Machine Vision System Spots Roadways in Need of Repair

Founded in 2016, Roadbotics is based on a machine vision technology developed at Carnegie Mellon University. Using footage collected from windshield-mounted cameras on cars driving through a road network, the computer vision algorithm has been trained to recognize flaws in road surfaces, including cracks, potholes and spalling. Geotagged road locations are rated on a five-color scale, and the data is collected into a map file that can be loaded into popular GIS imaging software.

“Normally this is a time-consuming and costly process,” says Ben Schmidt, Roadbotics CTO. “Here, we snap our fingers and there’s a comprehensive view of your road network.”

One of Roadbotics’ first customers was Ryan Fonzi, associate planning director for North Huntingdon Township, Pa., who needed a faster way to track the 160 miles of road under his supervision. “Their data was important for us—we can pull up conditions in certain wards. We have an unbalanced situation here where some wards are in better or worse shape, but now we can look at it township-wide,” he explains. “We have the data to help us make smarter decisions.”