Armed with trustworthy, citywide pavement intelligence, Trenton shifted from reactive firefighting to proactive programming in a single budget cycle.
Trenton faced paving decisions without a current, citywide view of street conditions; the team relied on outdated or inconsistent data and spot checks that missed hidden failures. With no clear prioritization method, plans often defaulted to reacting to complaints, making it hard to build defensible paving plans and answer “Why not my road?” in town meetings. Budget requests were also difficult to justify because the city could not show efficient use of taxpayer dollars with credible, up-to-date measurements.
To modernize its approach, Trenton selected Cyvl to perform a rapid, vehicle-based survey using LiDAR and sensors across 853 roadway miles. Within weeks, the Infrastructure Intelligence platform used AI to turn the raw survey into detailed pavement condition scores, geo-referenced distresses, and prioritized repair lists, along with a complete inventory of 4,008 signs and 430 guardrails. Delivered by July 29, 2025, the city gained defensible plans and board-ready reports, enabling leaders to make confident, data-driven decisions and schedule work faster.
Armed with trustworthy, citywide pavement intelligence, Trenton shifted from reactive firefighting to proactive programming in a single budget cycle. The weeks-not-months delivery by July 29, 2025 shortened the time between data collection and construction, allowing crews to address the most critical segments sooner and demonstrate quick wins to residents. Clear condition scores and asset maps strengthened budget narratives, streamlined public communication, and aligned day-to-day work with long-term goals.