Monthly Traffic Safety Analysis

1,171 CRASHES IN
VERMONT, VT
FEBRUARY 2016

All metrics benchmarked againstFebruary 2015

In February 2016, Vermont recorded 1,171 total vehicle crashes, a 41.1% decrease from the 1,989 crashes recorded in February 2015. Despite the overall reduction in collisions, the state saw an increase in fatal outcomes, with two crashes resulting in two fatalities, compared to zero in the prior year period. Crashes involving alcohol also increased from 41 in 2015 to 54 in 2016, a 31.7% rise.

1,171

▼ -41.1%was 1,989

Total Crash Events

2

Fatal Crashes

179

▼ -9.6%was 198

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. 229 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data indicates a significant downward trend in total crashes for February. Collisions fell by 41.1%, from 1,989 in February 2015 to 1,171 in February 2016. The number of persons injured also decreased by 9.6% from 198 to 179, although the number of fatalities rose from zero to two.

When Crashes Happen

The timing of crashes shifted between the two periods. In February 2016, the peak day for crashes was Tuesday with 236 incidents, whereas in February 2015, Monday saw the most crashes with 357. The peak hour also changed, moving from the 4 p.m. hour in 2015 (163 crashes) to the 7 a.m. hour in 2016 (92 crashes), indicating a shift from an afternoon to a morning commute peak.

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in February 2016 compared to the previous year, despite a lower total number of incidents. Two fatal crashes were recorded, resulting in two deaths, up from zero in February 2015. While the absolute number of crashes involving an injury saw a slight decrease from 198 to 179, the proportion of crashes resulting in an injury rose from 10.0% in the prior period to 15.3% in the current period.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.2%
Injury179minor injury crashes15.3%
↓-9.6%prior 198
No Injury761no injury crashes65%
↓-30.6%prior 1,096

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Most severe injury per crash record

Road & Environmental Conditions

Driving conditions associated with crashes varied significantly year-over-year. In February 2016, a higher proportion of collisions occurred after dark (31.8% of total crashes) compared to February 2015 (24.9%). Road surface conditions saw a notable shift: crashes on snowy roads decreased from being the most common factor in 2015 (accounting for 49.8% of crashes with a recorded surface) to 19.2% in 2016. Conversely, crashes on dry roads became the leading category in 2016, accounting for 47.6% of such crashes, up from 24.7% in the prior year.

Weather

Clear387 (45.7%)
↓-30.5%prior 557
Cloudy204 (24.1%)
↓-17.4%prior 247
Freezing Precipitation183 (21.6%)
↓-47.4%prior 348
Rain67 (7.9%)
Wind5 (0.6%)
↓-68.8%prior 16

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Weather condition at time of crash

Lighting

Daylight791 (68.0%)
↓-46.5%prior 1,479
Dark373 (32.0%)
↓-24.6%prior 495

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · Lighting condition field

Road Surface

Dry411 (47.6%)
↑41.2%prior 291
Snow166 (19.2%)
↓-71.7%prior 586
Wet131 (15.2%)
↑4.8%prior 125
Ice99 (11.5%)
↓-3.9%prior 103
Slush45 (5.2%)
↓-23.7%prior 59
Sand, mud, dirt, oil, gravel5 (0.6%)
Other - Explain in Narrative4 (0.5%)
↓-55.6%prior 9
Water (standing / moving)2 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-02-01 to 2016-02-29 · 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: 2016-02-01 through 2016-02-29
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2016-02-01 through 2016-02-29 (29 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,171

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 2016." Published July 5, 2026. Reporting period: 2016-02-01 to 2016-02-29. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/february-2016-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 2016 | ThatCarHitMe.com