Yearly Traffic Safety Analysis

222 CRASHES IN
MILTON, VT
2025

All metrics benchmarked against2024

Overall, total crashes in Milton increased by 16.84%, rising from 190 crashes in 2024 to 222 crashes in 2025. The most significant year-over-year shift was the emergence of fatal crashes, with 2 fatalities reported in 2025 compared to none in 2024. Despite the increase in total crashes, the number of injuries decreased by 14.29%, from 35 in 2024 to 30 in 2025.

222

16.8%was 190

Total Crash Events

2

Fatal Crashes

30

-14.3%was 35

Injury Crashes

2

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a notable increase in crash incidents, with total crashes rising from 190 in 2024 to 222 in 2025, representing a 16.84% increase. This period also saw the introduction of crash fatalities, with 2 reported in 2025 compared to 0 in 2024. Conversely, total injuries decreased by 14.29%, from 35 to 30, over the same period.

When Crashes Happen

The peak day for crashes shifted from Friday in 2024, with 33 incidents, to Monday in 2025, with 43 incidents. While the peak hour remained 4 PM for both years, the number of crashes at this hour increased significantly from 19 in 2024 to 30 in 2025. December experienced a substantial increase in crashes, rising from 20 in 2024 to 37 in 2025.

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate increased from 0% in 2024 to 0.9% in 2025, corresponding to 2 fatal crashes in 2025 compared to none in the prior year. The proportion of injury crashes decreased from 18.4% of total crashes in 2024 to 13.5% in 2025. Concurrently, the proportion of no-injury crashes increased from 81.6% to 85.6% of total crashes.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
Injury30minor injury crashes13.5%
-14.3%prior 35
No Injury190no injury crashes85.6%
22.6%prior 155

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

There was an increase in the proportion of crashes occurring in the dark, rising from 25.8% in 2024 to 29.7% in 2025. Crashes on snowy road surfaces also saw a notable increase in proportion, from 2.6% in 2024 to 5.0% in 2025. The proportion of crashes occurring in clear weather remained stable, at approximately 21% for both periods.

Weather

Clear47 (58.8%)
14.6%prior 41
Cloudy19 (23.8%)
18.8%prior 16
Freezing Precipitation10 (12.5%)
66.7%prior 6
Rain4 (5.0%)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight156 (70.3%)
10.6%prior 141
Dark66 (29.7%)
34.7%prior 49

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry55 (69.6%)
10.0%prior 50
Snow11 (13.9%)
120.0%prior 5
Wet10 (12.7%)
-9.1%prior 11
Slush1 (1.3%)
Ice1 (1.3%)
Sand, mud, dirt, oil, gravel1 (1.3%)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Vermont Crash Data, accessed programmatically via the Arcgis Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Arcgis Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2025-01-01 through 2025-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: Milton, VT
  • Total crash records analyzed: 222

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "Milton, VT Crash Intelligence Report: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/milton/2025-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

ThatCarHitMe.com · An Injuria.ai Company

Milton, VT Crash Report — 2025 | ThatCarHitMe.com