Yearly Traffic Safety Analysis

46 CRASHES IN
RUTLAND TOWN, VT
2024

All metrics benchmarked against2023

Rutland Town experienced a 6.1% decrease in total crashes, from 49 in the prior year to 46 in the current year. The most significant change observed was a 100% reduction in fatalities, with 0 fatalities reported in the current period compared to 1 in the prior year.

46

▼ -6.1%was 49

Total Crash Events

0

▼ -100.0%was 1

Fatal Crashes

12

▼ -14.3%was 14

Injury Crashes

0

▼ -100.0%was 1

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.

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 Rutland Town show a decrease in severity year-over-year. Total crashes decreased by 6.1%, from 49 to 46. Fatalities saw a significant 100% reduction, dropping from 1 to 0, while injuries also decreased by 14.3%, from 14 to 12.

When Crashes Happen

The temporal distribution of crashes shows a shift in peak times. The peak day for crashes moved from Wednesday with 10 crashes in the prior year to Tuesday with 11 crashes in the current year. Similarly, the peak hour shifted from 3 PM, which had 7 crashes in the prior year, to 12 PM, which recorded 9 crashes in the current year.

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

Crash severity saw notable improvements year-over-year. Fatal crashes decreased by 100%, with 0 fatal crashes in the current year compared to 1 in the prior year. The proportion of injury crashes also decreased, from 28.6% (14 crashes) in the prior year to 26.1% (12 crashes) in the current year, while the proportion of no-injury crashes increased from 69.4% to 73.9%.

Outcome by Severity (Crash Events)

Injury12minor injury crashes26.1%
↓-14.3%prior 14
No Injury34no injury crashes73.9%
→0.0%prior 34

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

The distribution of crashes by conditions shows some shifts year-over-year. Crashes occurring in cloudy weather increased from 10 (20.4%) in the prior year to 13 (28.3%) in the current year. Conversely, crashes on wet road surfaces decreased from 8 (16.3%) to 5 (10.9%). Additionally, conditions such as Freezing Precipitation (1 crash), Ice (1 crash), and Slush (1 crash) were reported in the current year, which were not present in the prior year's data.

Weather

Clear17 (50.0%)
↓-15.0%prior 20
Cloudy13 (38.2%)
↑30.0%prior 10
Rain3 (8.8%)
Freezing Precipitation1 (2.9%)

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

Lighting

Daylight37 (80.4%)
↓-5.1%prior 39
Dark9 (19.6%)
↓-10.0%prior 10

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

Road Surface

Dry29 (80.6%)
↑3.6%prior 28
Wet5 (13.9%)
↓-37.5%prior 8
Ice1 (2.8%)
Slush1 (2.8%)

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: Rutland Town, VT
  • Total crash records analyzed: 46

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). "Rutland Town, 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/rutland-town/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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Rutland Town, VT Crash Report — 2024 | ThatCarHitMe.com