Development of Three Driver State Detection Models from Driving Information Using Vehicle Simulator; Normal, Drowsy and Drunk Driving

Author:

Lee Kang Hee,Baek Keon Hee,Choi Su Bin,Jeong Nak Tak,Moon Hyung Uk,Lee Eun Seong,Kim Hyung Min,Suh Myung Won

Publisher

Springer Science and Business Media LLC

Subject

Automotive Engineering

Reference24 articles.

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2. Dai, J., Teng, J., Bai, X., Shen, Z. and Xuan, D. (2010). Mobile phone based drunk driving detection pervasive computing technologies for healthcare. Proc. 4th Int. Conf. Pervasive Computing Technologies for Healthcare, Munich, Germany.

3. Dawson, D. and Reid, K. (1997). Fatigue, alcohol and performance impairment. Nature 388, 6639, 235.

4. Eskandarian, A. (2012). Handbook of Intelligent Vehicles. Drowsy and Fatigued Driving Problem Significance and Detection Based on Driver Control Functions. Springer-Verlag London, London, UK.

5. Fu, R. and Wang, H. (2014). Detection of driving fatigue by using noncontact EMG and ECG signals measurement system. Int. J. Neural Systems 24, 3, 1450006.

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