Monthly Traffic Safety Analysis

1,795 CRASHES IN
VERMONT, VT
JANUARY 2019

All metrics benchmarked againstJanuary 2018

In January 2019, there were 1,795 total crashes recorded in Vermont, representing a 36.8% increase from the 1,312 crashes in January 2018. While the number of fatalities remained stable at two for both periods, the total number of injuries rose from 137 to 177. The most notable year-over-year shift was this significant overall increase in total collisions.

1,795

▲ 36.8%was 1,312

Total Crash Events

2

Fatal Crashes

177

▲ 29.2%was 137

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

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data from January 2019 indicates a significant upward trend compared to the same month in the previous year. Total crashes increased by 483, from 1,312 to 1,795. The number of people injured in these incidents also grew from 137 in January 2018 to 177 in January 2019, while fatalities held constant at two.

When Crashes Happen

The temporal patterns of crashes remained consistent year-over-year, though the volume of incidents increased. Tuesday was the peak day for crashes in both January 2019 (350 crashes) and January 2018 (224 crashes). Similarly, the 4 PM hour was the peak time for collisions in both periods, with 146 crashes in the current period compared to 103 in the prior. The data shows a general increase in crash volume during weekday commute hours in January 2019 compared to the previous year.

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes was unchanged at two in both January 2019 and January 2018, causing the fatal crash rate to decrease from 0.15% to 0.11% of total crashes due to the higher overall volume. While the absolute number of injury-involved crashes rose from 137 to 177, their proportion relative to all crashes saw a slight decline from 10.4% in the prior period to 9.9% in the current period.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.1%
→0.0%prior 2
Injury177minor injury crashes9.9%
↑29.2%prior 137
No Injury942no injury crashes52.5%
↑9.5%prior 860

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by lighting conditions was stable, with daylight crashes accounting for 73.5% of incidents in January 2019 and 72.3% in January 2018. Among crashes with documented road surface conditions, the proportion on adverse surfaces like snow, ice, or slush was consistent at approximately 71% for both periods. However, for crashes with recorded weather data, the share occurring in freezing precipitation, rain, or wind increased from 29.2% in January 2018 to 35.7% in January 2019.

Weather

Clear392 (43.7%)
↑3.4%prior 379
Freezing Precipitation288 (32.1%)
↑42.6%prior 202
Cloudy185 (20.6%)
↓-3.1%prior 191
Rain20 (2.2%)
↓-25.9%prior 27
Wind13 (1.4%)
↑116.7%prior 6

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Weather condition at time of crash

Lighting

Daylight1,320 (73.9%)
↑39.2%prior 948
Dark466 (26.1%)
↑29.4%prior 360

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · Lighting condition field

Road Surface

Snow347 (38.1%)
↑40.5%prior 247
Dry246 (27.0%)
↑13.4%prior 217
Ice132 (14.5%)
↓-10.2%prior 147
Wet132 (14.5%)
↓-5.7%prior 140
Slush42 (4.6%)
↑27.3%prior 33
Other - Explain in Narrative8 (0.9%)
↓-33.3%prior 12
Sand, mud, dirt, oil, gravel4 (0.4%)
↓-33.3%prior 6

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-01-31 · 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: 2019-01-01 through 2019-01-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-01-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,795

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: January 2019." Published July 5, 2026. Reporting period: 2019-01-01 to 2019-01-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/january-2019-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 — January 2019 | ThatCarHitMe.com