Data-driven methods have shown promising results in structural health monitoring (SHM)
applications. However, most of these approaches rely on the ideal dataset assumption and …

We present a novel perspective on how connected vehicles can reduce total vehicular delay
arising due to the capacity drop phenomenon observed at fixed freeway bottlenecks. We …

Traffic flow modeling is typically performed at one of three different scales (microscopic,
mesoscopic, or macroscopic), each with distinct modeling approaches. Recent works that …

In an era where data volume is growing exponentially, effective data management
techniques are more crucial than ever. Traditional methods typically manage the size of …

Recent works have attempted to use deep learning to predict future states of traffic flow, but
have met with mixed results. These approaches face two key challenges. First, training deep …

Emergent behaviors in complex systems arise due to the numerous local interactions that
occur between large numbers of individual agents. The observation and quantification of …