Yearly Traffic Safety Analysis

40 CRASHES IN
CLARENDON, VT
2016

All metrics benchmarked against2015

Total crashes decreased by 35.48% from 62 in the prior period to 40 in the current period. While overall incidents declined, the most notable shift is the emergence of one fatal crash and one fatality in the current period, compared to zero in the prior period. This indicates a concerning increase in crash severity despite fewer overall incidents.

40

-35.5%was 62

Total Crash Events

1

Fatal Crashes

11

22.2%was 9

Injury Crashes

1

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 13 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 shows a significant decrease in total crashes, falling by 35.48% from 62 crashes in the prior period to 40 crashes in the current period. This indicates a notable reduction in the total number of crash events year-over-year.

When Crashes Happen

The temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Friday with 14 incidents in the prior period to Thursday with 9 incidents in the current period. Similarly, the peak crash hour changed from 5 PM with 7 crashes in the prior period to 3 PM with 4 crashes in the current period.

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 saw a notable increase, with one fatal crash and one fatality reported in the current period, compared to zero fatal crashes and fatalities in the prior period. Injury crashes also increased proportionally, accounting for 27.5% of all crashes (11 crashes) in the current period compared to 14.5% (9 crashes) in the prior period. This indicates that while total crashes decreased, the proportion and count of more severe outcomes rose.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.5%
Injury11minor injury crashes27.5%
22.2%prior 9
No Injury15no injury crashes37.5%
-21.1%prior 19

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

There were shifts in crash conditions year-over-year. Crashes occurring in daylight decreased from 42 in the prior period to 25 in the current period, while those in dark conditions decreased from 20 to 15. Regarding road surface, dry conditions accounted for 21 crashes in the current period compared to 14 in the prior period, while crashes on snow and wet surfaces decreased from 5 to 2 and 4 to 2, respectively.

Weather

Clear18 (66.7%)
28.6%prior 14
Cloudy6 (22.2%)
0.0%prior 6
Freezing Precipitation3 (11.1%)

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

Lighting

Daylight25 (62.5%)
-40.5%prior 42
Dark15 (37.5%)
-25.0%prior 20

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

Road Surface

Dry21 (80.8%)
50.0%prior 14
Snow2 (7.7%)
-60.0%prior 5
Wet2 (7.7%)
Other - Explain in Narrative1 (3.8%)

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: Clarendon, VT
  • Total crash records analyzed: 40

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). "Clarendon, 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/clarendon/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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Clarendon, VT Crash Report — 2016 | ThatCarHitMe.com