Monthly Traffic Safety Analysis

711 CRASHES IN
VERMONT, VT
APRIL 2017

All metrics benchmarked againstApril 2016

In April 2017, there were 711 total crashes recorded in Vermont, representing a 23.1% decrease from the 924 crashes in April 2016. This downward trend extended to crash outcomes, with total fatalities dropping from 6 to 2 year-over-year. The most notable shift was the change in the daily pattern of collisions, with the peak day for crashes moving from Monday in 2016 to Saturday in 2017.

711

-23.1%was 924

Total Crash Events

2

-66.7%was 6

Fatal Crashes

138

-9.2%was 152

Injury Crashes

2

-66.7%was 6

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 97 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for April 2017 indicates a significant year-over-year decrease across key metrics compared to April 2016. Total crashes fell by 23.1%, from 924 to 711 incidents. In line with this trend, the number of people injured in collisions decreased by 9.2% from 152 to 138, while total fatalities fell from 6 to 2.

When Crashes Happen

The timing of crashes shifted between the two periods. The peak day for collisions moved from Monday (184 crashes) in April 2016 to Saturday (133 crashes) in April 2017. A similar change occurred with the peak hour, which shifted from 11 a.m. (79 crashes) in the prior year to 3 p.m. (67 crashes) in the current year. The overall reduction in crashes was concentrated on weekdays, while weekend crash totals remained nearly identical year-over-year.

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes showed mixed changes compared to the prior year. The proportion of fatal crashes decreased, accounting for 0.3% of all incidents in April 2017, down from 0.6% in April 2016. Conversely, the share of crashes resulting in an injury increased from 16.5% to 19.4% year-over-year. Crashes involving no injuries constituted 66.7% of the total in the current period, a slight increase from 65.3% previously.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
-66.7%prior 6
Injury138minor injury crashes19.4%
-9.2%prior 152
No Injury474no injury crashes66.7%
-21.4%prior 603

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Most severe injury per crash record

Road & Environmental Conditions

The environmental conditions during crashes varied between the two periods. In April 2017, a slightly larger share of crashes occurred after dark (22.6%) compared to April 2016 (20.9%). The proportion of collisions on non-dry road surfaces also increased, rising from 22.1% in the prior year to 25.4% in the current period. Crashes in adverse weather, such as rain or freezing precipitation, accounted for 17.2% of incidents with reported weather, up from 15.7% the previous year.

Weather

Clear328 (59.5%)
-30.4%prior 471
Cloudy128 (23.2%)
19.6%prior 107
Rain76 (13.8%)
123.5%prior 34
Freezing Precipitation19 (3.4%)
-74.3%prior 74

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Weather condition at time of crash

Lighting

Daylight537 (76.9%)
-25.1%prior 717
Dark161 (23.1%)
-16.6%prior 193

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · Lighting condition field

Road Surface

Dry414 (74.6%)
-24.0%prior 545
Wet114 (20.5%)
56.2%prior 73
Snow13 (2.3%)
-76.4%prior 55
Ice5 (0.9%)
-64.3%prior 14
Sand, mud, dirt, oil, gravel4 (0.7%)
-55.6%prior 9
Slush4 (0.7%)
Other - Explain in Narrative1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2017-04-01 to 2017-04-30 · 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: 2017-04-01 through 2017-04-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2017-04-01 through 2017-04-30 (30 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 711

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: April 2017." Published July 5, 2026. Reporting period: 2017-04-01 to 2017-04-30. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/april-2017-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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Vermont (Statewide) Crash Report — April 2017 | ThatCarHitMe.com