Effects of Automation and Fatigue on Drivers from Various Age Groups [PDF]
Safety, 2022 This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in
Sadegh Arefnezhad +2 more
doaj +3 more sources
Efficient and Robust Driver Fatigue Detection Framework Based on the Visual Analysis of Eye States [PDF]
Promet (Zagreb), 2023 Fatigue detection based on vision is widely employed in vehicles due to its real-time and reliable detection results. With the coronavirus disease (COVID-19) outbreak, many proposed detection systems based on facial characteristics would be unreliable ...
Yancheng Ling, Xiaoxiong Weng
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Research on the Prediction of Driver Fatigue Degree Based on EEG Signals [PDF]
SensorsObjective: Predicting driver fatigue degree is crucial for traffic safety. This study proposes a deep learning model utilizing electroencephalography (EEG) signals and multi-step temporal data to predict the next time-step fatigue degree indicator ...
Zhanyang Wang +3 more
doaj +2 more sources
A study of the effects of olfactory stimulus duration and concentration on sleep arousal under fatigue driving [PDF]
Frontiers in PsychologyOlfactory stimulation can alleviate passive task-related fatigue (PTR), but its mechanism and influencing factors are still unclear. This study used a controlled experimental design to explore the effect of mint odor on driving fatigue by comparing the ...
Faren Huo +3 more
doaj +2 more sources
Driver drowsiness estimation using EEG signals with a dynamical encoder–decoder modeling framework [PDF]
Scientific Reports, 2022 Drowsiness is a leading cause of accidents on the road as it negatively affects the driver’s ability to safely operate a vehicle. Neural activity recorded by EEG electrodes is a widely used physiological correlate of driver drowsiness.
Sadegh Arefnezhad +7 more
doaj +2 more sources
Active Vision-Based Attention Monitoring System for Non-Distracted Driving [PDF]
IEEE Access, 2021 Inattentive driving is a key reason of road mishaps causing more deaths than speeding or drunk driving. Research efforts have been made to monitor drivers' attentional states and provide support to drivers.
Lamia Alam +5 more
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Association of Visual-Based Signals with Electroencephalography Patterns in Enhancing the Drowsiness Detection in Drivers with Obstructive Sleep Apnea [PDF]
SensorsIndividuals with obstructive sleep apnea (OSA) face increased accident risks due to excessive daytime sleepiness. PERCLOS, a recognized drowsiness detection method, encounters challenges from image quality, eyewear interference, and lighting variations ...
Riaz Minhas +7 more
doaj +2 more sources
Drowsiness Detection System Based on PERCLOS and Facial Physiological Signal [PDF]
Sensors, 2022 Accidents caused by fatigue occur frequently, and numerous scholars have devoted tremendous efforts to investigate methods to reduce accidents caused by fatigued driving.
Robert Chen-Hao Chang +3 more
doaj +2 more sources
Mind the road: attention related neuromarkers during automated and manual simulated driving captured with a new mobile EEG sensor system [PDF]
Frontiers in NeuroergonomicsBackgroundDecline in vigilance due to fatigue is a common concern in traffic safety. Partially automated driving (PAD) systems can aid driving but decrease the driver's vigilance over time, due to reduced task engagement.
Joanna Elizabeth Mary Scanlon +4 more
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Sensitivity of PERCLOS70 to Drowsiness Level: Effectiveness of PERCLOS70 to Prevent Crashes Caused by Drowsiness [PDF]
IEEE Access, 2022 It has been reported that many crashes are caused by drowsiness. Thus, it is critical to predict the occurrence of severe drowsiness that may result in a crash by means of an effective measure.
Atsuo Murata +2 more
doaj +3 more sources