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Multimodal estimation of a driver's spontaneous irritation
Malta, Lucas
Miyajima, Chiyomi
Kitaoka, Norihide
Takeda, Kazuya
open access
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
In this paper we present our latest achievements in the continuous estimation of a driver's spontaneous irritation. Experiments are conducted with data from 20 drivers, recorded under real driving conditions. While driving, participants also interact with a speech dialogue system to retrieve and play music. A fusion method is proposed to integrate information on the driving environment, driver behavior, driver's physiological state, and speech recognition results. Overall, we are able to correctly detect 80% (true positive rate) of the irritation, and, when drivers are not irritated, we only make mistakes 9% of the time (false positive rate). Results also support the relevance of gas- and brake-pedal operation as well as speech recognition results in irritation estimation.
IEEE
2009-06-03
eng
journal article
VoR
http://hdl.handle.net/2237/13903
https://nagoya.repo.nii.ac.jp/records/12027
https://doi.org/10.1109/IVS.2009.5164341
1931-0587
Intelligent Vehicles Symposium, 2009 IEEE
573
577
https://nagoya.repo.nii.ac.jp/record/12027/files/Malta_IV2009-06.pdf
application/pdf
263.9 kB
2018-02-20