By June 17, 2022, Salisbury had a comprehensive, defensible plan grounded in measurable pavement condition scores for 36 roadway miles, enabling faster, more targeted maintenance.
Salisbury’s coastal roads face heavy seasonal traffic and weather stress, but leaders lacked a current, consistent view of street conditions to guide action. Outdated or inconsistent data forced staff to react to complaints and chase potholes rather than build a strategic paving plan. With no accurate paving budgets and limited ability to justify choices in public meetings, the city struggled to show efficient use of taxpayer dollars while keeping pace with resident expectations.
Salisbury selected Cyvl to rapidly survey every public road using vehicle-mounted LiDAR and sensors, capturing a complete, objective record of surface conditions across 36 roadway miles. Cyvl’s Infrastructure Intelligence platform applied AI to transform raw measurements into street-by-street condition scores, prioritized repair lists, and scenario-based budget plans that city leaders could trust. Delivered by June 17, 2022—weeks instead of months—the city received detailed, actionable pavement condition data for all 36 miles, plus clear reports and maps that made it easy to communicate the plan and move projects into construction faster.
By June 17, 2022, Salisbury had a comprehensive, defensible plan grounded in measurable pavement condition scores for 36 roadway miles, enabling faster, more targeted maintenance. With reliable data in hand, staff could schedule repairs by impact and urgency, communicate tradeoffs, and start work sooner—reducing the time between data collection and project execution. Residents saw quicker fixes, smoother commutes, and stronger accountability for how paving dollars were spent.