Monthly Traffic Safety Analysis

898 CRASHES IN
VERMONT, VT
NOVEMBER 2018

All metrics benchmarked againstNovember 2017

In November 2018, Vermont recorded 898 total traffic crashes, an 11.7% decrease from the 1,017 crashes reported in November 2017. While overall crashes, fatalities, and injuries declined, the most notable year-over-year change was in environmental conditions. Crashes involving freezing precipitation increased from 78 in the prior period to 252 in the current period, representing a shift from 7.7% to 28.1% of all crashes.

898

▼ -11.7%was 1,017

Total Crash Events

5

▼ -28.6%was 7

Fatal Crashes

147

▼ -10.9%was 165

Injury Crashes

5

▼ -28.6%was 7

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data indicates a downward trend in traffic incidents for November. Total crashes fell by 11.7%, from 1,017 in November 2017 to 898 in November 2018. This decline was accompanied by a reduction in both fatalities, which dropped from 7 to 5, and total injuries, which decreased by 10.9% from 165 to 147.

When Crashes Happen

The temporal patterns of crashes showed both consistency and change between the two periods. Friday remained the day with the most crashes in both November 2017 (174 crashes) and November 2018 (204 crashes). Similarly, the 5 p.m. hour was the peak time for collisions in both years, with 92 incidents in 2017 and 79 in 2018. However, the distribution of crashes throughout the week changed, with November 2018 showing pronounced peaks on Tuesday (192 crashes) and Friday, unlike the more evenly distributed weekday crash counts of the prior year.

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The overall severity of crashes showed a mixed but generally stable profile. The rate of fatal crashes declined slightly from 0.69% of all incidents in November 2017 to 0.56% in November 2018. The proportion of crashes resulting in an injury remained nearly constant, accounting for 16.2% of crashes in 2017 and 16.4% in 2018. The share of crashes with no reported injuries increased from 66.9% to 83.1% of the total.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.6%
↓-28.6%prior 7
Injury147minor injury crashes16.4%
↓-10.9%prior 165
No Injury746no injury crashes83.1%
↑9.7%prior 680

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Most severe injury per crash record

Road & Environmental Conditions

A significant year-over-year shift occurred in the environmental conditions at the time of crashes. In November 2018, incidents during freezing precipitation accounted for 252 crashes (28.1% of total), a substantial increase from 78 incidents (7.7% of total) in November 2017. This change is mirrored in road surface data, where crashes on snow-covered roads rose from 42 to 217, while crashes on dry roads fell from 498 to 244. The proportion of crashes occurring in daylight increased from 67.8% in 2017 to 71.2% in 2018.

Weather

Freezing Precipitation252 (35.9%)
↑223.1%prior 78
Clear207 (29.5%)
↓-46.6%prior 388
Cloudy159 (22.7%)
↓-12.2%prior 181
Rain82 (11.7%)
↑70.8%prior 48
Wind1 (0.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Weather condition at time of crash

Lighting

Daylight639 (72.3%)
↓-7.4%prior 690
Dark245 (27.7%)
↓-23.2%prior 319

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · Lighting condition field

Road Surface

Dry244 (33.9%)
↓-51.0%prior 498
Snow217 (30.2%)
↑416.7%prior 42
Wet178 (24.8%)
↑76.2%prior 101
Ice36 (5.0%)
↓-35.7%prior 56
Slush27 (3.8%)
Other - Explain in Narrative9 (1.3%)
Sand, mud, dirt, oil, gravel4 (0.6%)
↓-20.0%prior 5
Water (standing / moving)4 (0.6%)

Source: Vermont Crash Data · Arcgis Open Data · 2018-11-01 to 2018-11-30 · 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: 2018-11-01 through 2018-11-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2018-11-01 through 2018-11-30 (30 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 898

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 2018." Published July 5, 2026. Reporting period: 2018-11-01 to 2018-11-30. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/november-2018-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

ThatCarHitMe.com · An Injuria.ai Company

Vermont (Statewide) Crash Report — November 2018 | ThatCarHitMe.com