Yearly Traffic Safety Analysis

120 CRASHES IN
RICHMOND, VT
2017

All metrics benchmarked against2016

In 2017, Richmond experienced 120 crashes, a 5.26% increase from the 114 crashes recorded in 2016. The total number of injuries also saw a slight increase from 17 to 18. The most notable shift was a 46.67% increase in crashes occurring during Freezing Precipitation conditions, rising from 15 in 2016 to 22 in 2017.

120

5.3%was 114

Total Crash Events

0

Fatal Crashes

18

5.9%was 17

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

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Richmond showed a slight upward trend, increasing by 5.26% from 114 crashes in 2016 to 120 crashes in 2017. Total injuries also saw a marginal rise of 5.88%, from 17 in 2016 to 18 in 2017, while fatalities remained at zero in both years.

When Crashes Happen

Friday remained the peak day for crashes in both years, with the count increasing from 23 in 2016 to 34 in 2017. The peak hour for crashes consistently remained at 3p, recording 10 crashes in both 2016 and 2017. Notably, crashes on Thursday increased by 81.82% from 11 to 20, while crashes on Tuesday decreased by 43.48% from 23 to 13.

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both 2016 and 2017, indicating no change in the fatal crash rate. Injury-involved crashes increased slightly from 17 (14.9% of total crashes) in 2016 to 18 (15% of total crashes) in 2017. Crashes resulting in no injury also saw a minor increase from 71 to 72, though their proportion of total crashes slightly decreased from 62.3% to 60%.

Outcome by Severity (Crash Events)

Injury18minor injury crashes15%
5.9%prior 17
No Injury72no injury crashes60%
1.4%prior 71

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in 'Cloudy' conditions increased by 50% from 18 in 2016 to 27 in 2017, and crashes during 'Freezing Precipitation' rose by 46.67% from 15 to 22. Concurrently, crashes in 'Clear' weather decreased by 17.95% from 39 to 32. Crashes occurring in 'Dark' lighting conditions increased by 33.33% from 30 in 2016 to 40 in 2017, while crashes on 'Snow' road surfaces rose by 42.86% from 14 to 20.

Weather

Clear32 (36.4%)
-17.9%prior 39
Cloudy27 (30.7%)
50.0%prior 18
Freezing Precipitation22 (25.0%)
46.7%prior 15
Rain7 (8.0%)
-22.2%prior 9

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight80 (66.7%)
-4.8%prior 84
Dark40 (33.3%)
33.3%prior 30

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry45 (51.1%)
0.0%prior 45
Snow20 (22.7%)
42.9%prior 14
Wet16 (18.2%)
14.3%prior 14
Ice6 (6.8%)
0.0%prior 6
Water (standing / moving)1 (1.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: Richmond, VT
  • Total crash records analyzed: 120

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). "Richmond, VT Crash Intelligence Report: 2017." Published July 5, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/richmond/2017-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

ThatCarHitMe.com · An Injuria.ai Company

Richmond, VT Crash Report — 2017 | ThatCarHitMe.com