AI and integrated data help university set pavement maintenance budget

Client

Confidential (Higher Education)

Location

Madison, Wisc.

Challenge

Our client has a long-term partnership with a higher education institution that operates over 90 parking lots across its campus, covering more than 1.4 million square feet of pavement.

Project selection had been based on biannual, self-performed manual assessments. The institution was seeking a more objective approach and was particularly interested in our ability to eliminate subjectivity while completing all pavement assessments during summer weekends. Our pavement consulting services team delivered an innovative and repeatable solution that met these needs.

Solution

Technology is essential to providing timely and unbiased data on the pavement condition of over 90 parking lots of various sizes. Our digital data collection methods allowed our two-person team to scan all requested lots on weekends in the summer of 2025. Emptier lots means more data, without interrupting daily campus operations.

The data collected from each lot was stitched into a high-resolution image using Terracon’s proprietary Pave-AI technology. Our team ran this imagery through our ML/AI model which has been trained to identify all 2D distresses per ASTM 6433 (including distress type, severity level, and extent).This data allows us to provide a Pavement Condition Index (PCI) score, the unbiased and quantifiable data required to put together a maintenance and rehabilitation plan for future pavement improvements at the University.

Results

With the information provided by the Pave AI generated PCI scores, our client and the institution can now prioritize improvements, set future maintenance budgets, and plan to keep all lots on campus in good condition for years to come.