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 …

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 …

A survey on vision-based driver distraction analysis

W Li, J Huang, G Xie, F Karray, R Li - Journal of Systems Architecture, 2021 - Elsevier
Motor vehicle crashes are great threats to our life, which may result in numerous fatalities, as
well as tremendous economic and societal costs. Driver inattention, either distraction or …

Distracted driving detection based on the fusion of deep learning and causal reasoning

P Ping, C Huang, W Ding, Y Liu, M Chiyomi, T Kazuya - Information Fusion, 2023 - Elsevier
Distracted driving is one of the key factors that cause drivers to ignore potential road hazards
and then lead to accidents. Existing efforts in distracted behavior recognition are mainly …

Deep learning-based hard spatial attention for driver in-vehicle action monitoring

I Jegham, I Alouani, AB Khalifa, MA Mahjoub - Expert Systems with …, 2023 - Elsevier
Distracted driving is one of the main causes of deaths and injuries in the world. Monitoring
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …

Efficient driver anomaly detection via conditional temporal proposal and classification network

L Su, C Sun, D Cao, A Khajepour - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Detecting driver inattentive behaviors is crucial for driving safety in a driver monitoring
system (DMS). Recent works treat driver distraction detection as a multiclass action …

Application of physiological sensors for personalization in semi-autonomous driving: A review

EJC Nacpil, Z Wang, K Nakano - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
As automobiles become increasingly autonomous, there is growing interest in personalized
automation based on human behavior. However, there is an increasing need for behavioral …

FDAN: Fuzzy deep attention networks for driver behavior recognition

W Xiao, G Xie, H Liu, W Chen, R Li - Journal of Systems Architecture, 2024 - Elsevier
Driver behavior is an essential factor affecting traffic safety, and driver behavior monitoring
systems (DMSs) are widely exploited in intelligent transportation systems to reduce the risk …

Sad: Sensor-based anomaly detection system for smart junctions

P Mohandas - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The low cost and advancement of sensor technology have long proven to be invaluable in
their use in all areas of science. Several video-based methods have already been …

Driver distraction analysis using face pose cues

CV Hari, P Sankaran - Expert Systems with Applications, 2021 - Elsevier
Vehicle driver distraction is one of the major reasons for road accidents. Involvement with a
co-passenger, use of in-vehicle devices or phone leads to a situation where the driver head …