior, Bio-Signal, Safety
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.11 No.2,
March
3,
2021
ABSTRACT: Traffic accidents are mainly caused by human error. In an aging society,
the number of accidents attributed to elderly drivers is increasing. One
noteworthy reason for this is operation misapplication. Studies have been
conducted on the use of human-machine interfaces (HMIs) to inform the driver when he or she makes an
error and encourage appropriate actions. However, the driver state during the
erroneous action has not been investigated. The purpose of this study is to clarify the difference in the driver’s state
between normal and surprising situations in a misapplication scenario,
utilizing multimodal information such as biometric information and driver
operation. We found significant changes in the interaction of components
between the normal and the surprised driving state.
The results could provide basic knowledge for the future development of
a driver assistance system and driver state estimation using data acquired from
multiple sensors in the vehicle.