Effects of Driver Fatigue Monitoring – An Expert Survey

Author(s):  
Katja Karrer ◽  
Matthias Roetting
2014 ◽  
Vol 548-549 ◽  
pp. 1093-1097 ◽  
Author(s):  
Dong Yao Jia ◽  
Sheng Xiong Zou

Because fatigue monitoring based on the image of the non-contact measurement is single and low accuracy, a novelty driver fatigue monitoring system based on multivariate hierarchical Bayesian network is proposed. The system mainly includes four modules following: face region detecting, eyelid closure judging, head region positioning, and fatigue analyzing. The eye region is positioned precisely by the method of gray projection function, the binary image which contains the whole eye information using self-adapting threshold method is obtained, and then driver fatigue monitoring system based on hierarchical Bayesian network is used to evaluate the fatigue level of the driver. The experimental results show that the fatigue monitoring accuracy is up to 90% in specific conditions, it’s effective to improve the detection accuracy compared to the other method.


2018 ◽  
Vol 95 (3) ◽  
pp. 409-414
Author(s):  
Nabil Yassine ◽  
Steve Barker ◽  
Khaled Hayatleh ◽  
Bhaskar Choubey ◽  
Rajasekhar Nagulapalli

Author(s):  
Christopher W. Ferrone ◽  
Charles Sinkovits

The National Transportation Safety Board has reported statistics which indicate that 31% of all fatal-to-the-truck driver accidents occur due to fatigue/inattention [1] and 58% of all single-vehicle large truck crashes were also fatigue related [2]. If these numbers can be reduced, many lives can be saved. A Driver Fatigue Monitoring System has been designed and built to monitor whether a driver is sleeping or inattentive. This integrated system monitors the steering input behavior of the driver during a specified period of time. If the number of steering inputs is below the expected predetermined threshold, the system activates an audible alarm and light in the cab, waking the driver. Furthermore, this system can deactivate cruise control as well as activate various other preprogrammed truck systems or components to further aid in the control of the truck and to alert nearby motorists.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 67342-67353 ◽  
Author(s):  
Yin-Cheng Tsai ◽  
Peng-Wen Lai ◽  
Po-Wei Huang ◽  
Tzu-Min Lin ◽  
Bing-Fei Wu

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