A consortium of 12 US state transportation departments has published results from a two-year pilot program using autonomous drone fleets for highway bridge inspections. The program documented average cost savings of 70% compared to traditional inspection methods requiring lane closures, scaffolding, and specialized climbing teams.
Drones equipped with millimeter-wave radar and LiDAR sensors created detailed 3D digital twins of 340 bridges, automatically identifying spalling, cracking, rebar exposure, and bearing deterioration. Machine learning algorithms prioritized repair urgency, enabling departments to allocate maintenance budgets more effectively.
The Federal Highway Administration is now drafting guidelines to make drone-based inspections an approved alternative to manual methods for bridges under 200 feet in span length. Full regulatory approval is expected by early 2027.