Carnegie Mellon Professor Combating Potholes With Technology
Potholes. They are the scourge of the daily commute. If you live in an area that does not experience a lot, good for you. But in places like New England or Detroit, it is a constant battle. But one scientist is trying to take on potholes with technology. According to the public radio program, Marketplace, Carnegie Mellon University and the city of Pittsburg are teaming up on a project to find better ways to identify and even predict potholes. The projects is being spearheaded by Christop Mertz, working with Traffic21, a division of the university dedicated to finding real-world solutions to problems that plague the transportation infrastructure. RELATED: UK To Test Wireless Charging Roads Mertz is using a computer program he designed that looks at photos of the street to detect cracks in the pavement. The photos are taken from his own car driving around the city, but also from cameras placed in three city vehicles.
Like most cities, Pittsburg manually records potholes on city streets. The three inspectors have other responsibilities, and also use their eyes, resulting in potentially subjective reporting. It takes the inspectors four to five years to get through the 1,100 miles of city streets. The observations are punched into a pavement management system to predict what sections need the most work. By the time they are finished, much of that data could be out of date, due to further cracking and years of frost heaves. This is a pretty common model for public works departments across the country.
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Mertz system can record any street it drives on, and then the data is ranked as green, yellow, or red, based on the quality of the road surface. The data takes a few days to process and then provides a predictive model for the potential of potholes in cracks. For city planners that means being able to more accurately provide money and resources to those tasked with repairing the city streets.
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The program is not without its bugs. At the moment, data has to be transferred manually, and sometimes cannot distinguish shadows from road wear. But as this program evolves and becomes more functional, it can serve as a model for northern cities which in a constant battle with mother nature to keep their roads smooth and safe.