Self-driving cars and “robotaxis” need detailed mappings of the real-world environments they operate in and require massive data for extensive training and testing before they can be deployed. Even with this data, and despite the increasing sophistication of these vehicles, they still can get themselves into tricky situations that require a human driver to fix. This can present compounding traffic problems if there’s no qualified driver near the vehicle. But with all of their sensors and connectivity, why can’t a remote driver take control of the vehicle from afar?
The issue is latency; the time it takes for information to get back and forth between driver and vehicle. Anything less than instantaneous feedback is prohibitively dangerous when operating a two-ton machine, and current cellular networks are not up to the task.
Researchers from the University of Utah’s John and Marcia Price College of Engineering, the University of Minnesota’s College of Science and Engineering, and the University of California, Riverside, in collaboration with researchers from Nokia Bell Labs and GM Research and Development, are working on how remote driving and self-driving can complement each other. By solving the latency problem, remote drivers at tele-operation centers up to hundreds of miles away could take over in situations where self-driving vehicles get stuck, lost, or confused. They could also operate vehicles in remote areas that lack the detailed map data that self-driving modes rely on.
In July 2026, the team demonstrated their work in a real-world setting using Minnesota’s custom CAV (connected and automated vehicle) on Utah’s POWDER mobile and wireless test bed, equipped with the network technologies and end-to-end teleoperation application the team developed.
Their efforts are part of a U.S. National Science Foundation program called Breaking the Low Latency Barrier for Verticals in Next-G Wireless Networks (NSF 24-545). The researchers from Minnesota, Utah, California, Nokia and GM are part of an NSF “Breaking Low” project, funded by the NSF Directorate for Technology, Innovation and Partnerships (NSF TIP), and aptly called DRIVE-SAFE.
“While there were lot of great expectations initially regarding 5G enabling a range of emerging vertical industries, many of them did not take off as hoped partly due to the perception that 5G technology was really not up to meeting their performance requirements,” said Dr. Sudharman K. Jayaweera, Program Director, Emerging Technologies Section, NSF TIP. “The NSF Breaking Low program was motivated by the need for 5G/NextG technology solutions that can verifiably demonstrate specific low-latency performance targets required by a particular wireless vertical application. Remote and cooperative driving is one such use-case in which reliable low-latency connectivity is absolutely critical for it to be viable for mass adoption. DRIVE-SAFE project is an industry and academia collaboration where wireless networking experts work side-by-side with autonomous vehicular technology experts to develop, demonstrate and verify networking technology innovations that meet the specific latency performance needs of remote and cooperative driving under real operating conditions. This project is developing a bold new approach to make NextG networking enable vertical applications, as NSF TIP hoped to achieve from the Breaking Low program.”
Today’s 5G cellular network our phones connect to was designed largely with individual consumers, not vehicles, in mind. Dropped calls or slow upload speeds are annoyances, rather than dealbreakers. The fact that cars are rapidly moving objects exacerbates both problems and creates a new one: hand-offs. Traveling through overlapping coverage zones from multiple cell towers creates opportunities for packets of information to be lost.
“Your car already has a lot of relevant information, like speed and direction, that could help these networks maintain a faster, better connection,” says Kobus Van Der Merwe, the Jay Lepreau Professor in the Kahlert School of Computing and Co-PI of the DRIVE-SAFE project. “Ultimately, we need closed-loop networks, where cars and base stations are talking to each other, so they can take advantage of this information and make better decisions.”
One of the key enablers for the DRIVE-SAFE project is the availability of open source cellular network technologies which allows researchers to explore novel network solutions. One example is the OCUDU project (Open Centralized Unit / Distributed Unit) , the so-called “Linux of [Radio Access Networks]”, which is funded by the FutureG Office within the Office of the Under Secretary of Defense for Research and Engineering. Another example is the Duranta OAI RAN 5G open source stack developed and maintained by the OpenAirInterface Software Alliance. These open source stacks foster the creation of real-world end-to-end solutions, like that created by the DRIVE-SAFE team.
“So many of these types of projects end up in the ‘valley of death’ — great preliminary findings but no ability to turn them into results,” says Zhi-Li Zhang, Distinguished McKnight University Professor and Qwest Chair Professor of the University of Minnesota and Lead PI of the DRIVE-SAFE project. “We’re committed to making teleoperation feasible in the real world.”
In their demonstration, the CAV made several laps of a parking lot on the University of Utah campus, all while being piloted from inside a conference room in the Merrill Engineering Building. Rather than using a commercial 5G network to send information back and forth to the vehicle, the tele-operation station connected to the vehicle via an OCUDU-enabled 5G network instantiated in the POWDER testbed, and enhanced with network technologies developed by the DRIVE-SAFE team.
This setup allowed the DRIVE-SAFE researchers to explore “trajectory-driven network optimization” techniques to reduce the latency typically associated with a mobile network. One trajectory-driven approach the team developed optimizes the handover process essential to any mobile network: In essence, interaction between the tele-operation service and the network allows the network to control the handover process based on the trajectory of the vehicle and thus avoid unnecessary handovers that might add latency or other undesirable network effects. This trajectory-driven approach is in contrast with default handover behavior in today’s 5G networks where cellular devices always switch to a stronger connection when one is available. But that behavior can be counterintuitively counterproductive if the device is a moving car: switching multiple times in succession is worse for latency than staying on a single network, even if it’s not the fastest.
Another approach the team developed is adapting the modulation and coding scheme associated with a wireless link based on its trajectory. That capability, developed by Nokia Bell Labs, is called Semantic-Aware RAN Adaptation, or SARA. For example, rather than reacting to transmission errors after they occur, which is too slow for a moving vehicle, SARA uses the vehicle’s reported position and speed to adjust the link before conditions degrade, and it protects safety-critical driving commands more strictly than the video feed. In the Utah trials, this technology held the teleoperation session together at the edge of cell coverage, where the unmodified network lost the link entirely.
“The vehicle already knows where it is going and how fast. Our contribution makes that information actionable inside the radio scheduler itself,” says Nakjung Choi, project Co-PI and department head at Nokia Bell Labs. “The same mechanism generalizes well past driving. Drones, remote-controlled machinery and industrial automation all need a network that adapts to what the application is doing, and building that in natively is one of the key pillars of upcoming AI-native 6G networks.”
The researchers will demonstrate the DRIVE-SAFE capabilities again in October, kicking off the second year of their project. Plans for the second year include working with the other DRIVE-SAFE partner institutions, University of California, Riverside and GM to explore the feasibility of combining 5G and V2X capabilities to further enhance tele-operated driving.