Live & Validated · .NET 10 Service
Lat/long → an official reference post, with a full MIRE roadway dataset attached.
A responding officer's GPS coordinate isn't the final answer. It has to become a standardized location reference — which highway and mile marker, or for local roads, which street and how far from the nearest intersection or landmark — before the record is usable for analysis, safety planning, or public reporting. This service does that conversion in about a second, and pairs it with a full roadway dataset that goes well beyond just the position itself.
Measured by comparing this tool's output against thousands of a state's own already-finalized 2023 crash records — a direct comparison to known-correct answers, not a guess.
On local and city streets — a much harder problem nationally, since a statewide local-road reference system often exists but isn't publicly accessible — following MMUCC guidelines, the tool correctly identifies the situation (intersection vs. mid-block, on/under a bridge, etc.) roughly 4 times out of 5 in a state's largest cities, and reliably produces a usable location everywhere else, even where public map data isn't a perfect word-for-word match to the exact recorded phrasing.
A stateless .NET service — no database, nothing saved, nothing to install or back up. It resolves a request and returns the answer, running three stages in order:
Snaps the point to the nearest state highway centerline, then interpolates the reference post / log mile by bracketing between the two nearest physically-surveyed mile markers — not the route segment's own often 300+ mile long Beg/End reference-post span.
For local and municipal roads not on the state LRS: distance and direction from the nearest intersecting street, bridge, or railroad crossing, following official MMUCC guidelines.
Fans out to speed limit, AADT, district, municipal boundary, and street-centerline layers. Elements with no confirmed authoritative source report as unavailable with an honest reason, rather than guessing.
All spatial data comes from the state's own public GIS services — no authentication required, read-only queries. A failed data source is recorded and the request still completes with everything that could be resolved, rather than failing outright.
Some roads are recorded internally using a grid/mile-number system (e.g. "Road 60"), while public map data uses a completely different street name for the same physical road (e.g. "South 60th Road"). No amount of matching logic can fix two different naming systems describing the same physical road — that gap can only be closed with access to a state's own internal road-naming records, which isn't available publicly. That's the single thing standing between "very good" and the accuracy already shown on state highways, applied everywhere in the state — an expectation untested against real local-road data today, a claim to prove, not one we're making yet.
Full methodology available on request.
