Monthly Traffic Safety Analysis

643 CRASHES IN
VERMONT, VT
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Vermont recorded 643 total traffic crashes, an 18.7% decrease from the 791 crashes recorded in March 2022. This downward trend was also reflected in crash outcomes, with total injuries falling from 148 to 117 and fatalities decreasing from 4 to 3 year-over-year. The most notable shift was the overall reduction in crash volume across the state.

643

-18.7%was 791

Total Crash Events

3

-25.0%was 4

Fatal Crashes

117

-20.9%was 148

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

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Vermont improved in March 2023 compared to the same month in the prior year. Total crashes decreased by 18.7%, falling from 791 to 643. This improvement extended to crash severity, with total injuries declining by 20.9% (from 148 to 117) and fatalities dropping from 4 to 3.

When Crashes Happen

The temporal patterns of crashes showed some consistency and some shifts between March 2022 and March 2023. Wednesday remained the peak day for crashes in both periods, with 159 incidents in 2022 and 114 in 2023. However, the peak hour for crashes shifted slightly from the 3 p.m. hour in 2022 (75 crashes) to the 4 p.m. hour in 2023 (58 crashes). Notably, Saturday crashes saw a significant decrease, dropping from 143 in March 2022 to 79 in March 2023.

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes showed a slight improvement in March 2023 compared to the prior year. The number of fatal crashes decreased from 4 to 3, though the proportion of fatal crashes relative to the total remained stable at 0.5% for both periods. The percentage of crashes resulting in an injury also saw a slight dip, from 18.7% (148 crashes) in March 2022 to 18.2% (117 crashes) in March 2023. Correspondingly, the share of crashes involving no injuries increased from 63.3% to 80.1% year-over-year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
-25.0%prior 4
Injury117minor injury crashes18.2%
-20.9%prior 148
No Injury515no injury crashes80.1%
2.8%prior 501

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by lighting conditions remained nearly unchanged, with approximately 73% occurring in daylight in both March 2023 and March 2022. When examining road surface conditions, the proportion of crashes on dry roads was stable, accounting for 55.5% of incidents with a recorded condition in 2023 versus 55.6% in 2022. However, there was a notable increase in crashes on icy surfaces, which accounted for 6.4% of crashes with a reported road condition in 2023, up from 3.5% in the prior year.

Weather

Clear230 (46.8%)
-14.2%prior 268
Freezing Precipitation133 (27.1%)
17.7%prior 113
Cloudy113 (23.0%)
11.9%prior 101
Rain15 (3.1%)
-37.5%prior 24

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight470 (74.1%)
-18.5%prior 577
Dark164 (25.9%)
-20.0%prior 205

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry277 (55.5%)
-3.1%prior 286
Snow100 (20.0%)
5.3%prior 95
Wet67 (13.4%)
-22.1%prior 86
Ice32 (6.4%)
77.8%prior 18
Slush19 (3.8%)
-9.5%prior 21
Sand, mud, dirt, oil, gravel2 (0.4%)
Other - Explain in Narrative2 (0.4%)

Source: Vermont Crash Data · Arcgis Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 643

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: March 2023." Published July 5, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/march-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 — March 2023 | ThatCarHitMe.com