No Boundaries

Transportation Maintenance Innovation

Katie Johnson

No Boundaries Publishes Phase III Summary of Activities

With its third phase coming to an end, the No Boundaries Transportation Maintenance Innovations pooled fund has published a summary of the group’s activities from 2020 to 2025.

The No Boundaries pooled fund is a community of practice dedicated to identifying and sharing innovations that help states save time and money on all aspects of their maintenance-related activities. The group promotes adaptation, implementation and broader use of successful tools, technologies and practices, and facilitates opportunities that encourage collaboration.

No Boundaries’ fourth phase will build upon its previous work to support successful tech transfer. The group hosts two in-person peer exchanges each year where member representatives can meet and discuss their challenges and innovative maintenance solutions. No Boundaries also supports a variety of additional opportunities for learning and exchanging knowledge, and maintains a searchable online database where maintenance innovations can be found and showcased by transportation agencies at all levels of government. 

Download No Boundaries’ new Phase III Summary of Activities, and learn how to join the next phase of No Boundaries at TPF-5(548).

Nebraska Investigates Effects of Concrete Sealers on Pavement Markings

A penetrating sealer can increase the durability and performance of a concrete pavement, but whether sealer should be applied before or after pavement markings may not be well understood.

To determine whether a concrete sealer affects the adhesion or reflectivity of pavement markings and which should be applied to a concrete pavement first, the Nebraska Department of Transportation conducted a research study that tested the effects of different sealers placed over or under markings consisting of paint and reflective glass beads.

Read the report: Effect of Penetrating Concrete Sealers on Pavement Marking, May 2025.

Image source: Nebraska Department of Transportation

Tennessee Investigates Mitigation Strategies for Wildlife-Vehicle Collisions

Large animals such as deer that make it onto the roadway can cause severe injuries, fatalities and property damage when they’re struck by a vehicle.

To identify the factors that can lead to wildlife-vehicle crashes and strategies that can reduce the risks to drivers and animals, the Tennessee Department of Transportation conducted a research study that identified high-risk locations across the state and recommendations to raise awareness and mitigate the potential for crashes.

Read the research brief: Countermeasures for High-Risk Locations for Wildlife Related Crashes in Tennessee, July 2025

Image source: Tennessee Department of Transportation

Missouri Develops Automated Warning System for Work Zones

Truck-mounted attenuators (TMAs) are designed to protect workers in highway work zones, but warning workers when a vehicle breaches the area requires the TMA drivers to issue an alert manually.  

To remove the burden on TMA drivers, Missouri DOT developed an automated warning system that can detect an imminent work zone crash and issue timely, context-sensitive warnings to workers.

Read the final report: Audible Alert and TMA Lighting, June 2025

Image source: Missouri DOT

Aurora Pooled Fund Develops Method for Estimating Road Surface Conditions in Real Time

Real-time road surface condition information can help state maintenance crews allocate their time and resources effectively.

To help states quickly determine where maintenance is needed most, the Aurora Pooled Fund, a 19-state collaborative research effort led by Iowa DOT, developed tools that leverage images collected automatically from road weather information system stations to provide an up-to-date maintenance priority ranking.

Read the research brief: Using Road Images to Estimate Real-Time Road Surface Conditions, June 2025.

Image source: Aurora Pooled Fund

Washington State Develops Automated System for Managing Road Sign Inventory

Without proper management, traffic signs that have been vandalized or damaged through natural processes can be less effective, reducing the safety and well-being of the traveling public.

To improve how well it monitors and manages its road sign inventory, the Washington State Department of Transportation developed an automated system that uses artificial intelligence and street images to recognize when signs are in need of maintenance or replacement.

Read the research brief: Automated Traffic Sign Recognition Using Computer Vision and Deep Learning, March 2025

Image source: Washington State Department of Transportation