New York City’s thousands of traffic cameras capture endless hours of footage each day, but analyzing that video to identify safety problems and implement improvements typically requires resources that most transportation agencies don’t have.
Now, researchers at NYU Tandon School of Engineering have developed an artificial intelligence system that can automatically identify collisions and near-misses in existing traffic video by combining language reasoning and visual intelligence, potentially transforming how cities improve road safety without major new investments.
Published in the journal Accident Analysis & Prevention, the research won New York City’s Vision Zero Research Award, an annual recognition of work that aligns with the city’s road safety priorities and offers actionable insights. Professor Kaan Ozbay, the paper’s senior author, presented the study at the eighth annual Research on the Road symposium.








