Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles

Z Hu, S Lou, Y Xing, X Wang, D Cao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

A review of recent developments in driver drowsiness detection systems

Y Albadawi, M Takruri, M Awad - Sensors, 2022 - mdpi.com
Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

Intelligent driver drowsiness detection for traffic safety based on multi CNN deep model and facial subsampling

M Ahmed, S Masood, M Ahmad… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Facts reveal that numerous road accidents worldwide occur due to fatigue, drowsiness, and
distraction while driving. Few works on the automated drowsiness detection problem …

A survey on driver behavior analysis from in-vehicle cameras

J Wang, W Chai, A Venkatachalapathy… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Distracted or drowsy driving is unsafe driving behavior responsible for thousands of crashes
every year. Studying driver behavior has challenges associated with observing drivers in …

Real-time machine learning-based driver drowsiness detection using visual features

Y Albadawi, A AlRedhaei, M Takruri - Journal of imaging, 2023 - mdpi.com
Drowsiness-related car accidents continue to have a significant effect on road safety. Many
of these accidents can be eliminated by alerting the drivers once they start feeling drowsy …

A novel learning model of driver fatigue features representation for steering wheel angle

Z Li, L Chen, L Nie, SX Yang - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
In the field of advanced driver assistance systems (ADAS), effective learning of driver fatigue
characteristics representation is a major challenge due to uncertainties of both real roads …

Early identification and detection of driver drowsiness by hybrid machine learning

A Altameem, A Kumar, RC Poonia, S Kumar… - IEEE …, 2021 - ieeexplore.ieee.org
Drunkenness or exhaustion is a leading cause of car accidents, with severe implications for
road safety. More fatal accidents could be avoided if fatigued drivers were warned ahead of …

Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review

SA El-Nabi, W El-Shafai, ESM El-Rabaie… - Multimedia Tools and …, 2024 - Springer
There are several factors for vehicle accidents during driving such as drivers' negligence,
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …

[HTML][HTML] A systematic review on detection and prediction of driver drowsiness

ME Shaik - Transportation research interdisciplinary perspectives, 2023 - Elsevier
Driver drowsiness has emerged as one of the key factors in recent times' traffic accidents,
which can result in fatalities, serious physical losses, large monetary losses, and significant …

Attention for vision-based assistive and automated driving: A review of algorithms and datasets

I Kotseruba, JK Tsotsos - IEEE transactions on intelligent …, 2022 - ieeexplore.ieee.org
Driving safety has been a concern since the first cars appeared on the streets. Driver
inattention has been singled out as a major cause of accidents early on. This is hardly …