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Active Traffic Signal Operations Optimization

A cornerstone of the program is its long-term collaboration with the Regional Transportation Commission of Washoe County to optimize traffic signal operations throughout the Reno-Sparks metropolitan area. Led by Professor Zong Tian, this initiative engages student researchers in managing the timing of more than 400 traffic signals using advanced big-data analytics and hardware-in-the-loop simulation technologies.

"Our goal is to not only enhance safety and efficiency for all road users but also explore readily implementable innovation and equip students with hands-on experience in real-world problem solving."— Professor Zong Tian

The work has proven especially valuable during heavy construction along the 395/580 freeway corridor, where timely signal-timing adjustments have helped maintain flow and reduce delays. By leveraging real-time vehicle trajectory data, the team has minimized commuter travel delays and produced insights that can be adapted by transportation agencies nationwide.

Next-Generation Traffic Sensing Technologies

Professor Hao Xu's research group has pioneered the use of LiDAR-based sensing systems to advance data collection on vehicle movements and pedestrian behavior. The team has deployed roadside sensors at key intersections in northern and southern Nevada to continuously gather data, helping identify patterns that contribute to roadway incidents and risks to vulnerable road users.

"Our work empowers the implementation of emerging technologies to capture detailed interactions of all traffic on roads — from vehicular speeds to pedestrian crossings — which are essential for developing safer and smarter road environments."— Professor Hao Xu

These efforts support real-world practices in Nevada and across the nation, including the City of Reno's Micromobility Pilot Project, by providing data that informs infrastructure improvements and policy decisions.

Safety in School Zones and Rural Highways

Under the leadership of Associate Professor Seri Park, a series of studies are underway to evaluate and enhance safety measures in school zones and along rural highways. The team employs advanced driving-simulation technology to examine driver behavior in rural settings, including along US-95 in Nye County.

"Our analysis of speed patterns in school zones has revealed significant safety concerns, particularly during peak school hours."— Associate Professor Seri Park

By combining rigorous field data with simulation-based analyses, the team generates actionable recommendations for improving enforcement strategies and designing safer road environments — informing both local policy and the national dialogue on traffic safety best practices.

AI and Multisource Data for Transportation Policy

Two major grants from the U.S. Department of Transportation's Safe Streets and Roads for All (SS4A) program — totaling more than $5 million — are driving projects that integrate artificial intelligence and multisource traffic data with traffic signal operations and "safe routes to school" planning. Additional funding from the California Department of Transportation supports studies into high-occupancy vehicle (HOV) lane performance using emerging high-resolution telemetric data.