Abstract: This paper aims to examine the effect of fatigue caused by temporary/permanent physical characteristics on driver behavior and detect fatigue drivers as a result of the research. In this context, the driver was monitored by fixed cameras in daylight conditions. Driver fatigue detection system was developed to use yawning for fatigue detection and classify this characteristic with the Convolutional Neural Network (ConNN) model. Proposed method is trained and evaluated on YawDD, Nthu-DDD and KouBM-DFD dataset. Experimental results demonstrate that the proposed ConNN can efficiently detect driver fatigue status with driving images. The proposed ConNN algorithm accuracy is higher than other CNN-based methods. Accuracy rates shows 99.35%, 99.25% and 99,01%, respectively.
Key words: Driver fatigue, Mouth detection, ConNN
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