Recent studies show that driver drowsiness (fatigue) and inattention are major causes of fatal road accidents. A large number of these accidents could be avoided if the vehicles were equipped with sensors that reliably could monitor the attention and alertness cues of the drivers, and systems that, based on the sensor input, could warn the drivers in time. Driver fatigue and attention monitorin...

Fatigue and driver drowsiness monitoring is an important subject for designing driver assistance systems. The measurement of eye closure is a fundamental step for driver awareness detection. We propose a method which is based on eyelid detection and the measurement of the distance between the eyelids. First, the face and the eyes of the driver are localized. After extracting the eye region, the...

accurate delivery of torque to implant screws is critical to generate ideal preload in the screw joint and to offer protection against screw loosening. mechanical torque-limiting devices (mtlds) are available for this reason. in this study, the accuracy of one type of friction-style and two types of spring-style mtlds at baseline, following fatigue conditions and sterilization processes were de...

Most traffic accidents may be attributed to driver impairment as a consequence of factors such as inattention, fatigue, intoxication, etc. It is now technically feasible to monitor and diagnose driver behaviour with respect to impairment with the aid of a limited number of in-vehicle sensors, however, a valid framework for the evaluation of driver impairment is still lacking. In order to provid...

Nowadays, the human error is usually identified as the conclusive cause of investigations in road accidents. The human although is the person in control of vehicle until the moment of crash but it has to be understood that the human is under continued impact by various factors including road environment, vehicle and human’s state, abilities and conduct. The current advances in design of vehicle...

Many traffic accidents are caused by drivers with fatigue states. It is important to detect fatigue states of drivers from their eye opening degrees, namely normal, dozing and fatigue. The paper proposes a fatigue state recognition algorithm that combines independent component analysis (ICA) and one-dimensional hidden Markov model (HMM) together. The algorithm firstly does binarisation processi...

Fatigued driving is one of the leading causes traffic accidents, and detecting fatigued effectively critical to improving safety. Given variety individual variability surroundings, drivers’ states weariness, uncertainty key characteristic factors, in this paper, we propose a deep-learning-based study MAX-MIN driver fatigue detection algorithm. First, ShuffleNet V2K16 neural network used for fac...