Monthly Traffic Safety Analysis

573 CRASHES IN
VERMONT, VT
FEBRUARY 2023

All metrics benchmarked againstFebruary 2022

In February 2023, Vermont recorded 573 total traffic crashes, a 32.5% decrease from the 849 crashes reported in February 2022. During this period, total fatalities fell from 5 to 2, and total injuries decreased from 133 to 119. The most significant year-over-year change was the nearly one-third reduction in the total volume of crashes across the state.

573

▼ -32.5%was 849

Total Crash Events

2

▼ -60.0%was 5

Fatal Crashes

119

▼ -10.5%was 133

Injury Crashes

2

▼ -60.0%was 5

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 12 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics in Vermont showed a significant downward trend in February 2023 compared to the same month in the prior year. Total crashes fell by 32.5%, from 849 to 573. Correspondingly, fatalities decreased from 5 to 2, and the number of injuries saw a 10.5% reduction from 133 to 119.

When Crashes Happen

The temporal patterns of crashes shifted between February 2022 and February 2023. The peak day for collisions moved from Friday (205 crashes) in the prior year to Tuesday (97 crashes) in the current period. While the peak hour for crashes remained at 3 p.m. in both years, the volume of crashes during that hour decreased from 75 to 47. The crash distribution in February 2023 was more evenly spread across weekdays compared to the prior year, which saw a pronounced spike on Friday.

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a mixed change year-over-year. The number of fatal crashes decreased from 5 in February 2022 to 2 in February 2023, with the fatal crash rate dropping from 0.59% to 0.35%. While the absolute number of injuries also fell from 133 to 119, the proportion of crashes resulting in an injury increased from 15.7% to 20.8% of all collisions. Crashes resulting in no injuries decreased from 562 to 440.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
↓-60.0%prior 5
Injury119minor injury crashes20.8%
↓-10.5%prior 133
No Injury440no injury crashes76.8%
↓-21.7%prior 562

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by road condition changed notably between the two periods. In February 2023, 37.5% of crashes occurred on dry roads, up from 25.7% in the prior year. The proportion of crashes on adverse surfaces like snow, ice, wet, or slush also increased slightly, from 36.3% in February 2022 to 39.1% in February 2023. The share of crashes occurring in daylight (around 72%) and in darkness (around 28%) remained consistent across both periods.

Weather

Clear223 (51.4%)
↓-14.9%prior 262
Freezing Precipitation121 (27.9%)
↓-19.3%prior 150
Cloudy77 (17.7%)
↓-17.2%prior 93
Rain9 (2.1%)
↓-40.0%prior 15
Wind4 (0.9%)
↓-42.9%prior 7

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash

Lighting

Daylight414 (72.4%)
↓-31.5%prior 604
Dark158 (27.6%)
↓-33.9%prior 239

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field

Road Surface

Dry215 (48.1%)
↓-1.4%prior 218
Snow112 (25.1%)
↓-32.9%prior 167
Wet63 (14.1%)
↓-35.1%prior 97
Ice34 (7.6%)
↓-10.5%prior 38
Slush15 (3.4%)
↑150.0%prior 6
Other - Explain in Narrative6 (1.3%)
→0.0%prior 6
Sand, mud, dirt, oil, gravel2 (0.4%)
↓-60.0%prior 5

Source: Vermont Crash Data · Arcgis Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-02-01 through 2023-02-28 (28 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 573

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). "vermont, VT Crash Intelligence Report: February 2023." Published July 5, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/february-2023-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

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Vermont (Statewide) Crash Report — February 2023 | ThatCarHitMe.com