The Pavement Condition Index (PCI) has long been the standard for evaluating the condition of road surfaces, from public streets to critical airport runways. Developed by the U.S. Army Corps of Engineers, PCI quantifies pavement health on a scale from 0 to 100, based on visual assessment of surface distresses. While widely adopted globally, PCI’s biggest drawback is its reliance on manual, visual inspection—an approach that is time-consuming, subjective, and lacking in repeatability. 

At XenomatiX, we’re working to improve that. 

As part of our mission to bring precision and automation to pavement inspection, our XenoTrack system is evolving to deliver complete, accurate and objective PCI scores.  

There are two key steps to surpass traditional visual assessments: automation and accurate, objective quantification of pavement distresses. A purely camera-based solution can achieve automation—capturing images efficiently and consistently—but it falls short in delivering the precision and objectivity needed for true quantification. This is where 6D road scanning technology demonstrates its strength. By precisely measuring the pavement’s geometry and surface characteristics, it enables comprehensive evaluation of all PCI components, providing reliable numerical data rather than subjective impressions. The result is a consistent, data-driven PCI score that reflects the actual condition of the pavement. 

A New Approach: XenoTrack 

XenomatiX’ system calculates PCI using high-resolution camera and a 3D solid-state lidar combined with edge AI algorithms. Our approach captures pavement geometry and surface anomalies across the entire road width, identifying and quantifying all relevant PCI parameters.