[HTML][HTML] Graph attention networks: a comprehensive review of methods and applications
Real-world problems often exhibit complex relationships and dependencies, which can be
effectively captured by graph learning systems. Graph attention networks (GATs) have …
effectively captured by graph learning systems. Graph attention networks (GATs) have …
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 …
A hierarchical framework for improving ride comfort of autonomous vehicles via deep reinforcement learning with external knowledge
Ride comfort plays an important role in determining the public acceptance of autonomous
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
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 …
Comparative analysis of twelve transfer learning models for the prediction and crack detection in concrete dams, based on borehole images
US Khan, M Ishfaque, SUR Khan, F Xu, L Chen… - Frontiers of Structural …, 2024 - Springer
Disaster-resilient dams require accurate crack detection, but machine learning methods
cannot capture dam structural reaction temporal patterns and dependencies. This research …
cannot capture dam structural reaction temporal patterns and dependencies. This research …
A comprehensive survey on traffic missing data imputation
Intelligent Transportation Systems (ITS) are essential and play a key role in improving road
safety, reducing congestion, optimizing traffic flow and facilitating the development of smart …
safety, reducing congestion, optimizing traffic flow and facilitating the development of smart …
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) …
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 …