Integrating Automated Vehicles with 5G Networks to Realize the Future of Transportation
Summary
Widespread deployment of fully automated or “autonomous” vehicles (AVs) that can operate without human interaction would make travel easier, cheaper, and safer. Reaching this highest level of automation requires AVs to be connected to 5G networks, which in turn allows AVs to communicate with “smart”, 5G-connected roadway infrastructure. The federal government can support progress towards this goal through a three-part initiative. Part 1 would establish Transportation Infrastructure Pilot Zones to field-test the integration of AV technology with 5G networks in settings across the country. Part 2 would create a National Connected AV Research Consortium to pursue connected-vehicle research achieving massive scale. Part 3 would launch a targeted research initiative focused on ensuring safety in a connected AV era, and Part 4 would create a new U.S. Corps of Engineers and Computer Scientists for Technology to embed technically skilled experts into government. With primary support from the National Highway and Traffic Safety Administration (NHTSA), the National Science Foundation (NSF), and the Department of Defense (DOD), this initiative would also help develop a basic framework for achieving a 90% reduction in vehicle crashes nationwide, deliver new transportation services, and establish national standards for AV technology. Initiative outcomes would promote U.S. global leadership in AVs, create new jobs and economic opportunities, and prepare the U.S. workforce to integrate technology of the future into systems of the present.
Investment should instead be directed at sectors where American technology and innovation exist but the infrastructure to commercialize them domestically does not—and where the national security case is clear.
As of March 2026, there were at least nine documented U.S. wrongful arrests tied to face recognition misidentification. Errors like these are as much human as machine.
The real opportunity of AI lies not just in the tools, but in an educator workforce prepared to wield them. When done right, this investment in human infrastructure ensures AI accelerates learning outcomes for all students, closing the “digital design divide.”
Good information sources, like collections, must be available and maintained if companies are going to successfully implement the vision of AI for science expressed by their marketing and executives.