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 …
Using inertial sensors to determine head motion—a review
S Ionut-Cristian, D Dan-Marius - Journal of Imaging, 2021 - mdpi.com
Human activity recognition and classification are some of the most interesting research
fields, especially due to the rising popularity of wearable devices, such as mobile phones …
fields, especially due to the rising popularity of wearable devices, such as mobile phones …
Towards next generation of pedestrian and connected vehicle in-the-loop research: A digital twin co-simulation framework
Digital Twin is an emerging technology that replicates real-world entities into a digital space.
It has attracted increasing attention in the transportation field and many researchers are …
It has attracted increasing attention in the transportation field and many researchers are …
A novel heterogeneous network for modeling driver attention with multi-level visual content
Driver attention modeling is a crucial technique in building human-centric intelligent driving
systems. Considering the human visual mechanism, this study leverages multi-level visual …
systems. Considering the human visual mechanism, this study leverages multi-level visual …
Comprehensive driver behaviour review: Taxonomy, issues and challenges, motivations and research direction towards achieving a smart transportation environment
The aim of this article is to review and analyse previous academic articles associated with
car behaviour analysis for the period of 2010 to June 10, 2021 and understand the benefits …
car behaviour analysis for the period of 2010 to June 10, 2021 and understand the benefits …
FDAN: Fuzzy deep attention networks for driver behavior recognition
W **ao, G **e, 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 …
Real-time multistep time-series prediction of driver's head pose during IVIS secondary tasks for Human–Machine codriving and distraction warning systems
X Zhao, Z Li, C Zhao, C Wang - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
An accurate prediction of a driver's head pose in the in-vehicle information system (IVIS)
tasks is essential for both distraction warning and vehicle takeover rule-making in human …
tasks is essential for both distraction warning and vehicle takeover rule-making in human …
Active vision-based attention monitoring system for non-distracted driving
Inattentive driving is a key reason of road mishaps causing more deaths than speeding or
drunk driving. Research efforts have been made to monitor drivers' attentional states and …
drunk driving. Research efforts have been made to monitor drivers' attentional states and …
TML: A triple-wise multi-task learning framework for distracted driver recognition
We propose a multi-task learning framework for improving the performance of vision-based
deep-learning approaches for driver distraction recognition. The most popular tool so far for …
deep-learning approaches for driver distraction recognition. The most popular tool so far for …
Context-Aware Driver Attention Estimation Using Multi-Hierarchy Saliency Fusion With Gaze Tracking
Accurate vision-based driver attention estimation is a challenging task due to the limitations
of the visual sensor, and it is a critical and fundamental function of building a human …
of the visual sensor, and it is a critical and fundamental function of building a human …