Monthly Traffic Safety Analysis

1,596 CRASHES IN
VERMONT, VT
DECEMBER 2016

All metrics benchmarked againstDecember 2015

In December 2016, Vermont recorded 1,596 total vehicle crashes, a 26.3% increase from the 1,264 crashes reported in December 2015. While overall crashes and resulting injuries rose, the number of crashes attributed to driving under the influence (DUI) decreased from 59 to 40. The most significant year-over-year change was a substantial increase in crashes occurring on roads with snow, ice, or slush, and during freezing precipitation.

1,596

▲ 26.3%was 1,264

Total Crash Events

6

▲ 20.0%was 5

Fatal Crashes

237

▲ 19.7%was 198

Injury Crashes

6

▲ 20.0%was 5

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 371 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data indicates a rising trend in traffic collisions for December. Total crashes increased by 26.3%, from 1,264 in December 2015 to 1,596 in December 2016. This upward trend was also reflected in crash outcomes, with total injuries rising 19.7% from 198 to 237 and fatalities increasing from 5 to 6.

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In December 2016, the peak day for crashes was Thursday with 324 incidents, whereas in December 2015, the peak was Tuesday with 317 incidents. The peak hour for crashes also changed, moving from the 5 PM hour in 2015 (141 crashes) to the 12 PM hour in 2016 (129 crashes). The evening commute peak observed in 2015 was less pronounced in 2016, which saw a higher concentration of crashes during the morning commute and midday.

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the absolute number of fatal crashes increased from 5 in December 2015 to 6 in December 2016, the fatal crash rate as a percentage of all crashes saw a slight decrease from 0.40% to 0.38%. Similarly, the number of injury-resulting crashes rose from 198 to 237 year-over-year. However, their proportion relative to all crashes declined from 15.7% in 2015 to 14.8% in 2016, as no-injury crashes grew from 57.9% to 61.5% of the total.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.4%
↑20.0%prior 5
Injury237minor injury crashes14.8%
↑19.7%prior 198
No Injury982no injury crashes61.5%
↑34.2%prior 732

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Most severe injury per crash record

Road & Environmental Conditions

A significant shift occurred in the conditions under which crashes happened, with a notable increase in incidents related to winter weather. The proportion of crashes on dry roads decreased from 37.4% in December 2015 to 24.1% in December 2016. Concurrently, crashes on snowy roads increased from 83 to 358, and those in freezing precipitation rose from 152 to 385. The majority of crashes in both periods occurred during daylight.

Weather

Clear413 (37.5%)
↑25.5%prior 329
Freezing Precipitation385 (35.0%)
↑153.3%prior 152
Cloudy267 (24.3%)
↓-1.8%prior 272
Rain28 (2.5%)
↓-73.6%prior 106
Wind8 (0.7%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Weather condition at time of crash

Lighting

Daylight1,191 (75.2%)
↑32.3%prior 900
Dark393 (24.8%)
↑9.8%prior 358

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · Lighting condition field

Road Surface

Dry384 (34.7%)
↓-18.8%prior 473
Snow358 (32.3%)
↑331.3%prior 83
Wet184 (16.6%)
↑4.5%prior 176
Ice132 (11.9%)
↑37.5%prior 96
Slush45 (4.1%)
↑55.2%prior 29
Other - Explain in Narrative3 (0.3%)
Sand, mud, dirt, oil, gravel1 (0.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-12-01 to 2016-12-31 · 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: 2016-12-01 through 2016-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2016-12-01 through 2016-12-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,596

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: December 2016." Published July 5, 2026. Reporting period: 2016-12-01 to 2016-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/december-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 — December 2016 | ThatCarHitMe.com