Yearly Traffic Safety Analysis

7,063 CRASHES IN
VERMONT, VT
2024

All metrics benchmarked against2023

In 2024, Vermont recorded 7,063 motor vehicle crashes, a 1.6% decrease from the 7,177 crashes documented in 2023. While the overall number of incidents remained relatively stable, the data shows a notable 28% increase in crashes involving pedestrians, which rose from 100 in the prior year to 128 in the current period. Total fatalities fell by 12.3% to 57, while total injuries saw a 3.5% increase to 1,725.

7,063

▼ -1.6%was 7,177

Total Crash Events

▼ -12.3%was 65

Fatal Crashes

1,725

▲ 3.5%was 1,667

Injury Crashes

▼ -12.3%was 65

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 112 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Vermont were relatively stable year-over-year, with total incidents decreasing by a slight 1.6% from 7,177 in 2023 to 7,063 in 2024. However, the outcomes of these crashes showed a mixed trend. The number of fatalities declined by 12.3% (from 65 to 57), while the number of injuries increased by 3.5% (from 1,667 to 1,725).

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Tuesday with 1,110 incidents, a change from 2023 when Friday was the peak day with 1,263 crashes. The peak hour for collisions remained consistent, with the 4 p.m. hour seeing the highest frequency in both 2024 (619 crashes) and 2023 (636 crashes).

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes showed a slight shift year-over-year. The proportion of crashes resulting in an injury increased from 23.2% in 2023 to 24.4% in 2024. Conversely, the percentage of fatal crashes decreased from 0.9% to 0.8% of all incidents. This corresponds with a drop in the fatality rate per 100 crashes, which fell from 0.91 in 2023 to 0.81 in 2024.

Outcome by Severity (Crash Events)

Fatal57fatal crashes0.8%

↓-12.3%prior 65

Injury1,725minor injury crashes24.4%

↑3.5%prior 1,667

No Injury5,169no injury crashes73.2%

↓-3.0%prior 5,329

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · 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 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crash conditions saw some year-over-year changes, particularly in weather and road surfaces, while lighting conditions remained stable. The proportion of crashes occurring in daylight was nearly identical at approximately 75% in both 2024 and 2023. However, crashes on snowy roads increased from 6.1% to 7.3% of the total, while those on wet roads decreased from 12.5% to 10.9%. Similarly, the share of crashes during rainy conditions fell from 6.9% to 5.5%.

Weather

Clear3,423 (64.5%)

↑2.0%prior 3,355

Cloudy906 (17.1%)

↓-17.0%prior 1,091

Freezing Precipitation575 (10.8%)

↑4.5%prior 550

Rain387 (7.3%)

↓-21.7%prior 494

Wind16 (0.3%)

↑220.0%prior 5

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight5,284 (75.6%)

↓-1.7%prior 5,376

Dark1,706 (24.4%)

↓-0.7%prior 1,718

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry3,786 (71.1%)

↓-1.8%prior 3,855

Wet770 (14.5%)

↓-14.0%prior 895

Snow514 (9.6%)

↑16.6%prior 441

Ice127 (2.4%)

↓-29.1%prior 179

Slush50 (0.9%)

↓-27.5%prior 69

Sand, mud, dirt, oil, gravel43 (0.8%)

↑13.2%prior 38

Water (standing / moving)21 (0.4%)

↑23.5%prior 17

Other - Explain in Narrative16 (0.3%)

↓-30.4%prior 23

Source: Vermont Crash Data · Arcgis Open Data · 2024-01-01 to 2024-12-31 · 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 2024-12-31
Report generated: July 5, 2026

Data Coverage

Reporting period: 2024-01-01 through 2024-12-31 (366 days)
Geographic scope: vermont, VT
Total crash records analyzed: 7,063

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: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/2024-annual-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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7,063 CRASHES INVERMONT, VT2024