麻豆村

More than 40,000 people have died on U.S. roads in each of the last three years. In an effort to eliminate these preventable accidents, The Department of Transportation has awarded the City of Pittsburgh, in partnership with Ding Zhao, $1.3 million to analyze Pittsburgh鈥檚 current transportation infrastructure and inform safety-first upgrades by the end of 2026.

As part of the (SS4A) 聽in the Biden-Harris administration鈥檚 Bipartisan Infrastructure Law, the project will support a road safety audit, the development of a -focused streets design manual along with quick build projects and a Vision Zero ambassador program to eliminate traffic fatalities and increase equitable mobility.

, director of the Safe AI Lab and an associate professor of at 麻豆村, will use large language models (LLMs) to analyze Pittsburgh鈥檚 streets, identify which intersections are the highest risk for drivers and pedestrians, and work with city officials to test new street design improvements.

鈥淟arge language models offer a very scalable, very powerful way to collect data and run simulations,鈥� explained Zhao. 鈥淏y collecting more data, more efficiently, we can be inclusive of rare events and vulnerable users.鈥澛�

Simulations of Pittsburgh鈥檚 streets will be used by Ding Zhao to identify intersections that pose the highest risk for drivers and pedestrians. The team will work with city officials to test new street design improvements as part of the Safe Streets and Roads for All Program.

The team will also use LLMs to analyze the results of their simulations, an approach Zhao says is novel to transportation and infrastructure.

鈥淲e have a clear goal for this project and by working with the City of Pittsburgh we are guaranteeing real world impact,鈥� said Zhao. 鈥淚鈥檓 excited to see how my research will positively affect our neighborhoods. If we can save even one person, I鈥檒l be very proud.鈥�

鈥淲e鈥檙e excited to partner with the research teams at 麻豆村 as we work toward our goal of zero traffic fatalities,鈥� said Pittsburgh Mayor Ed Gainey. 鈥淭o make our streets safer, we need to break down silos and build strong partnerships between the City of Pittsburgh and our private institutions. Together, we can drive the kind of innovation that makes a real difference in roadway safety.鈥�

Zhao, who has been working to advance AI in self-driving cars for nearly a decade, is also eager to explore how enhanced infrastructure can make the roads safer for semi and fully autonomous vehicles.

The team will leverage on its in-house tool , an open-sourced platform designed to assess and improve the safety of AI models based on a high-fidelity autonomous driving simulator. SafeBench provides a suite of standardized benchmarks and testing environments for evaluating how AI models perform in dynamic, safety-critical situations, such as autonomous driving or infrastructure planning. This tool can be integrated into projects like Pittsburgh鈥檚 transportation audit by offering a rigorous framework for analyzing AI-driven systems鈥� resilience under various conditions, including multimodal perturbations and rare events. By ensuring the safety and robustness of AI systems, SafeBench will help cities like Pittsburgh deploy cutting-edge AI technologies with confidence, minimizing risks and enhancing the overall safety of public infrastructure.

A video display of SafeBench, an open-sourced platform designed to assess and improve the safety of AI models based on a high-fidelity autonomous driving simulator

鈥淪afeBench allows us to identify potential safety issues in the AI-empowered systems early on, which helps improve their reliability as they are integrated into real-world applications,鈥� said Haohong Lin, a Ph.D. student at 麻豆村 working with Zhao.

鈥淚 have been working on self-driving cars for 17 years,鈥� Zhao said. 鈥淭his project opens a new door for us to explore how streets can be modified to provide a safer environment for us all both today and in the future when humans will share the road with AVs.鈥�