Driving style classification by analyzing eeg responses to unexpected obstacle dodging tasks

Chin-Teng Lin*, Sheng Fu Liang, Wen Hung Chao, Li-Wei Ko, Chih Feng Chao, Yu Chieh Chen, Teng Yi Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Driving safely has received increasing attention of the publics due to the growing number of traffic accidents that the driver's driving style is highly correlated to many accidents. The purpose of this study is to investigate the relationship between driver's driving style and driver's ERP response. In our research, a virtual reality (VR) driving environment is developed to provide stimuli to subjects. Independent component analysis (ICA) is used to decompose the electroencephalogram (EEG) data. The power spectrum analysis of ICA components and correlation analysis are employed to investigate the EEG activities related to driving style. Experimental results demonstrate that we may classify the drivers into aggressive or gentle styles based on the observed ERP difference corresponding to the proposed unexpected obstacle dodging tasks.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
Pages4916-4919
Number of pages4
DOIs
StatePublished - 28 Aug 2007
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan
Duration: 8 Oct 200611 Oct 2006

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume6
ISSN (Print)1062-922X

Conference

Conference2006 IEEE International Conference on Systems, Man and Cybernetics
CountryTaiwan
CityTaipei
Period8/10/0611/10/06

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