Monthly Traffic Safety Analysis

1,278 CRASHES IN
VERMONT, VT
FEBRUARY 2017

All metrics benchmarked againstFebruary 2016

In February 2017, Vermont recorded 1,278 total vehicle crashes, a 9.1% increase from the 1,171 crashes reported in February 2016. While the overall number of crashes rose, the most significant year-over-year change was a sharp increase in fatalities, which grew from 2 to 7. Conversely, the total number of injuries reported in crashes decreased from 179 to 132 during the same period.

1,278

▲ 9.1%was 1,171

Total Crash Events

7

▲ 250.0%was 2

Fatal Crashes

132

▼ -26.3%was 179

Injury Crashes

7

▲ 250.0%was 2

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 325 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for February indicates an upward trend in the total number of collisions, rising from 1,171 in 2016 to 1,278 in 2017. This represents an increase of 107 incidents year-over-year. Despite this rise in total crashes, the number of people injured decreased by 26.3%, while the number of fatalities increased from 2 to 7.

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In February 2017, the peak day for crashes was Wednesday with 239 incidents, and the peak hour was 3 p.m. with 99 crashes. This contrasts with February 2016, when the peak day was Tuesday (236 crashes) and the peak hour occurred during the morning commute at 7 a.m. (92 crashes).

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crash outcomes changed notably year-over-year. The fatal crash rate more than tripled, increasing from 0.17% of all crashes in February 2016 to 0.55% in February 2017, with fatalities rising from 2 to 7. In contrast, the proportion of crashes resulting in an injury decreased from 15.3% to 10.3% over the same period. The share of non-injury crashes remained relatively stable, accounting for 65.0% in 2016 and 63.7% in 2017.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.5%
↑250.0%prior 2
Injury132minor injury crashes10.3%
↓-26.3%prior 179
No Injury814no injury crashes63.7%
↑7.0%prior 761

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Most severe injury per crash record

Road & Environmental Conditions

Driving conditions associated with crashes worsened in February 2017 compared to the previous year. The proportion of crashes occurring on snowy road surfaces increased from 14.2% to 25.0%, and incidents during freezing precipitation rose from 15.6% to 23.1% of all crashes. Correspondingly, the share of crashes on dry roads fell from 35.1% in 2016 to 23.7% in 2017. Crashes in daylight conditions made up a larger share of the total, increasing from 67.5% to 75.0%.

Weather

Clear346 (40.5%)
↓-10.6%prior 387
Freezing Precipitation295 (34.5%)
↑61.2%prior 183
Cloudy202 (23.7%)
↓-1.0%prior 204
Rain8 (0.9%)
↓-88.1%prior 67
Wind3 (0.4%)
↓-40.0%prior 5

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Weather condition at time of crash

Lighting

Daylight959 (75.8%)
↑21.2%prior 791
Dark307 (24.2%)
↓-17.7%prior 373

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · Lighting condition field

Road Surface

Snow320 (37.3%)
↑92.8%prior 166
Dry303 (35.3%)
↓-26.3%prior 411
Wet145 (16.9%)
↑10.7%prior 131
Ice43 (5.0%)
↓-56.6%prior 99
Slush36 (4.2%)
↓-20.0%prior 45
Sand, mud, dirt, oil, gravel6 (0.7%)
↑20.0%prior 5
Other - Explain in Narrative5 (0.6%)

Source: Vermont Crash Data · Arcgis Open Data · 2017-02-01 to 2017-02-28 · 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: 2017-02-01 through 2017-02-28
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2017-02-01 through 2017-02-28 (28 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,278

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 2017." Published July 5, 2026. Reporting period: 2017-02-01 to 2017-02-28. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/february-2017-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 2017 | ThatCarHitMe.com