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

Z Hu, S Lou, Y **ng, 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 …

Decision-making in driver-automation shared control: A review and perspectives

W Wang, X Na, D Cao, J Gong, J **… - IEEE/CAA Journal of …, 2020 - ieeexplore.ieee.org
Shared control schemes allow a human driver to work with an automated driving agent in
driver-vehicle systems while retaining the driverʼ s abilities to control. The human driver, as …

Driver distraction and in-vehicle interventions: A driving simulator study on visual attention and driving performance

RE Amini, C Al Haddad, D Batabyal, I Gkena… - Accident Analysis & …, 2023 - Elsevier
Driving simulator studies are popular means to investigate driving behaviour in a controlled
environment and test safety-critical events that would otherwise not be possible in real-world …

Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …

HV Koay, JH Chuah, CO Chow, YL Chang - Engineering Applications of …, 2022 - Elsevier
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …

Detecting human driver inattentive and aggressive driving behavior using deep learning: Recent advances, requirements and open challenges

MH Alkinani, WZ Khan, Q Arshad - Ieee Access, 2020 - ieeexplore.ieee.org
Human drivers have different driving styles, experiences, and emotions due to unique
driving characteristics, exhibiting their own driving behaviors and habits. Various research …

Driver distraction detection based on vehicle dynamics using naturalistic driving data

X Wang, R Xu, S Zhang, Y Zhuang, Y Wang - Transportation research part …, 2022 - Elsevier
Distracted driving such as phone use during driving is risky, as it increases the probability of
severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in …

[HTML][HTML] Survey and synthesis of state of the art in driver monitoring

A Halin, JG Verly, M Van Droogenbroeck - Sensors, 2021 - mdpi.com
Road vehicle accidents are mostly due to human errors, and many such accidents could be
avoided by continuously monitoring the driver. Driver monitoring (DM) is a topic of growing …

Perceived risk vs actual driving performance during distracted driving: A comparative analysis of phone use and other secondary distractions

P Choudhary, A Gupta, NR Velaga - … research part F: traffic psychology and …, 2022 - Elsevier
The present study attempts to explore the association of drivers' risk perception towards
phone usage as well as other everyday distractions (operating a music player and eating …

Towards computationally efficient and realtime distracted driver detection with mobilevgg network

B Baheti, S Talbar, S Gajre - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
According to the World Health Organization (WHO) report, the number of road traffic deaths
have been continuously increasing since last few years though the rate of deaths relative to …

CAT-CapsNet: A convolutional and attention based capsule network to detect the driver's distraction

H Mittal, B Verma - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Worldwide inflation in the count of road accidents has raised an alarming scenario wherein
driver distraction is identified as one of the main causes. According to the National Highway …