Monthly Traffic Safety Analysis

683 CRASHES IN
VERMONT, VT
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, there were 683 total traffic crashes, a 2.1% increase from the 669 crashes recorded in January 2023. While total crashes and fatalities remained relatively stable, the most notable year-over-year change was a 62.5% increase in crashes involving pedestrians, which rose from 8 to 13 incidents.

683

2.1%was 669

Total Crash Events

2

Fatal Crashes

134

-5.0%was 141

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

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Comparing January 2024 to the same month in the prior year, the overall number of traffic crashes saw a slight increase of 2.1%, rising from 669 to 683. Despite the rise in total incidents, the number of resulting injuries decreased by 5.0% from 141 to 134. The number of fatalities remained unchanged at two for both periods.

When Crashes Happen

The temporal patterns of crashes shifted between January 2023 and January 2024. The peak day for crashes moved from Friday (155 crashes) in the prior year to Tuesday (126 crashes) in the current period. While the 5 p.m. hour remained the peak time for collisions in both years, the number of crashes during this hour increased from 46 to 63. The daily distribution of crashes was more evenly spread in January 2024, lacking the sharp Friday peak observed in the previous year.

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes showed a slight shift year-over-year. The number of fatal crashes remained constant at two incidents in both January 2024 and January 2023, with the fatal crash rate holding steady at approximately 0.3%. However, the proportion of crashes resulting in any injury decreased from 21.1% of all crashes in the prior year to 19.6% in the current period. Correspondingly, no-injury crashes increased as a share of the total, rising from 76.8% to 78.6%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
0.0%prior 2
Injury134minor injury crashes19.6%
-5.0%prior 141
No Injury537no injury crashes78.6%
4.5%prior 514

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record

Road & Environmental Conditions

In January 2024, a larger share of crashes occurred during daylight hours (72.6%) compared to January 2023 (68.6%). Crashes in clear weather conditions became more prevalent, accounting for 30.6% of incidents, up from 26.2% in the prior year. Similarly, the proportion of crashes on dry road surfaces increased from 25.9% to 31.5% year-over-year, even as collisions on roads with snow also saw a slight proportional increase from 21.2% to 23.0%.

Weather

Clear209 (38.2%)
19.4%prior 175
Freezing Precipitation188 (34.4%)
6.2%prior 177
Cloudy131 (23.9%)
6.5%prior 123
Rain16 (2.9%)
-30.4%prior 23
Wind3 (0.5%)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash

Lighting

Daylight496 (73.2%)
8.1%prior 459
Dark182 (26.8%)
-5.7%prior 193

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field

Road Surface

Dry215 (38.7%)
24.3%prior 173
Snow157 (28.3%)
10.6%prior 142
Wet109 (19.6%)
4.8%prior 104
Ice48 (8.6%)
-15.8%prior 57
Slush20 (3.6%)
-20.0%prior 25
Other - Explain in Narrative5 (0.9%)
Water (standing / moving)1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 683

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 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/january-2024-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 2024 | ThatCarHitMe.com