Institute for Future Mobility

Digitization

Advancing connectivity and computation to enable safety and efficiency

Sabrullah Deniz works with a drone carrying a first-aid kit on the lawn outside Ayres Hall.
Lee Han speaks to PhD candidates Yangsong Gu and Diyi Liu about the content displayed on a wall of monitors showing live TDOT traffic cams and related data.
Close up of hands tinkering with GRANT, a small, autonomous vehicle.

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. 

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—rapidly, reliably, securely, and safely.

Close up of the circuitry inside an autonomous RC car.

UT’s Approach

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

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. Others focus on improving the communication between and controls for components of smart infrastructure such as traffic signals.  

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

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 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.

“Safety and efficiency drive the grand vision behind UT’s 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.”

—Subhadeep Chakraborty, Associate Professor, Mechanical, Aerospace & Biomedical Engineering

Professor Lee Han explains the application of his research involving crowdsourced traffic and road condition data to graduate students Yangsong Gu and Diyi Liu in a lab at the University of Tennessee.
Graduate students Adam Foshie and Charles Rizzo work on autonomous vehicle GRANT (Ground Roaming Autonomous Neuromorphic Targeter) in a neuromorphic computing lab at the University of Tennessee.
Adam Foshie and Charles Rizzo work on autonomous vehicle GRANT (Ground Roaming Autonomous Neuromorphic Targeter) in a neuromorphic computing lab at the University of Tennessee.
An autonomous car as it navigates a temporary track in the Zeanah Engineering Complex at the University of Tennessee.
PhD student Sabrullah Deniz prepares for drone delivery of a first-aid package on the lawn in front of Ayres Hall on August 09, 2023. Photo by Jennie Andrews/Freelance Photographer/University of Tennessee.

Highlights

Asad Khattak and Nastaran Moradloo presenting at a conference

Improving Nighttime Pedestrian Safety

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.

Assistant Professor Zhenbo Wang holds a nano drone in the Autonomous Systems Laboratory in the Nathan W. Dougherty Engineering Building at the University of Tennessee.

Flying Forward

Associate Professor of Mechanical, Aerospace, and Biomedical Engineering Zhenbo Wang, a recipient of the National Science Foundation’s 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.

An Atari 2600 used in an experiment in a lab at the University of Tennessee.

Applying Neuromorphic Computing to Cameras and Detection Devices

Assistant Professor of Electrical Engineering and Computer Science Catherine Schuman works alongside two EECS colleagues, Professor James Plank and Professor Garrett Rose, to improve the speed and efficiency of data computing. Their work has immense implications for our ability to analyze vehicle data in real time.

Read about their research.

Hairong Qi

CAV Technology for the Future

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’s work with UT’s EcoCAR team.

Two hands hold a nano drone with an orange shirt in the background.

Facilities & Initiatives

A number of programs, facilities, and equipment support UT’s mobility digitization research.

The silhouettes of two men viewing graphs of transportation data on large monitors.

Our Researchers

  • Subhadeep Chakraborty.

    Subhadeep Chakraborty

    Associate Professor, Mechanical, Aerospace & Biomedical Engineering

    Coordination of connected autonomous vehicles, signal phase and timing optimization using machine learning

  • Daniel Costinett.

    Daniel Costinett

    Associate Professor, Electrical Engineering & Computer Sciences

    Power electronics for electric vehicles

  • Aly Fathy.

    Aly Fathy

    Professor, Electrical Engineering & Computer Science

    Electrical energy storage, batteries, lightweight materials

  • Kevin Heaslip.

    Kevin Heaslip

    Director of Center for Transportation Research, Professor, Civil & Environmental Engineering

    Future transportation concepts (electrified connected automated transportation), transportation operations (freeway, transit, and integrated corridor management), and cybersecurity (transportation and critical infrastructure)

  • Michael Jantz.

    Michael Jantz

    Associate Professor, Electrical Engineering & Computer Science

    Virtual machines, operating systems, compilers, program optimization, performance and power efficiency

  • Computer illustration of a human wearing a lab coat with a power T the pocket.

    Asad Khattak

    Beaman Distinguished Professor, Civil & Environmental Engineering

    Intelligent transportation technologies, transportation safety, sustainable transportation

  • Weizi Li.

    Weizi Li

    Assistant Professor, Electrical Engineering & Computer Science

    Intelligent transportation systems, robotics, machine learning (reinforcement learning), multi-agent simulation/systems, smart city, socio-technical systems

  • James Plank.

    James Plank

    Professor, Electrical Engineering & Computer Science

    Fault-tolerance, erasure codes, storage systems, distributed computing, operating systems

  • Hairong Qi.

    Hairong Qi

    Gonzalez Family Professor, Electrical Engineering & Computer Science

    Image processing, computer vision and machine learning, collaborative information processing in sensor networks

  • Garrett Rose.

    Garrett Rose

    Associate Department Head & Professor, Electrical Engineering & Computer Science

    Nanoelectric circuit design, memristors and memristive systems, emerging nanoelectronic computer architectures, hardware security and security implications of emerging computing systems, neuromorphic computing

  • Catherine Schuman stands in front of a whiteboard with formulas written on it.

    Catherine Schuman

    Assistant Professor, Electrical Engineering & Computer Science

    Neuromorphic computing, smart transportation, smart infrastructure, autonomous vehicles

  • Jinyuan Stella Sun.

    Jinyuan (Stella) Sun

    Professor, Electrical Engineering & Computer Science

    Security and privacy in wired/wireless networks and critical application systems

  • Zhenbo Wang.

    Zhenbo Wang

    Assistant Professor, Mechanical, Aerospace & Biomedical Engineering

    Optimal control; convex optimization; machine learning; guidance, navigation, and control; space systems; aerial vehicles; connected vehicles

See all Digitization Faculty