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In recent years, transportation agencies have increasingly turned to machine learning (ML) to enhance the effectiveness of infrastructure asset management. However, limited local inventory data often hinders building accurate and reliable ML models. Additionally, data privacy and ownership concerns discourage...

This report presents several advancements in the empirical modeling of liquefaction-induced lateral spread. It starts with a newly collected dataset of 5,560 historical lateral spread displacement vectors, a sample size over 10 times larger than the existing databases and subsurface data comprising over...

Adverse weather has long been recognized as one of the major causes of motor vehicle crashes due to its negative impact on visibility and road surface. Providing drivers with real-time weather information is therefore extremely important to ensure safe driving in adverse weather. However, identification...

This research examines a range of incident detection technologies to determine a recommended combination of approaches for use in the Utah Department of Transportation (UDOT) Advanced Traffic Management System (ATMS). The technologies that were examined are computer-based Automatic Incident Detection...