Monthly Traffic Safety Analysis

667 CRASHES IN
VERMONT, VT
MAY 2022

All metrics benchmarked againstMay 2021

In May 2022, there were 667 total traffic crashes in Vermont, a 16.4% decrease from the 798 crashes recorded in May 2021. Despite the overall reduction in collisions, the number of reported injuries increased by 12.7% year-over-year, rising from 134 to 151. Crashes involving alcohol (DUI) also saw a notable increase of 27.8% over the same period, from 36 to 46 incidents.

667

▼ -16.4%was 798

Total Crash Events

7

▼ -12.5%was 8

Fatal Crashes

151

▲ 12.7%was 134

Injury Crashes

7

▼ -12.5%was 8

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 100 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic collisions shows a year-over-year decline for May. Total crashes fell from 798 in May 2021 to 667 in May 2022, representing a 16.4% reduction. However, this downward trend did not extend to all metrics, as total injuries rose from 134 to 151, an increase of 12.7%, and fatal crashes decreased by only one incident, from 8 to 7.

When Crashes Happen

The temporal patterns of crashes shifted between May 2021 and May 2022. The day with the most crashes moved from Friday (151 incidents) in the prior year to Tuesday (105 incidents) in the current period. Similarly, the peak hour for collisions changed from 3 p.m. (75 crashes) in 2021 to 5 p.m. (62 crashes) in 2022. While both periods show a concentration of crashes during afternoon hours, the distribution in May 2022 was more evenly spread across weekdays compared to the sharp peak on Friday observed in the previous year.

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The proportion of crashes resulting in a fatality remained stable, with a fatal crash rate of 1.0% in May 2021 and 1.05% in May 2022. A more significant shift occurred in non-fatal injury crashes, which increased both in absolute numbers (from 134 to 151) and as a proportion of all crashes, rising from 16.8% to 22.6%. This increase in crash severity occurred despite a 16.4% overall decrease in total collisions.

Outcome by Severity (Crash Events)

Fatal7fatal crashes1%
↓-12.5%prior 8
Injury151minor injury crashes22.6%
↑12.7%prior 134
No Injury409no injury crashes61.3%
↓-1.9%prior 417

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by lighting conditions remained consistent year-over-year, with daylight crashes accounting for 77.3% of incidents in May 2021 and 76.5% in May 2022. Crashes on wet roads increased from 32 to 41, while those on dry roads decreased slightly from 390 to 385. Among crashes with reported weather data, the proportion occurring in clear conditions rose from 78.5% in the prior period to 80.8% in the current period, even as the absolute number of crashes in the rain increased from 27 to 33.

Weather

Clear346 (80.8%)
↑2.1%prior 339
Cloudy48 (11.2%)
↓-26.2%prior 65
Rain33 (7.7%)
↑22.2%prior 27
Wind1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Lighting

Daylight510 (77.5%)
↓-17.3%prior 617
Dark148 (22.5%)
↓-15.4%prior 175

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry385 (88.5%)
↓-1.3%prior 390
Wet41 (9.4%)
↑28.1%prior 32
Sand, mud, dirt, oil, gravel5 (1.1%)
Other - Explain in Narrative3 (0.7%)
Ice1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 667

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: May 2022." Published July 5, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/may-2022-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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