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PUBLICATIONS

Big Data in Traffic Safety Analytics

Leverage massive amounts of data from multiple sources such as GPS, Wi-Fi and Bluetooth devices, traffic cameras, connected vehicles, and crowdsensing to discover new opportunities in traffic safety analytics.

Spatiotemporal Modeling of Transportation-related Data

Transportation-related data is generally spatially and/or temporally correlated. We focus on the development of statistical models that can appropriately account for the spatiotemporal dependence of transportation-related data and to make more reliable inferences.

Machine Learning in Transportation

Increased computational power and availability of the massive amount of data have underlined the value of the machine learning algorithms for addressing the emerging challenges in transportation systems.

Resilience of Transportation Systems  

 

 Over the years, we have seen that extreme weather events such as hurricanes are becoming more frequent and severe. Great efforts are expected to mitigate the impacts of extreme weather events, adapt to adverse situations through effective emergency management, and develop operational plans for fast recovery after disruptions. 

Analysis, Modeling, and Prevention of Secondary Crashes

 

Secondary crashes or crashes that occur within the boundaries of the impact area of prior, primary crashes are one of the incident types that frequently affect highway traffic operations and safety. Our studies explored the mechanisms of secondary crashes and provided insights into preventing secondary crashes and mitigating their impacts. 

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