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 …

Driver distraction detection methods: A literature review and framework

A Kashevnik, R Shchedrin, C Kaiser, A Stocker - IEEE Access, 2021 - ieeexplore.ieee.org
Driver inattention and distraction are the main causes of road accidents, many of which
result in fatalities. To reduce road accidents, the development of information systems to …

[HTML][HTML] A review of sensory interactions between autonomous vehicles and drivers

J Lu, Z Peng, S Yang, Y Ma, R Wang, Z Pang… - Journal of Systems …, 2023 - Elsevier
Nowadays, human-oriented has already become the direction of the development of the
intelligent vehicle, among which, the cabin, in constant contact with drivers, is getting more …

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 …

Driver fatigue detection systems using multi-sensors, smartphone, and cloud-based computing platforms: a comparative analysis

Q Abbas, A Alsheddy - Sensors, 2020 - mdpi.com
Internet of things (IoT) cloud-based applications deliver advanced solutions for smart cities
to decrease traffic accidents caused by driver fatigue while driving on the road …

Decentralized cooperative crossing at unsignalized intersections via vehicle-to-vehicle communication in mixed traffic flows

GN Bifulco, A Coppola, A Petrillo… - Journal of Intelligent …, 2022 - Taylor & Francis
Abstract Connected Autonomous Vehicles (CAVs) are going to share the road environment
with human drivers until their full market deployment achievement. In this context, this paper …

The challenges of driving mode switching in automated vehicles: A review

L Hu, H Cai, J Huang, D Cao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The conversion between automated and manual driving is currently an inevitable topic for
automated vehicles. Firstly, from the concepts, types, and key issues of driving mode …

Multimodal corpus design for audio-visual speech recognition in vehicle cabin

A Kashevnik, I Lashkov, A Axyonov, D Ivanko… - IEEE …, 2021 - ieeexplore.ieee.org
This paper introduces a new methodology aimed at comfort for the driver in-the-wild
multimodal corpus creation for audio-visual speech recognition in driver monitoring systems …