Traffic crashes remain one of the leading causes of injury and death across communities of all sizes—from dense urban corridors to rural and tribal lands. A central challenge in transportation safety is the inability to anticipate risks before they become deadly. Strengthening that foresight would allow communities to intervene earlier—preventing crashes rather than reacting to them.

Researchers at the University of Utah are tackling this challenge head-on with two newly awarded federal grants that bring advanced artificial intelligence (AI), vehicle-to-everything (V2X) technology, and real-time sensing into transportation safety planning and decision-making.

Just before Christmas Eve, the U.S. Department of Transportation (USDOT) announced nearly $1 billion in funding through its highly competitive Safe Streets and Roads for All (SS4A) grant program. The University of Utah will lead one major award, as well as play a large role in a second project, awarded to support safer streets across Utah and California.

To achieve their goals, both projects will focus specifically on multimodal safety data collection, predictive sensing demonstrations, and real-time alert systems designed to inform future safety investments and policy decisions.

 

Designing Streets That Think Ahead: AI and V2X Powering Predictive Technologies

The University of Utah-led project, “Integrated AI Computing and V2X Infrastructure Systems for Safer Streets,” was awarded $3.99 million in federal funding.

The project’s inventiveness stems from the perceptive shift from reactive safety measures to focusing instead on how we can create predictive technologies that could provide real-time warnings. By integrating AI-powered computing with connected infrastructure, these tools will support the development and update of Comprehensive Safety Action Plans—a cornerstone of the SS4A program—while also demonstrating how emerging technologies can improve outcomes for drivers, pedestrians, cyclists, and transit users.

The University of Utah-led SS4A project is being steered by Cathy Liu (PI) and Chenxi Liu (Co-PI)—both professors in the Department of Civil & Environmental Engineering (CvEEN)—in partnership with public agencies including Utah Department of Transportation, Wasatch Front Regional Council, Salt Lake City, Garfield County, the Trinidad Rancheria, industry partner AIWaysion, and university collaborators at Johns Hopkins University and Rensselaer Polytechnic Institute.

Work will span diverse communities and various transportation settings, including:

  • Salt Lake City
  • Garfield County
  • The Trinidad Rancheria

 

Collaborating on Safety Solutions for Tribal Lands: Protecting Lives Through Real-Time Hazard Detection

The University of Utah is also a key partner on a second SS4A award led by the Cher-Ae Heights Indian Community of the Trinidad Rancheria in California. That project, “Advancing Vision Zero on Tribal Lands through Real-Time Hazard Detection and Behavior Monitoring,” received $1.6 million in funding.

This three-year effort focuses on improving safety along Scenic Drive and five locations on U.S. Highway 101, where landslide risk and traffic behavior pose serious safety challenges. The project will deploy:

  • AI-enabled geotechnical sensors
  • AI-driven landslide alerts
  • Multimodal traffic sensing
  • Intelligent roadside warning systems

Data from these systems will feed into a centralized platform to evaluate outcomes and guide updates to the Tribe’s Comprehensive Safety Action Plan. Represented by CvEEN faculty members Chenxi Liu (PI), Tong Qiu (Co-PI), and Cathy Liu (Co-PI), the University of Utah will serve as a subcontractor on this project.

 

Research Leadership and Collaboration

Together, these projects highlight how interdisciplinary research, strong community partnerships, and emerging technologies can reshape how transportation agencies understand risk—and take action—to save lives.