A review of vision-based traffic semantic understanding in ITSs
J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …
situations and emergencies more accurately and provide a more accurate basis for anomaly …
Infrastructure-based object detection and tracking for cooperative driving automation: A survey
Object detection and tracking play a fundamental role in enabling Cooperative Driving
Automation (CDA), which is regarded as the revolutionary solution to addressing safety …
Automation (CDA), which is regarded as the revolutionary solution to addressing safety …
[HTML][HTML] 3d-net: Monocular 3d object recognition for traffic monitoring
Abstract Machine Learning has played a major role in various applications including
Autonomous Vehicles and Intelligent Transportation Systems. Utilizing a deep convolutional …
Autonomous Vehicles and Intelligent Transportation Systems. Utilizing a deep convolutional …
Leveraging deep convolutional neural networks pre-trained on autonomous driving data for vehicle detection from roadside LiDAR data
Recent technological advancements in computer vision algorithms and data acquisition
devices have greatly facilitated the research and applications of deep learning-based traffic …
devices have greatly facilitated the research and applications of deep learning-based traffic …
A dynamic clustering algorithm for lidar obstacle detection of autonomous driving system
F Gao, C Li, B Zhang - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Lidar is an important sensor of the autonomous driving system to detect environmental
obstacles, but the spatial distribution of its point cloud is non-uniform because of the …
obstacles, but the spatial distribution of its point cloud is non-uniform because of the …
An automatic lane marking detection method with low-density roadside LiDAR data
Lane information is an essential part of high-resolution micro-traffic data (HRMTD). Most of
the lane detection algorithms for Light Detection and Ranging (LiDAR) are applied to high …
the lane detection algorithms for Light Detection and Ranging (LiDAR) are applied to high …
A survey and framework of cooperative perception: From heterogeneous singleton to hierarchical cooperation
Perceiving the environment is one of the most fundamental keys to enabling Cooperative
Driving Automation, which is regarded as the revolutionary solution to addressing the safety …
Driving Automation, which is regarded as the revolutionary solution to addressing the safety …
LiDAR-enhanced connected infrastructures sensing and broadcasting high-resolution traffic information serving smart cities
Connected-vehicle system is an important component of smart cities. The complete benefits
of connected-vehicle technologies need the real-time information of all vehicles and other …
of connected-vehicle technologies need the real-time information of all vehicles and other …
Vehicle detection under adverse weather from roadside LiDAR data
Roadside light detection and ranging (LiDAR) is an emerging traffic data collection device
and has recently been deployed in different transportation areas. The current data …
and has recently been deployed in different transportation areas. The current data …
Roadside lidar vehicle detection and tracking using range and intensity background subtraction
In this study, we developed the solution of roadside LiDAR object detection using a
combination of two unsupervised learning algorithms. The 3D point clouds are firstly …
combination of two unsupervised learning algorithms. The 3D point clouds are firstly …