How We Estimate Speed-Camera Revenue

One of the most common questions we get is: where do the revenue estimates come from? The short answer is that we multiply reported violation counts by the posted fine amount for each jurisdiction. The longer answer is that the quality of those inputs varies dramatically, and understanding the gaps is just as important as reading the top-line numbers.

This article explains the methodology in full. For a live view of estimated revenue by jurisdiction, see the cameras leaderboard. For the legal background on how fines are structured, see our laws comparison. For the technical picture of how cameras capture violations in the first place, see How Automated Speed Enforcement Works in the DMV.

The Core Formula

Our revenue estimate for any jurisdiction that publishes data is straightforward:

Estimated annual revenue = reported violations per year × posted fine per violation

Neither component is invented. Violation counts come from public records — jurisdiction open-data portals, published annual reports, or FOIA responses. Fine amounts come from the statutory or regulatory schedule in effect for that jurisdiction.

The formula is conservative by design. It does not account for:

• Administrative fees layered on top of the base fine (some jurisdictions add processing fees)
• Fine escalation for repeat violations within a window (some jurisdictions double the fine)
• Collection rates (not every issued ticket is ultimately paid)
• Revenue sharing between the jurisdiction and the camera vendor (many programs operate on a per-citation split)

We use the base fine only, applied to reported violation counts. This means our estimates are likely lower than the amount jurisdictions actually collect, not higher. We flag this on the about page and in the leaderboard data.

Where Violation Counts Come From

D.C.

D.C. publishes automated enforcement data through its open-data portal. The District runs one of the most transparent camera programs in the region, with violation counts available broken down by camera location, date, and type (speed vs. red-light vs. bus-lane). These records are the most complete and up-to-date inputs we have.

For D.C. cameras and their violation data, see D.C. cameras.

Maryland Jurisdictions

Maryland is more fragmented. Individual jurisdictions — Baltimore City, Montgomery County, Prince George's County, and others — publish their own data on different schedules and in different formats. Some publish monthly reports; others publish annual summaries; a few have not released recent figures at all.

We source Maryland data from county open-data portals, annual transportation department reports, and periodic legislative oversight submissions. When a Maryland jurisdiction has not published recent violation counts, we show "No data reported" for that jurisdiction rather than estimating or extrapolating.

See the per-county breakdowns: Baltimore City, Montgomery County, Prince George's County, Howard County.

Virginia Jurisdictions

Virginia's school-zone camera program is newer, and data reporting practices are still developing. Several Virginia localities have published initial program reports; others have not yet released figures. As with Maryland, the principle is the same: we show real data where it exists, and "No data reported" where it does not.

See: Arlington, Fairfax, Alexandria.

Fine Rates Used

Fine amounts per jurisdiction are taken from the statutory or regulatory schedule in effect at the time of the data:

• D.C.: The D.C. tiered schedule runs from $100 (1–10 mph over) to $500 (26+ mph over). For estimation purposes, we apply a weighted average across speed tiers reflective of the typical distribution of violations — most citations cluster in the lower tiers. The site's posted fine reflects the base tier; see DC's published schedule for the full range.
• Maryland jurisdictions: Effective October 1, 2025 (HB 182), Maryland replaced its prior flat rate with a tiered civil fine schedule: $40 (12–15 mph over) up to $425 (40+ mph over), with a separate higher scale for work zones. Our estimates use the base posted fine listed in JURISDICTION_CATALOG as a conservative floor; the actual collected amount will be higher for violations in upper speed tiers. See Maryland's current schedule for the full table.
• Virginia jurisdictions: Virginia's statute sets graduated fines: $50 (10–14 mph over), $75 (15–19 mph over), and $100 (20+ mph over). Our estimates use the $100 ceiling as the posted fine for conservatism, but most violations likely fall in lower tiers.

These are the figures reflected in JURISDICTION_CATALOG in our codebase — they are not invented; they are the posted legal fine amounts.

When We Show "No Data Reported"

This is important: we do not fabricate or interpolate violation counts. If a jurisdiction does not publish the data, the revenue field for that jurisdiction says "No data reported" — not an estimate, not a projection from older figures, not a calculation based on camera counts.

This is a deliberate design choice. Camera programs generate public revenue from public roads. If a jurisdiction isn't publishing that data, the honest thing to say is that the data doesn't exist in our system — not to paper over the gap with a guess that could easily mislead.

Several Maryland counties and Virginia localities currently fall into this category. Their absence from the estimated-revenue rankings doesn't mean they generate no revenue; it means they haven't made the data available.

The Limits of the Estimate

Lag Between Data and Reality

Public data releases take time. Annual reports come out months after the period they cover. Open-data portals vary in how frequently they refresh. Our estimates reflect the most recent published figures we have, which may be one or two years behind the current enforcement reality.

Vendor Revenue Splits

Many camera programs are operated by private vendors under contracts that split the per-citation revenue between the jurisdiction and the vendor. We have no line of sight into those contract terms for most jurisdictions. Our revenue estimate represents the gross reported violation activity, not the net revenue retained by the government.

Non-Paying Citations

Not every issued citation results in payment. Tickets can be contested successfully, dismissed for procedural reasons, or simply ignored (though ignoring them tends to result in registration holds). The actual amount collected is lower than the gross violation-count-times-fine calculation. How much lower varies by jurisdiction and is generally not published.

Fine Schedule Changes

Jurisdictions occasionally revise their fine schedules. If a jurisdiction raised or lowered its fine rate during the data period, our estimate may not precisely reflect that. We note the effective fine rate used in the methodology section on the about page.

Why Publish Estimates at All?

Given all these caveats, why produce estimates rather than just listing raw violation counts?

Because revenue is the metric that makes camera programs legible in policy terms. Raw violation counts tell you how busy an enforcement program is; revenue estimates tell you what the program is worth financially to the jurisdiction operating it. That context matters when evaluating whether a program is primarily a safety intervention or primarily a revenue mechanism — a debate that runs through every legislative cycle in all three jurisdictions.

Publishing the estimates alongside the methodology, the caveats, and the "No data reported" labels is how we try to be useful without being misleading. The cameras leaderboard presents the estimates visually; this article explains the math.

Getting the Data Yourself

All of the source data we use is public record. If you want to verify our estimates or dig deeper:

• D.C.: Search the D.C. Open Data portal (opendata.dc.gov) for automated traffic enforcement datasets
• Maryland: Individual county open-data portals; Maryland State Highway Administration annual reports
• Virginia: Virginia Department of Transportation (VDOT) and individual locality websites for school-zone camera program reports

If you find data we're missing or notice a discrepancy, contact us at the address on the about page. We update the data as new releases become available.

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Revenue estimation is only as good as the data feeding it. We are transparent about where that data is strong, where it's stale, and where it simply doesn't exist yet. If you want to understand the numbers you see on this site, this article and the about page together give you the full picture.