A hierarchical fuzzy decision model for driver's unsafe states monitoring

In this paper, we present a hierarchical fuzzy decision model for driver's unsafe states monitoring. In this model, we want to combine the multi-aspect information into one output parameter, which stands for the level of inattentiveness of the driver. Five parameters are calculated: eye-closing duration, mouth-opening duration, mouth state change frequency (from opening to closure or from closure to openning), face detection failure duration, and historical information. Dozens of videos collected in Beijing urban streets of one driver are used for the test of the model. Experiment results and conclusions on the performance of the model are presented.

[1]  Michael L. Donnell,et al.  Fuzzy Decision Analysis , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  Fangwen Zhai,et al.  A detection model for driver's unsafe states based on real-time face-vision , 2010, 2010 International Conference on Image Analysis and Signal Processing.

[3]  Miguel Ángel Sotelo,et al.  Real-time system for monitoring driver vigilance , 2004, Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005..

[4]  Liying Lang,et al.  The Study of Driver Fatigue Monitor Algorithm Combined PERCLOS and AECS , 2008, 2008 International Conference on Computer Science and Software Engineering.

[5]  Jingyu Yang,et al.  Driver Fatigue Detection: A Survey , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[6]  Jun Zhou,et al.  Hierarchical fuzzy control , 1991 .

[7]  Zhiwei Zhu,et al.  Real-time nonintrusive monitoring and prediction of driver fatigue , 2004, IEEE Transactions on Vehicular Technology.

[8]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..