vialytics Expands AI-Powered Road Management with Damaged Lane Marking Detection

Edison, NJ – vialytics is expanding its AI-powered road management platform with damaged lane marking detection, a new capability that helps municipalities identify worn or faded pavement markings during routine road assessments. By automatically detecting significantly damaged lane markings from roadway imagery, the feature gives public works teams a more efficient way to prioritize repainting, support maintenance planning, and improve roadway safety without conducting separate network surveys.

The new capability analyzes street imagery captured through vialytics’ standard road assessment workflow. Using computer vision, the system flags locations where pavement markings show substantial visibility loss and surfaces those segments directly in the vialytics web platform for review and action.

Damaged lane marking detection is designed to identify significantly deteriorated pavement markings with approximately 50% or greater visibility reduction across multiple marking types, including lane lines, arrows, stop bars, crosswalks, symbols, and roadway numbers. While longitudinal lane markings make up the majority of detections due to their prevalence across road networks, the system is built to identify a broader range of pavement marking deterioration.

Within the vialytics web system, affected segments appear in a dedicated view where staff can filter, visually verify, and evaluate locations on an interactive map. The AI performs the initial screening, while municipal teams remain in control of review, prioritization, and maintenance decisions.

Because detections are surfaced at both the image and network level, the feature helps agencies identify broader repainting needs across a roadway system and prioritize maintenance more strategically. From there, users can generate work orders for internal crews or contractors, enabling faster repainting cycles and clearer scopes of work.

By grading lane marking conditions using objective image data, damaged lane marking detection also provides a stronger foundation for maintenance planning and budget discussions. Municipal teams can use documented roadway conditions to support conversations with finance departments, leadership, or elected officials while gaining a clearer understanding of network-wide need.

A partner municipality using vialytics has reported significant efficiency gains from replacing manual windshield surveys and spreadsheet tracking with automated detection and digital workflows.

With the introduction of AI-based damaged lane marking detection, vialytics continues advancing its connected approach to infrastructure management by linking data collection, condition assessment, and maintenance execution within a single platform. The feature builds on the system municipalities already use to manage roads, traffic assets, green infrastructure, and public space, helping teams move from insight to action without fragmented tools.

To further explore how municipalities can use AI-powered road data to detect damaged lane markings and prioritize repainting more efficiently, vialytics has also published a new blog on the topic. Read it here: https://www.vialytics.com/blog...

About vialytics

vialytics provides AI-powered pavement condition assessments that streamline road assessments, improve efficiency, and support long-term planning for public works agencies.

Trusted by more than 1,000 municipalities across seven countries, the platform uses computer vision and mobile data collection to help agencies understand infrastructure conditions and make confident, data-driven maintenance decisions.