Connected and automated vehicles: Infrastructure, applications, security, critical challenges, and future aspects
Autonomous vehicles (AV) are game-changing innovations that promise a safer, more
convenient, and environmentally friendly mode of transportation than traditional vehicles …
convenient, and environmentally friendly mode of transportation than traditional vehicles …
Understanding traffic bottlenecks of long freeway tunnels based on a novel location-dependent lighting-related car-following model
To understand the formation of lighting-related traffic bottlenecks along the long freeway
tunnels in the daytime, this study develops an intelligent driver model incorporating the …
tunnels in the daytime, this study develops an intelligent driver model incorporating the …
TriPField: A 3D potential field model and its applications to local path planning of autonomous vehicles
Potential fields have been integrated with local path-planning algorithms for autonomous
vehicles (AVs) to tackle challenging scenarios with dense and dynamic obstacles. Most …
vehicles (AVs) to tackle challenging scenarios with dense and dynamic obstacles. Most …
Modeling automatic pavement crack object detection and pixel-level segmentation
Timely pavement crack detection can prevent further pavement deterioration. However,
obtaining sufficient quantities of crack information at low cost remains a challenge. This …
obtaining sufficient quantities of crack information at low cost remains a challenge. This …
Data-driven indoor positioning correction for infrastructure-enabled autonomous driving systems: A lifelong framework
C Zhao, A Song, Y Zhu, S Jiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Infrastructure-enabled autonomous driving systems have been increasingly applied in
confined environments. Automated valet parking (AVP) in smart parking garages is one of …
confined environments. Automated valet parking (AVP) in smart parking garages is one of …
Safe, efficient, and comfortable autonomous driving based on cooperative vehicle infrastructure system
J Chen, C Zhao, S Jiang, X Zhang, Z Li… - International journal of …, 2023 - mdpi.com
Traffic crashes, heavy congestion, and discomfort often occur on rough pavements due to
human drivers' imperfect decision-making for vehicle control. Autonomous vehicles (AVs) …
human drivers' imperfect decision-making for vehicle control. Autonomous vehicles (AVs) …
Multi-performance enhanced eco-driving strategy for connected fuel cell hybrid electric bus based on stein soft actor-3-critic
Eco-driving strategies increasingly emphasize enhancing multi-performance including
safety, comfort, durability, and traffic efficiency under optimal energy-saving. This paper …
safety, comfort, durability, and traffic efficiency under optimal energy-saving. This paper …
A two-stage framework for parking search behavior prediction through adversarial inverse reinforcement learning and transformer
Parking scenarios are spatially dense and have a lot of interactions, making predicting
vehicles' search behavior crucial and challenging for autonomous driving. Existing data …
vehicles' search behavior crucial and challenging for autonomous driving. Existing data …
Analysis of perception accuracy of roadside millimeter-wave radar for traffic risk assessment and early warning systems
C Zhao, D Ding, Z Du, Y Shi, G Su, S Yu - International journal of …, 2023 - mdpi.com
Millimeter-wave (MMW) radar is essential in roadside traffic perception scenarios and traffic
safety control. For traffic risk assessment and early warning systems, MMW radar provides …
safety control. For traffic risk assessment and early warning systems, MMW radar provides …
Ego‐planning‐guided multi‐graph convolutional network for heterogeneous agent trajectory prediction
Accurate prediction of the future trajectories of traffic agents is a critical aspect of
autonomous vehicle navigation. However, most existing approaches focus on predicting …
autonomous vehicle navigation. However, most existing approaches focus on predicting …