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Interactive, multi-purpose traffic prediction platform using connected vehicles dataset
(University of Missouri--Columbia, 2022)
Traffic congestion is a perennial issue because of the increasing traffic demand yet limited budget for maintaining current transportation infrastructure; let alone expanding them. Many congestion management techniques ...
Artificial intelligence enabled automatic traffic monitoring system
(University of Missouri--Columbia, 2019)
The rapid advancement in the field of machine learning and high-performance computing have highly augmented the scope of video-based traffic monitoring systems. In this study, an automatic traffic monitoring system is ...
AI-based framework for automatically extracting high-low features from NDS data to understand driver behavior
(University of Missouri--Columbia, 2022)
detection methods formulate the problem as a pure classification problem, assuming a discretized input signal with known start and end locations for each event or segment. In practice, however, vehicle telemetry data used for detecting driver maneuvers...
Edge computing - enabled road condition monitoring : system development and evaluation
(University of Missouri--Columbia, 2023)
[EMBARGOED UNTIL 8/1/2024] Real-time pavement condition monitoring provides highway agencies with timely and accurate information that could form the basis of pavement maintenance and rehabilitation policies. Existing ...
Detection and quantification of delamination in concrete via time-lapse thermography with machine learning
(University of Missouri--Columbia, 2021)
This study developed a framework to automatically extract sub-surface defects from time-lapse thermography (TLT) images of reinforced concrete bridge components. Traditional approaches for processing TLT data typically ...