{"id":349,"date":"2023-01-13T12:31:12","date_gmt":"2023-01-13T17:31:12","guid":{"rendered":"https:\/\/research-multi-dev.utk.edu\/energy-dev\/?page_id=349"},"modified":"2026-04-22T08:25:54","modified_gmt":"2026-04-22T12:25:54","slug":"digitization","status":"publish","type":"page","link":"https:\/\/research.utk.edu\/mobility\/research-areas\/digitization\/","title":{"rendered":"Digitization"},"content":{"rendered":"\n
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Digitization<\/h1>\n\n\n\n

Advancing connectivity and computation to enable safety and efficiency<\/em><\/p>\n<\/div>

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UT research in digitization helps build a future in which connected and automated vehicles and smart infrastructure work together seamlessly to optimize vehicle performance, keep traffic flowing smoothly, and protect people in and around vehicles. <\/p>\n\n\n\n

The automation of transportation requires capabilities to harness and manage tremendous amounts of data. We are developing new communication and computing technologies that will enable vehicles to generate, analyze, and act on the right data\u2014rapidly, reliably, securely, and safely.<\/p>\n<\/div>\n\n\n\n

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UT’s Approach<\/h2>\n\n\n\n

Improving driver and pedestrian safety is a key part of our digitization research. Faculty and graduate students diagnose and predict autonomous vehicle safety parameters<\/a>, calibrate car-following models<\/a>, investigate patterns and edge cases in accident scenarios<\/a> with automated vehicles, and improve underlying algorithms<\/a> to guide vehicle actions in different contexts. UT faculty also address the security vulnerabilities of connected mobility using techniques such as blockchain<\/a> to enhance threat detection and defense. <\/p>\n\n\n\n

UT researchers in Knoxville and Chattanooga have supported the Tennessee Department of Transportation in developing strategies related to intelligent mobility, including infrastructure and vehicular communications<\/a>. Others focus on improving the communication between and controls for components of smart infrastructure such as traffic signals<\/a>.  <\/p>\n\n\n\n

UT faculty and students are also exploring technologies that have promising mobility applications, such as artificial intelligence<\/a>, machine learning<\/a>, and neuromorphic computing<\/a>. Others are exploring how to increase energy efficiency in high-performance computing<\/a> for connected devices.<\/p>\n\n\n\n

UT is one of only six universities in the United States to advance research initiatives in collaboration with AT&T. Our faculty and students use the state-of-the-art AT&T 5G Lab<\/a> located at the UT Research Park to explore cutting-edge solutions for connected mobility, including near-real-time decision-making and control of vehicles, traffic monitoring, network optimization, and secure 5G communications for transportation systems.<\/p>\n\n\n\n

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Safety and efficiency drive the grand vision behind UT\u2019s digitization research. Building this vision requires cross-discipline collaboration. My work brings together mechanical engineering and computer vision, hardware and software and statistical data analysis.\u201d<\/h2>\n\n\n\n
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Subhadeep Chakraborty, Associate Professor, Mechanical, Aerospace & Biomedical Engineering<\/em><\/p>\n<\/blockquote>\n<\/div>\n<\/div>\n\n\n\n

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Highlights<\/h2>\n\n\n\n
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Improving Nighttime Pedestrian Safety<\/a><\/strong><\/h3>\n\n\n\n

UT researchers studied the nighttime performance of pedestrian automatic emergency braking systems. Their findings have implications for the algorithms that support these systems and for other vehicle technologies such as cameras and radar systems.

Learn more about this research.<\/a>

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Flying Forward<\/strong><\/a><\/h3>\n\n\n\n

Associate Professor of Mechanical, Aerospace, and Biomedical Engineering Zhenbo Wang, a recipient of the National Science Foundation\u2019s CAREER award, is researching novel airway infrastructure, operations, and controls for autonomous aircraft. His work will help facilitate autonomous control, real-time optimization, and optimal decision-making.

Envision the future of air travel.<\/a>
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Schuman\u2019s Team Controls Tricky Engines with Neuromorphic Network<\/a><\/strong><\/h3>\n\n\n\n

Assistant Professor of Electrical Engineering and Computer Science Catherine Schuman her graduate students, and their collaborators at ORNL have been working on a neuromorphic (biological brain-inspired) computing system that determines the best fuel injection parameters at a lower power cost than competing models.

Read about their research.<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

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CAV Technology for the Future<\/strong><\/a><\/h3>\n\n\n\n

Gonzalez Family Professor of Electrical Engineering and Computer Science Hairong Qi introduces UT students to the future of connected automated vehicles and the need for ever-improving computer vision technologies. 

Read about Qi\u2019s work with UT\u2019s EcoCAR team.<\/a>

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Facilities & Initiatives<\/h2>\n\n\n\n

A number of programs, facilities, and equipment support UT\u2019s mobility digitization research.<\/p>\n\n\n\n