Authors
Shouyi Wang, Yiqi Zhang, Changxu Wu, Felix Darvas, Wanpracha Art Chaovalitwongse
Publication date
2014/7/8
Journal
IEEE Transactions on Intelligent Transportation Systems
Volume
16
Issue
1
Pages
136-150
Publisher
IEEE
Description
This paper presents a new computational framework for early detection of driver distractions (map viewing) using brain activity measured by electroencephalographic (EEG) signals. Compared with most studies in the literature, which are mainly focused on the classification of distracted and nondistracted periods, this study proposes a new framework to prospectively predict the start and end of a distraction period, defined by map viewing. The proposed prediction algorithm was tested on a data set of continuous EEG signals recorded from 24 subjects. During the EEG recordings, the subjects were asked to drive from an initial position to a destination using a city map in a simulated driving environment. The overall accuracy values for the prediction of the start and the end of map viewing were 81% and 70%, respectively. The experimental results demonstrated that the proposed algorithm can predict the start and end …
Total citations
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Scholar articles
S Wang, Y Zhang, C Wu, F Darvas… - IEEE Transactions on Intelligent Transportation …, 2014