Yearly Traffic Safety Analysis

11 CRASHES IN
WELLS, VT
2016

All metrics benchmarked against2015

In 2016, Wells recorded 11 total crashes, a 38.9% decrease from the 18 crashes reported in 2015. The most significant year-over-year change was the reduction in traffic fatalities, which dropped from one in the prior period to zero in the current period. Despite the overall decline in collisions, the number of injuries doubled from two to four.

11

-38.9%was 18

Total Crash Events

0

-100.0%was 1

Fatal Crashes

4

100.0%was 2

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

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic collisions in Wells shows a significant year-over-year decline. Total crashes fell by 38.9%, from 18 in 2015 to 11 in 2016. While the number of fatalities decreased from one to zero, the number of reported injuries increased from two to four during the same period.

When Crashes Happen

Temporal crash patterns shifted between the two periods. In 2016, the peak time for crashes was 11 a.m., with 3 incidents, a change from the prior year's peak during the 3 p.m. and 4 p.m. hours. The most frequent crash days also changed, with Tuesday and Saturday each recording 3 crashes in 2016, compared to Thursday being the peak day with 4 crashes in 2015.

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes improved, with fatal crashes eliminated in 2016 after one was recorded in 2015, which had accounted for 5.6% of that year's total. However, the proportion of crashes resulting in an injury increased substantially, rising from 11.1% of all crashes in 2015 (2 incidents) to 36.4% in 2016 (4 incidents). The total number of people injured doubled from two to four, even as the total number of crashes decreased.

Outcome by Severity (Crash Events)

Injury4minor injury crashes36.4%
100.0%prior 2
No Injury4no injury crashes36.4%
-33.3%prior 6

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The conditions under which crashes occurred saw notable shifts. The proportion of collisions happening on dry roads increased from 33.3% (6 crashes) in 2015 to 54.5% (6 crashes) in 2016. While daylight remained the most common lighting condition in both years, the share of crashes occurring in the dark increased from 11.1% (2 crashes) to 27.3% (3 crashes). In both periods, clear weather was the most frequently cited condition, present in 27.8% of crashes in 2015 and 36.4% in 2016.

Weather

Clear4 (57.1%)
-20.0%prior 5
Cloudy1 (14.3%)
Freezing Precipitation1 (14.3%)
Rain1 (14.3%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash

Lighting

Daylight8 (72.7%)
-50.0%prior 16
Dark3 (27.3%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field

Road Surface

Dry6 (75.0%)
0.0%prior 6
Snow1 (12.5%)
Wet1 (12.5%)

Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2016-01-01 through 2016-12-31 (366 days)
  • Geographic scope: Wells, VT
  • Total crash records analyzed: 11

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). "Wells, VT Crash Intelligence Report: 2016." Published July 5, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/wells/2016-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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Wells, VT Crash Report — 2016 | ThatCarHitMe.com