Communications of the ACM
Virginia Tech Researchers Devise Traffic App to Rival Weather Apps
Researchers at the Transportation Institute of Virginia Polytechnic Institute and State University are working to develop a cloud-based traffic app that will be able to predict when and where traffic is likely to occur.
Credit: University of California, San Diego
Researchers at the Virginia Polytechnic Institute and State University's (Virginia Tech) Transportation Institute are developing a cloud-based application that will use real-time information and historical data to predict when and where traffic is likely to occur.
The app is based on an algorithm that combines historical and real-time data to predict traffic patterns and congestion.
Virginia Tech Ph.D. candidate Hao Chen says typical mapping applications rely on mileage and speed limits to predict travel times, but they are very unreliable. "Most people think traffic prediction has been implemented, used long ago, but it's actually new," Chen says. "We can provide on average 95-percent prediction accuracy for travel time."
One of the major challenges in developing the app was managing the massive amount of information that is needed to create accurate predictions. The researchers overcame that obstacle using cloud computing. "The cloud computes the answer and then ships it back to your phone or laptop," says Virginia Tech professor Wu Feng. "The big data simply remains in the cloud."
From Computerworld
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