Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles
Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …
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 …
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 …
detect driver inattention is essential in building a safe yet intelligent transportation system …
A survey on vision-based driver distraction analysis
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 …
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
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 …
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
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 …
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …
Efficient driver anomaly detection via conditional temporal proposal and classification network
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 …
system (DMS). Recent works treat driver distraction detection as a multiclass action …
Application of physiological sensors for personalization in semi-autonomous driving: A review
As automobiles become increasingly autonomous, there is growing interest in personalized
automation based on human behavior. However, there is an increasing need for behavioral …
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 …
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 …
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 …
co-passenger, use of in-vehicle devices or phone leads to a situation where the driver head …