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 …

Appearance-based gaze estimation with deep learning: A review and benchmark

Y Cheng, H Wang, Y Bao, F Lu - IEEE Transactions on Pattern …, 2024‏ - ieeexplore.ieee.org
Human gaze provides valuable information on human focus and intentions, making it a
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

J Dong, S Chen, M Miralinaghi, T Chen, P Li… - … research part C …, 2023‏ - Elsevier
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 …

Latent space autoregression for novelty detection

D Abati, A Porrello, S Calderara… - Proceedings of the …, 2019‏ - openaccess.thecvf.com
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 …

A review of sensor technologies for perception in automated driving

E Marti, MA De Miguel, F Garcia… - IEEE intelligent …, 2019‏ - ieeexplore.ieee.org
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 …

A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook

M Liu, E Yurtsever, J Fossaert, X Zhou… - IEEE Transactions …, 2024‏ - ieeexplore.ieee.org
Autonomous driving has rapidly developed and shown promising performance due to recent
advances in hardware and deep learning techniques. High-quality datasets are fundamental …

Towards knowledge-driven autonomous driving

X Li, Y Bai, P Cai, L Wen, D Fu, B Zhang… - arxiv preprint arxiv …, 2023‏ - arxiv.org
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

Predicting head movement in panoramic video: A deep reinforcement learning approach

M Xu, Y Song, J Wang, ML Qiao… - IEEE transactions on …, 2018‏ - ieeexplore.ieee.org
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 …

DADA: Driver attention prediction in driving accident scenarios

J Fang, D Yan, J Qiao, J Xue… - IEEE transactions on …, 2021‏ - ieeexplore.ieee.org
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 …

What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach

S Zhu, Q Meng - Accident Analysis & Prevention, 2022‏ - Elsevier
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 …