The University of Connecticut’s Connecticut Transportation Institute (CTI) has been awarded a $10.4 million, five-year grant (2025–2030) by the Federal Highway Administration (FHWA) and the Connecticut Department of Transportation (CTDOT) to advance roadway safety through cutting-edge, data-driven research.
The grant, led by Kai Wang, Ph.D. (Assistant Research Professor, Project Manager, CTI) as Principal Investigator, with Eric Jackson, Ph.D. (Research Professor, Executive Director, CTI) as Co-PI, will fund the expansion and automation of the Connecticut Roadway Safety Management System (CRSMS) platform. The project will also provide expanded analytical and technical support to CTDOT.
“This grant represents a significant investment in our work and a strong endorsement of the impact our team continues to make in advancing data-driven roadway safety efforts across the state,” said Dr. Wang.
Harnessing AI for Safer Roads
The initiative will integrate modern AI technologies like computer vision, machine learning and deep learning, natural language processing, and large language models into real-time traffic operations and safety analysis for Connecticut. These advancements will help identify high-risk areas, track traffic patterns, and inform evidence-based policy changes that improve roadway safety for all.
The project also opens opportunities for interdisciplinary collaboration between CTI and other UConn College of Engineering departments, strengthening research at the intersection of artificial intelligence, transportation, and public safety.
Expanding Research Capacity
The grant will support 11 current full-time employees at CTI and fund an additional six full-time employees and graduate assistants. This investment in personnel underscores the state and federal commitment to both research innovation and workforce development in transportation safety.
About Dr. Kai Wang:
Dr. Wang received his Ph.D. in Transportation & Urban Engineering from UConn in 2016, along with Master’s degrees in Transportation Engineering (South Dakota State University) and Computational Data Analytics (Georgia Institute of Technology). Since joining CTI in 2016, he has led numerous projects funded by FHWA, USDOT, NCHRP, and state DOTs, securing more than $23 million in funding as PI or Co-PI. His work applies statistical modeling, machine learning, and big data technologies to deliver practical, real-world solutions that improve roadway safety and infrastructure development.
