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September 24, 2020 | Tom Ballard

DOE awards major grant to consortium led by UTC that will leverage Chattanooga’s smart corridor

The U.S. Department of Energy has awarded a $1.89 million grant to a consortium coordinated by the University of Tennessee at Chattanooga (UTC) to create a new model for traffic intersections that reduces energy consumption.

UTC’s Center for Urban Informatics and Progress (CUIP) will lead the group that will leverage its existing smart corridor to accommodate the new research. Partners include the University of Pittsburgh, Georgia Institute of Technology, Oak Ridge National Laboratory (ORNL), and the City of Chattanooga.

“This project is a huge opportunity for us,” says Mina Sartipi, CUIP Director and Principal Investigator. “Collaborating with the City of Chattanooga and working with Georgia Tech, Pitt, and ORNL on a project that is future-oriented, novel, and full of potential is exciting. This work will contribute to the existing body of literature and lead the way for future research. Our existing infrastructure, the MLK Smart Corridor, will be the cornerstone for this work, as it gives us a precedent for applied research—research with real-world nuance.”

The project will leverage the capabilities of connected vehicles and infrastructures to optimize and manage traffic flow. The researchers note that while adaptive traffic control systems (ATCS) have been in use for a half century to improve mobility and traffic efficiency, they weren’t designed to address fuel consumption and emissions. Likewise, while automobile and vehicle standards have increased significantly, their potential for greater improvement is hampered by inefficient traffic systems that increase idling time and stop-and-go traffic. Finding a solution is paramount since the National Transportation Operations Coalition graded the state of the nation’s traffic signals as D+.3

The goal of the project that will extend a little more than three years is to develop a dynamic feedback Ecological ATCS (Eco-ATCS) which reduces fuel consumption and greenhouse gases while maintaining a highly operable and safe transportation environment. The integration of AI will allow additional infrastructure enhancements including emergency vehicle preemption, transit signal priority, and pedestrian safety. The ultimate goal is to reduce corridor-level fuel consumption by 20 percent.

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