Using brainwaves and eye tracking to determine attention levels for auto-lighting systems

Junzo Watada, Yung Chin Hsiao, Hanayuki Kitagawa

    Research output: Contribution to journalArticle

    Abstract

    To prevent car accidents, it should be possible for pedestrians and other drivers to detect oncoming vehicles. Many car accidents are caused because persons are not aware of approaching traffic, and this applies especially to visual awareness. The daytime running light (DRL) and the third braking light (TBL) were developed to significantly increase the visibility of vehicles, and their effectiveness has been verified through numerous studies. Usage of light-emitting diode (LED) lighting technology has also become popular in auto-lighting systems because of its advantages of energy efficiency, long life, and stylish appearance. However, LED lighting technology is very different from conventional incandescent or high-intensity discharge (HID) lighting technology. In this paper, we determine the effectiveness of LEDs as DRLs and TBLs. We measure human attention levels by observing brainwaves and performing eye-tracking experiments that shows the relationship between the theory of attention, brainwaves, and eye tracking. The results obtained show that it is feasible to evaluate automotive exterior lighting using the attention levels of subjects.

    Original languageEnglish
    Pages (from-to)611-618
    Number of pages8
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume19
    Issue number5
    Publication statusPublished - 2015 Sep 1

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    Keywords

    • Brainwave
    • Daytime running light
    • Eye tracking
    • Light-emitting diode
    • Third braking light

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

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