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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 …
Appearance-based gaze estimation with deep learning: A review and benchmark
Human gaze provides valuable information on human focus and intentions, making it a
crucial area of research. Recently, deep learning has revolutionized appearance-based …
crucial area of research. Recently, deep learning has revolutionized appearance-based …
Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems
User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
Latent space autoregression for novelty detection
Novelty detection is commonly referred as the discrimination of observations that do not
conform to a learned model of regularity. Despite its importance in different application …
conform to a learned model of regularity. Despite its importance in different application …
A review of sensor technologies for perception in automated driving
After more than 20 years of research, ADAS are common in modern vehicles available in the
market. Automated Driving systems, still in research phase and limited in their capabilities …
market. Automated Driving systems, still in research phase and limited in their capabilities …
A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook
Autonomous driving has rapidly developed and shown promising performance due to recent
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
Towards knowledge-driven autonomous driving
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …
investigation highlights the limitations of current autonomous driving systems, in particular …
Predicting head movement in panoramic video: A deep reinforcement learning approach
Panoramic video provides immersive and interactive experience by enabling humans to
control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in …
control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in …
DADA: Driver attention prediction in driving accident scenarios
Driver attention prediction is becoming an essential research problem in human-like driving
systems. This work makes an attempt to predict the driver attention in driving accident …
systems. This work makes an attempt to predict the driver attention in driving accident …
What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach
Autonomous vehicles (AVs) are emerging in the automobile industry with potential benefits
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …