Case Study: Iowa State University improves road safety and traffic efficiency with Google for Education TensorFlow

Iowa State researchers use machine learning to improve road safety and efficiency

Iowa State University partnered with Google for Education to help the Iowa Department of Transportation tackle a major road-safety challenge: managing and interpreting huge volumes of real-time traffic data across Iowa’s 115,000-mile roadway system. With winter weather, crashes, and changing road conditions creating constant operational pressure, the team needed a faster way to analyze data from cameras, sensors, GPS devices, and snow plows to support better decision-making.

Using Google’s TensorFlow machine-learning platform, researchers at Iowa State’s Institute of Transportation built models to analyze traffic flow, detect crashes from camera images, identify congestion patterns, and help predict incidents more quickly. The solution improved the DOT’s ability to alert responders and commuters faster, making Iowa roadways safer and more efficient while enabling more predictive traffic operations.

Iowa State University

Neal Hawkins

Associate Director of the Institute of Transportation