Xianbiao (XB) Hu, PhD Associate Professor, Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, PA. xbhu@psu.edu
Published in Transportation Research Today, Volume 1, November 2026, Article 100009 (Elsevier). Open access, CC BY-NC-ND 4.0. DOI: 10.1016/j.trt.2026.100009 Full text: https://www.sciencedirect.com/science/article/pii/S3051360X26000090
Highly automated vehicle (HAV) deployments in the United States are expanding rapidly, yet the policy discourse surrounding them remains shaped by misconceptions about what the technology actually is, who can legally operate it, and what it takes to scale economically, among others. This paper argues that these misconceptions are not information deficits solely resolvable through public education. They are products of three structural forces: (1) American federalism, which distributes regulatory authority across 50 states with no binding federal framework; (2) market incentives, which reward companies for blurring the boundary between driver-assistance and autonomous driving; and (3) legislative lag, which allows statutes to outpace the enforcement infrastructure needed to implement them. Drawing on expert focus groups with 35 participants from 29 organizations, a cross-state regulatory comparison covering all 50 states and the District of Columbia, and our direct involvement in evaluating Pennsylvania’s Act 130, the paper poses six questions that expose how these forces produce specific policy failures. Among the findings: no new vehicle a consumer can currently purchase operates beyond SAE Level 2—the consumer “self-driving car” does not exist in any legally meaningful sense; and a single interstate freight trip can cross six states with six incompatible regulatory regimes, insurance requirements ranging from zero to five million dollars, and no automatic interstate reciprocity. The paper concludes that state-level fragmentation is a durable institutional feature of American HAV governance, not a temporary phase, and recommends structural responses: differentiated regulation by automation level, interstate compacts for freight corridor harmonization, mandatory disclosure of operational economics, and standardized enforcement protocols. Autonomous freight is identified as the highest-return near-term priority.
Keywords: highly automated vehicles; autonomous vehicle policy; regulatory fragmentation; United States transportation law; structural misalignment; autonomous freight
Can you buy a self-driving car, and legally drive it where you live? Highly automated vehicle (HAV) deployments are expanding fast: Waymo robotaxis operate in multiple U.S. cities, Aurora’s autonomous trucks haul freight on the Dallas–Houston corridor, and AVIA reports over 145 million autonomous miles logged on U.S. roads. Yet no vehicle a consumer can currently purchase operates beyond SAE Level 2. The consumer “self-driving car” does not exist in any legally meaningful sense. Even where it might, many states allow only corporations and institutions, not individuals, to hold operating certificates. The gap between what people assume and what the law permits is wider than most realize.
The paper argues this gap is not an information deficit. It is the product of three structural forces: American federalism, which has produced 50 independent regulatory regimes with no automatic reciprocity; market incentives, which reward companies for blurring the line between driver-assistance and genuine autonomy; and legislative lag, which lets statutes outpace the enforcement infrastructure needed to implement them.
Drawing on expert focus groups with 35 participants from 29 organizations, a 50-state legislative review, and direct involvement in evaluating Pennsylvania’s Act 130, the paper poses six diagnostic questions that expose how these forces produce consequential policy failures. Its conclusion: state-level fragmentation is a durable institutional feature of American HAV governance, not a temporary phase.
Dr. Xianbiao (XB) Hu is an Associate Professor of Civil and Environmental Engineering at Penn State and a Managing Editor of the Journal of Intelligent Transportation Systems. His research spans smart mobility systems, automated vehicles, Physical AI, and transportation electrification. He partnered with PennDOT to evaluate Act 130 and leads research on autonomous truck-mounted attenuator deployment through a national pooled fund study with 17 state DOTs.