Worcester, MA

Worcester, MA Infrastructure Assessment

Summary

• Data-driven paving program stood up in weeks, accelerating repairs for residents
• 477 roadway miles scanned with LiDAR for objective, segment-level condition scores
• Clear, defensible plans and budgets that reduce 311 complaints and improve council confidence

Problem

Worcester’s roads face harsh freeze–thaw cycles and heavy traffic, yet older and inconsistent pavement data left leaders unsure which streets to fix and when, with little confidence in paving budgets. Manual windshield surveys were slow, unsafe, and often outdated by the time reports were compiled, making it hard to act fast for the community. In public meetings, staff were pressed with “Why not my road?” but lacked a clear, defensible prioritization method to justify choices and secure funding without appearing political.

Solution

Worcester chose Cyvl to rapidly survey the entire network using vehicle-mounted LiDAR and sensors, capturing high-resolution data across 477 roadway miles. Cyvl’s Infrastructure Intelligence platform used AI to transform raw data into segment-level condition scores, prioritized repair lists, and defensible multi-year plans with budget scenarios, giving engineers and public works leaders the information they needed to act quickly. Final datasets, maps, dashboards, and reports were delivered by November 20, 2023—weeks instead of months—so crews could schedule work sooner and city leaders could clearly explain decisions to residents.

Impact

With detailed, actionable pavement condition data for all 477 roadway miles, Worcester built a defensible paving program faster and focused work where it would help residents most. The city shifted from reacting to complaints to proactively planning projects, aligning crews and budgets around objective evidence. Faster delivery of accurate data shortened the window between collection and construction, enabling more repairs before winter and clearer communication during council and neighborhood meetings.

• Weeks‑fast data delivery meant quicker design, bid, and build cycles, translating to faster street improvements for residents
• Objective segment scores enabled crews to tackle the most critical segments first, improving safety and drivability across neighborhoods
• Town meetings ran smoother because staff could show maps, scores, and project rationales that residents and council could understand
• Fewer 311 complaints and emails as residents saw transparent plans and a clear schedule for when their street would be addressed
• Budget requests were easier to defend with evidence‑based scenarios, increasing confidence that taxpayer dollars were spent efficiently
• Public works could prioritize, schedule, and coordinate work far more easily, reducing change orders and maximizing the paving season