Yearly Traffic Safety Analysis

107 CRASHES IN
SHELBURNE, VT
2018

All metrics benchmarked against2017

Total crashes in Shelburne for the current year were 107, a slight decrease from 109 crashes in the prior year. This represents a 1.8% reduction in overall crash incidents year-over-year. A significant shift was observed in pedestrian-involved crashes, which increased from 0 in the prior year to 5 in the current year.

107

▼ -1.8%was 109

Total Crash Events

0

Fatal Crashes

18

▲ 50.0%was 12

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.

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained relatively stable, decreasing slightly from 109 to 107, a 1.8% reduction. However, the number of total injuries increased by 50%, rising from 12 in the prior year to 18 in the current year. This suggests a trend towards more severe outcomes despite a marginal decrease in crash frequency.

When Crashes Happen

The peak day for crashes shifted from Tuesday in the prior year, with 23 crashes, to Wednesday in the current year, with 20 crashes. Similarly, the peak crash hour moved from 3 PM, which had 21 crashes in the prior year, to 5 PM, which had 14 crashes in the current year. These changes indicate a shift in the most frequent times for crash occurrences.

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both the current and prior periods. However, the total number of injuries increased by 50%, from 12 in the prior year to 18 in the current year. Consequently, the proportion of injury crashes rose from 11% of all crashes in the prior year to 16.8% in the current year.

Outcome by Severity (Crash Events)

Injury18minor injury crashes16.8%
↑50.0%prior 12
No Injury89no injury crashes83.2%
↓-8.2%prior 97

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in Freezing Precipitation conditions decreased by 50%, from 12 in the prior year to 6 in the current year. There was also a decrease in crashes during dark lighting conditions, falling from 20 to 14. Conversely, crashes on wet road surfaces increased by 83.3%, from 6 in the prior year to 11 in the current year.

Weather

Clear48 (62.3%)
↑9.1%prior 44
Cloudy17 (22.1%)
↑6.3%prior 16
Freezing Precipitation6 (7.8%)
↓-50.0%prior 12
Rain6 (7.8%)

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight93 (86.9%)
↑4.5%prior 89
Dark14 (13.1%)
↓-30.0%prior 20

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry62 (73.8%)
↑5.1%prior 59
Wet11 (13.1%)
↑83.3%prior 6
Snow5 (6.0%)
↓-50.0%prior 10
Ice4 (4.8%)
Slush1 (1.2%)
Sand, mud, dirt, oil, gravel1 (1.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: Shelburne, VT
  • Total crash records analyzed: 107

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). "Shelburne, VT Crash Intelligence Report: 2018." Published July 5, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/shelburne/2018-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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Shelburne, VT Crash Report — 2018 | ThatCarHitMe.com