Despite rapid advancements in the automotive industry, traffic safety risks persist. Addressing this challenge requires innovative driver assistance technologies. Common accidents result from driver inattention, fatigue, and stress, leading to issues like falling asleep at the wheel and improper acceleration and braking. In this paper, we developed a sensor network using EEG and eye trackers to measure drivers' emotions, exploring the relationship between emotional states and driving behavior. Our study aims to contribute to advanced driver assistance systems that adapt to drivers' emotional needs, ultimately enhancing road safety.


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    Title :

    Measuring Driver's Emotion


    Contributors:


    Publication date :

    2023-11-27


    Size :

    1207415 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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