Monthly Traffic Safety Analysis

602 CRASHES IN
VERMONT, VT
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, Vermont recorded 602 total traffic crashes, a decrease from the 659 crashes documented in November 2022, representing an 8.7% year-over-year reduction. While total collisions and fatalities (3, down from 4) declined, the number of persons injured increased from 125 to 133. The most notable shift was the increase in the proportion of collisions resulting in an injury, which rose from 19.0% to 22.1% of all incidents.

602

-8.6%was 659

Total Crash Events

3

-25.0%was 4

Fatal Crashes

133

6.4%was 125

Injury Crashes

3

-25.0%was 4

Fatal Crash Events

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

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Vermont show a decrease in November 2023 compared to the same month in the prior year. Total crashes fell by 8.7%, from 659 to 602. This downward trend was also reflected in fatalities, which decreased from 4 to 3. However, the number of reported injuries ran counter to this trend, increasing by 6.4% from 125 to 133.

When Crashes Happen

The temporal patterns of crashes showed both consistency and change year-over-year. The 5 p.m. hour remained the peak time for collisions in both November 2022 (59 crashes) and November 2023 (64 crashes). However, the day with the most incidents shifted from Wednesday in the prior year, with 153 crashes, to Thursday in the current year, with 124 crashes.

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity profile of collisions shifted. The proportion of crashes resulting in an injury increased from 19.0% in November 2022 to 22.1% in November 2023, with the absolute number of injuries rising from 125 to 133. Conversely, fatal incidents saw a slight decline; there were 3 fatal crashes in November 2023 compared to 4 in the prior year, and the fatal crash rate decreased from 0.6% to 0.5%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
-25.0%prior 4
Injury133minor injury crashes22.1%
6.4%prior 125
No Injury454no injury crashes75.4%
-8.5%prior 496

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Road & Environmental Conditions

Comparing crash conditions, the proportion of incidents occurring on adverse road surfaces changed year-over-year. Crashes on icy roads more than doubled, from 10 in November 2022 to 21 in November 2023, increasing their share of total crashes from 1.5% to 3.5%. While the number of crashes in dark lighting conditions was identical at 188 in both periods, their proportion of total crashes rose from 28.5% to 31.2% due to the overall decrease in collisions.

Weather

Clear263 (56.8%)
-21.0%prior 333
Cloudy114 (24.6%)
40.7%prior 81
Freezing Precipitation55 (11.9%)
-1.8%prior 56
Rain31 (6.7%)
-29.5%prior 44

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash

Lighting

Daylight410 (68.6%)
-11.6%prior 464
Dark188 (31.4%)
0.0%prior 188

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Road Surface

Dry318 (67.8%)
-14.7%prior 373
Wet72 (15.4%)
4.3%prior 69
Snow45 (9.6%)
-16.7%prior 54
Ice21 (4.5%)
110.0%prior 10
Slush7 (1.5%)
Sand, mud, dirt, oil, gravel5 (1.1%)
Other - Explain in Narrative1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 602

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 2023." Published July 5, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/november-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 — November 2023 | ThatCarHitMe.com