{"id":44545,"date":"2022-08-12T10:39:16","date_gmt":"2022-08-12T14:39:16","guid":{"rendered":"https:\/\/blogarchive.utc.edu\/news\/?p=44545"},"modified":"2023-08-30T21:23:22","modified_gmt":"2023-08-31T01:23:22","slug":"largest-federal-dot-grant-in-utc-history-to-make-downtown-chattanooga-an-electric-vehicle-testbed","status":"publish","type":"post","link":"https:\/\/blogarchive.utc.edu\/news\/2022\/08\/largest-federal-dot-grant-in-utc-history-to-make-downtown-chattanooga-an-electric-vehicle-testbed\/","title":{"rendered":"Largest federal DOT grant in UTC history to make downtown Chattanooga an electric vehicle testbed"},"content":{"rendered":"
\"Aerial

Downtown Chattanooga will act as a \u201cliving testbed,\u201d connecting electric vehicles to customized charging opportunities considering traffic conditions and electric grid status, thanks to a historic U.S. Department of Transportation grant award. Photo by Angela Foster.<\/p><\/div>\n

Chattanooga will be home to the nation\u2019s largest electric vehicle \u201cliving testbed,\u201d thanks to $9.2 million in funding for a project proposed by the city and scientists at the University of Tennessee at Chattanooga with municipal, private industry and research partners.<\/p>\n

Funding will come from a $4.5-million U.S. Department of Transportation grant award\u2014the single-largest of its kind in UTC history\u2014announced this week and another $4.7 million from industry partners, UTC, Chattanooga city government and EPB.<\/p>\n

The winning Chattanooga proposal is for a networked system that will enable electric vehicle drivers to more readily locate charging stations. Charging opportunities will be customized for drivers as a result of the system recognizing the charge level of individual electric vehicles, volume and pace of traffic and electric grid power demand to recommend charging stations and types by locations.<\/p>\n

The proposal was submitted by Chattanooga\u2019s Smart City program and its development was led by Osama Osman, Chief Scientist and Smart Transportation Thrust Lead for UTC\u2019s Center for Urban Informatics and Progress (CUIP)<\/a><\/strong> and CUIP Founding Director Mina Sartipi, also Guerry Professor in the UTC Department of Computer Science and Engineering.<\/p>\n

\u201cThis award is a game changer,\u201d Osman said. \u201cIt will transform Chattanooga into a living testbed for all sorts of smart transportation technologies, making the city a leader in EV deployment and EV charging management and set the stage for more transformation yet to come.<\/p>\n

\u201cThe idea is to connect EV users to customized charging opportunities considering traffic conditions and electric grid status\u2014customized in the sense of the charging station type, such as \u2018fast\u2019\u2014and location to be recommended to an EV user based on their current charge, how much time they have, real-time traffic status, and state of the electric grid.\u201d<\/p>\n

Chattanooga is the only Tennessee site awarded one of the 10 U.S. DOT grants totaling $45.2 million. All funded projects involve the use of advanced intelligent transportation systems technologies that will improve mobility and safety, provide multimodal transportation options and support underserved communities, according to DOT.<\/p>\n

Funding for the Chattanooga project will implement the technology needed to help drivers locate and recommend electrical vehicle charging stations.<\/p>\n

Sartipi said the proposal, titled \u201cEnd-to-End Decision Support System for Integrated Smart Electric Grid and Transportation System Management,\u201d is based on \u201ca three-year plan.\u201d<\/p>\n

\u201cIn the first year, we will develop the architecture and the ConOps as well as the procurement of the devices,\u201d Sartipi said. \u201cIn the second year, we will install and test the equipment. Relevant algorithms will be developed and baselines will be established. During the third year, we will collect data, analyze it and measure the impact.\u201d<\/p>\n

The\u00a0smart city test bed UTC established in 2019 along M.L. King Boulevard is a starting point, Sartipi said. Its use of cameras and sensors has yielded anonymous data for vehicle traffic, pedestrians and bicyclists.<\/p>\n

\u201cThis grant will not only expand the footprint of the testbed, but it also brings EVs and their charging needs into the picture,\u201d Sartipi said.<\/p>\n

\u201cThe state of Tennessee plans to have 200,000 EVs on the road by 2028. As we scale, the equity and inclusion must be considered to equalize the accessibility of the\u00a0charging stations. This proposal will help to understand the challenges and opportunities in all neighborhoods with EV charging and traffic management in a mid-size city.\u201d<\/p>\n

CUIP Testbed Manager Austin Harris, UTC Assistant Professor of Electrical Engineering Vahid Disfani and UTC Professor of Civil Engineering Ignatius Fomunung are key contributors to the project. Collaborators included experts from the Colorado School of Mines and industry partners Ouster, Seoul Robotics, Cubic, Iteris, Applied Information and Temple.<\/p>\n

More information: Read the U.S. DOT Federal Highway Administration press release<\/strong><\/a>.<\/p>\n

Learn More<\/h4>\n

Visit UTC<\/a><\/p>\n

UTC Center for Urban Informatics and Progress<\/a><\/p>\n

UTC Research Institute<\/a><\/p>\n

College of Engineering and Computer Science <\/a><\/p>\n

Dr. Mina Sartipi\u00a0<\/a><\/p>\n

Inventor Spotlight: Mina Sartipi<\/a><\/p>\n

Chattanooga Smart City Plan<\/a><\/p>\n

U.S. Department of Transportation Smart City Challenge<\/a><\/p>\n

City of Chattanooga Smart City Division<\/a><\/p>\n

How to apply<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The winning Chattanooga proposal is for a networked system that will enable electric vehicle drivers to more readily locate charging stations. Charging opportunities will be customized for drivers as a result of the system recognizing the charge level of individual electric vehicles, volume and pace of traffic and electric grid power demand to recommend charging stations and types by locations.<\/p>\n

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