Yearly Traffic Safety Analysis

24 CRASHES IN
LUNENBURG, VT
2019

All metrics benchmarked against2018

Total crashes in Lunenburg, VT, significantly increased by 140% year-over-year, rising from 10 crashes in 2018 to 24 crashes in 2019. Despite this overall increase in crash incidents, total injuries decreased from 3 in 2018 to 1 in 2019.

24

140.0%was 10

Total Crash Events

0

Fatal Crashes

1

-66.7%was 3

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. 13 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

Overall, crash incidents in Lunenburg, VT, showed a substantial increase year-over-year. The total number of crashes rose by 140%, from 10 crashes in 2018 to 24 crashes in 2019.

When Crashes Happen

The peak day for crashes shifted from Friday in 2018, with 3 crashes, to Saturday in 2019, with 5 crashes. The peak hour also changed, moving from 3 PM with 3 crashes in 2018 to 2 PM with 6 crashes in 2019. Crashes in 2019 were reported across 9 months, compared to 6 months in 2018, indicating a broader distribution throughout the year.

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

Total fatalities remained at 0 in both 2018 and 2019. However, total injuries decreased from 3 in 2018 to 1 in 2019. The proportion of crashes resulting in injury also significantly decreased, from 30% (3 out of 10 crashes) in 2018 to 4.2% (1 out of 24 crashes) in 2019.

Outcome by Severity (Crash Events)

Injury1minor injury crashes4.2%
-66.7%prior 3
No Injury10no injury crashes41.7%
42.9%prior 7

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

In 2019, Daylight conditions accounted for 17 crashes, an increase from 6 crashes in 2018. Crashes occurring in Dark conditions also increased from 4 in 2018 to 7 in 2019. The number of crashes in Cloudy conditions rose from 1 in 2018 to 3 in 2019, and crashes during Freezing Precipitation also increased from 1 to 3.

Weather

Clear4 (36.4%)
-33.3%prior 6
Cloudy3 (27.3%)
Freezing Precipitation3 (27.3%)
Rain1 (9.1%)

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

Lighting

Daylight17 (70.8%)
183.3%prior 6
Dark7 (29.2%)

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

Road Surface

Wet4 (36.4%)
Snow3 (27.3%)
Dry2 (18.2%)
Ice2 (18.2%)

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: Lunenburg, VT
  • Total crash records analyzed: 24

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). "Lunenburg, 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/lunenburg/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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Lunenburg, VT Crash Report — 2019 | ThatCarHitMe.com