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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 ...
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 ...