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Found 5 papers, 1 papers with code
Deep Learning Frameworks for Pavement Distress Classification: A Comparative Analysis
In this study, the authors deploy state-of-the-art deep learning algorithms based on different network backbones to detect and characterize pavement distresses.
Artificial Intelligence Enabled Traffic Monitoring System
Real-time object detection algorithms coupled with different tracking systems are deployed to automatically detect stranded vehicles as well as perform vehicular counts.
AI-Based Framework for Understanding Car Following Behaviors of Drivers in A Naturalistic Driving Environment
Furthermore, most studies are restricted to modeling the ego vehicle's acceleration, which is insufficient to explain the behavior of the ego vehicle.
DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving Videos
Identifying unusual driving behaviors exhibited by drivers during driving is essential for understanding driver behavior and the underlying causes of crashes.
Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras
This study implements a three-stage video analytics framework for extracting high-resolution traffic data such vehicle counts, speed, and acceleration from infrastructure-mounted CCTV cameras.
