Yearly Traffic Safety Analysis

103 CRASHES IN
RUTLAND CITY, VT
2023

All metrics benchmarked against2022

In 2023, Rutland City experienced 103 crashes, representing an 11.2% decrease from the 116 crashes recorded in 2022. A significant shift was observed in crash outcomes, with total fatalities increasing from 0 in 2022 to 2 in 2023. This also led to an increase in fatal crashes from 0 to 2 year-over-year.

103

-11.2%was 116

Total Crash Events

2

Fatal Crashes

47

27.0%was 37

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.

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Rutland City decreased by 11.2%, from 116 crashes in 2022 to 103 crashes in 2023. Despite this reduction in total incidents, the number of fatal crashes increased from 0 in 2022 to 2 in 2023, indicating a concerning trend in crash severity.

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day moving from Friday in 2022, which had 22 crashes, to Tuesday in 2023, with 20 crashes. Similarly, the peak crash hour changed from 5 PM in 2022, recording 13 crashes, to 3 PM in 2023, with 14 crashes. This indicates a change in the times when crashes are most frequent.

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes changed significantly, with fatal crashes increasing from 0 in 2022 to 2 in 2023, resulting in a fatal crash rate of 1.9% in the current period. Injury crashes also saw an increase in both count and proportion, rising from 37 (31.9% of total) in 2022 to 47 (45.6% of total) in 2023. Conversely, crashes resulting in no injury decreased from 79 (68.1%) to 54 (52.4%) year-over-year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.9%
Injury47minor injury crashes45.6%
27.0%prior 37
No Injury54no injury crashes52.4%
-31.6%prior 79

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by conditions saw notable shifts. Crashes occurring in clear weather increased from 42.2% of all crashes in 2022 to 56.3% in 2023, while crashes during daylight hours decreased from 81.9% to 72.8%. Concurrently, crashes in dark conditions increased from 18.1% in 2022 to 27.2% in 2023. Crashes on dry road surfaces also saw a notable increase in proportion, rising from 48.3% to 69.9%.

Weather

Clear58 (63.0%)
18.4%prior 49
Cloudy20 (21.7%)
25.0%prior 16
Rain11 (12.0%)
57.1%prior 7
Freezing Precipitation2 (2.2%)
Wind1 (1.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight75 (72.8%)
-21.1%prior 95
Dark28 (27.2%)
33.3%prior 21

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry72 (79.1%)
28.6%prior 56
Wet17 (18.7%)
30.8%prior 13
Snow2 (2.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: Rutland City, VT
  • Total crash records analyzed: 103

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 City, VT Crash Intelligence Report: 2023." Published July 5, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/rutland-city/2023-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 City, VT Crash Report — 2023 | ThatCarHitMe.com