California State Polytechnic University, Pomona

Spatiotemporal Heterogeneous Change of Travel Behavior during Wildfires in California

California suffers from frequent and intense wildfires every year due to its unique weather patterns and dense, flammable vegetation. Wildfires often cause significant infrastructure damage, disrupt roadway networks, interrupt business operations, and generate hazardous smoke, all of which can deteriorate the driving environment, elevate perceived safety risks, limit individuals’ ability to meet daily work-life demands, […]

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Vehicle Edge Computing for Travel Behavior and Demand in Future Intelligent Transportation Systems (ITS)

Meeting the diverse needs of stakeholders such as passengers, drivers, and service providers is imperative. Modern travelers seek real-time updates and personalized journey experiences. Drivers need consolidated data for safety and punctuality (Chen et al., 2021), while service providers rely on data analytics to optimize resources and enhance reliability (Wang et al., 2020). Traditional centralized

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Travel Behavior Data (TBD) Hub

In an era characterized by transformative shifts in demographics, lifestyles, work patterns, technological advances, societal values, and climate and environmental conditions, decision-makers are now confronted with ever-increasing, multifaceted uncertainties. The TBD National Center has launched a flagship initiative, called the TBD Hub, to provide transportation decision-makers information and deep insights about the state of the

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Deep Learning with LiDAR Point Cloud Data for Automatic Roadway Health Monitoring

Traditional methods for monitoring road conditions are fraught with challenges. Field inspections are labor-intensive and costly, aerial photography is subjective, and mobile measurement systems (MMS) require substantial investment in geospatial technology. In response to these limitations, there is a growing interest in leveraging advanced 3D scanning technologies, such as LiDAR and RGB-D scanners, in conjunction

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