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TMA (track mounted attenuators) involved work zones safety analysis and modeling, using machine learning to predict crash severity and crash frequency in the state of Missouri
(University of Missouri--Columbia, 2018)
, and through those recorded crash reports, combine using MWZs working schedules, figure out which factors and under which situations are common exist through all recorded crash both in MWZs and SWZs. Differential analysis model was explored and built...
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 ...
Edge computing - enabled road condition monitoring : system development and evaluation
(University of Missouri--Columbia, 2023)
. In terms of the ability to classify the IRI of pavement segments based on ride quality according to MAP-21 criteria, our proposed device achieved an average accuracy of 96.76 percent on I-70EB and 63.15 percent on South Providence (MO-163). Overall, our...
AI-based framework for automatically extracting high-low features from NDS data to understand driver behavior
(University of Missouri--Columbia, 2022)
Our ability to detect and characterize unsafe driving behaviors in naturalistic driving environments and associate them with road crashes will be a significant step toward developing effective crash countermeasures. Due ...
Automated conflation framework for integrating transportation big datasets
(University of Missouri--Columbia, 2019)
The constant merging of the data, commonly known as Conflation, from various sources, has been a vital part for any phase of development, be it planning, governing the existing system or to study the effects of any ...
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 ...
TMA (Truck Mounted Attenuators) alert system-development and testing
(University of Missouri--Columbia, 2022)
Truck Mounted Attenuators (TMAs) play a crucial role in safety of work zones as they decrease the impact of the crashes, reduce fatalities and injuries, and increase safety. However, there are almost no solid solutions to ...
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 ...