Yearly Traffic Safety Analysis

138 CRASHES IN
RUTLAND TOWN, VT
2019

All metrics benchmarked against2018

In Rutland Town, total crashes increased significantly by 165.38%, rising from 52 in 2018 to 138 in 2019. The number of injuries also saw a substantial increase, climbing by 183.33% from 6 in 2018 to 17 in 2019. This marked increase in overall crash activity and injuries is the most notable year-over-year shift.

138

165.4%was 52

Total Crash Events

0

Fatal Crashes

17

183.3%was 6

Injury Crashes

0

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 83 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for Rutland Town shows a substantial increase in crashes year-over-year, with total crashes rising from 52 in 2018 to 138 in 2019. This represents a 165.38% increase in crash incidents. Injuries also rose significantly, from 6 in 2018 to 17 in 2019, marking a 183.33% increase.

When Crashes Happen

The peak day for crashes shifted from Wednesday with 11 crashes in 2018 to Tuesday with 26 crashes in 2019. Similarly, the peak hour for crashes changed from 2 PM with 6 crashes in 2018 to 12 PM with 16 crashes in 2019. These shifts indicate a change in the temporal distribution of crash occurrences between the two years.

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both 2018 and 2019. Injury crashes increased from 6 in 2018 to 17 in 2019, representing a 183.33% rise. The proportion of total crashes that resulted in injury slightly increased from 11.5% in 2018 to 12.3% in 2019.

Outcome by Severity (Crash Events)

Injury17minor injury crashes12.3%
183.3%prior 6
No Injury38no injury crashes27.5%
-17.4%prior 46

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Despite a significant increase in total crashes, the number of crashes occurring in "Clear" weather decreased from 31 in 2018 to 20 in 2019, and "Rain" crashes decreased from 4 to 2. Conversely, crashes in "Cloudy" weather increased from 7 to 10, and "Freezing Precipitation" crashes rose from 5 to 8. Regarding road surface conditions, crashes on "Dry" surfaces decreased from 35 to 29, "Wet" surfaces from 8 to 4, and "Ice" surfaces from 4 to 3, while crashes on "Snow" surfaces increased from 3 to 6. Crashes in "Daylight" increased from 45 to 115, and in "Dark" conditions from 6 to 23, consistent with the overall rise in total crashes.

Weather

Clear20 (50.0%)
-35.5%prior 31
Cloudy10 (25.0%)
42.9%prior 7
Freezing Precipitation8 (20.0%)
60.0%prior 5
Rain2 (5.0%)

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash

Lighting

Daylight115 (83.3%)
155.6%prior 45
Dark23 (16.7%)
283.3%prior 6

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field

Road Surface

Dry29 (64.4%)
-17.1%prior 35
Snow6 (13.3%)
Wet4 (8.9%)
-50.0%prior 8
Ice3 (6.7%)
Slush2 (4.4%)
Other - Explain in Narrative1 (2.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-12-31 (365 days)
  • Geographic scope: Rutland Town, VT
  • Total crash records analyzed: 138

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: 2019." Published July 5, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/rutland-town/2019-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 — 2019 | ThatCarHitMe.com