Monthly Traffic Safety Analysis

1,243 CRASHES IN
VERMONT, VT
NOVEMBER 2016

All metrics benchmarked againstNovember 2015

In November 2016, Vermont recorded 1,243 traffic crashes, a 20.1% increase from the 1,035 crashes documented in November 2015. This period saw fatalities rise from 4 to 6 and total injuries increase by 32.7% from 156 to 207. The most significant year-over-year shift was a dramatic rise in crashes occurring during freezing precipitation, which increased from 17 incidents in the prior year to 141 in the current period.

1,243

20.1%was 1,035

Total Crash Events

6

50.0%was 4

Fatal Crashes

207

32.7%was 156

Injury Crashes

6

50.0%was 4

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 321 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data for November indicates a rising trend in traffic collisions across Vermont. Total crashes increased by 20.1%, from 1,035 in November 2015 to 1,243 in November 2016. This increase was accompanied by a 32.7% rise in injuries (from 156 to 207) and an increase in total fatalities from 4 to 6.

When Crashes Happen

The overall temporal patterns of crashes remained consistent year-over-year, with Tuesday being the peak day for crashes in both November 2015 (182 crashes) and November 2016 (244 crashes). Similarly, the 5 PM hour was the peak time for collisions in both periods. However, the current period saw a notable increase in crashes during the morning commute, with incidents at 7 AM increasing from 53 to 87 and at 8 AM from 53 to 65.

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased in November 2016 compared to the previous year. The number of fatal crashes rose from 4 to 6, and the total number of injuries grew from 156 to 207. The proportion of all crashes that resulted in an injury increased from 15.1% in November 2015 to 16.7% in November 2016, while the fatal crash rate rose from 0.39% to 0.48%.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.5%
50.0%prior 4
Injury207minor injury crashes16.7%
32.7%prior 156
No Injury709no injury crashes57%
9.2%prior 649

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Most severe injury per crash record

Road & Environmental Conditions

Adverse environmental conditions were a more significant factor in November 2016 compared to the prior year. While crashes on dry roads decreased from 637 to 512, there was a substantial increase in incidents on compromised surfaces. Crashes on snowy or icy roads rose from a combined 21 in November 2015 to 147 in November 2016, and crashes in freezing precipitation increased from 17 to 141. The proportional split between daylight and dark conditions remained stable.

Weather

Clear405 (48.5%)
-22.3%prior 521
Cloudy190 (22.8%)
28.4%prior 148
Freezing Precipitation141 (16.9%)
729.4%prior 17
Rain96 (11.5%)
104.3%prior 47
Wind3 (0.4%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Weather condition at time of crash

Lighting

Daylight850 (69.4%)
19.5%prior 711
Dark375 (30.6%)
17.6%prior 319

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · Lighting condition field

Road Surface

Dry512 (60.3%)
-19.6%prior 637
Wet170 (20.0%)
117.9%prior 78
Snow94 (11.1%)
Ice53 (6.2%)
178.9%prior 19
Sand, mud, dirt, oil, gravel7 (0.8%)
-12.5%prior 8
Slush7 (0.8%)
Other - Explain in Narrative5 (0.6%)
Water (standing / moving)1 (0.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-11-01 to 2016-11-30 · 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: 2016-11-01 through 2016-11-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2016-11-01 through 2016-11-30 (30 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,243

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: November 2016." Published July 5, 2026. Reporting period: 2016-11-01 to 2016-11-30. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/november-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 — November 2016 | ThatCarHitMe.com