Yearly Traffic Safety Analysis

1,404 CRASHES IN
BURLINGTON, VT
2019

All metrics benchmarked against2018

Burlington experienced a slight decrease in total crashes, from 1439 in the prior period to 1404 in the current period, representing a 2.4% reduction. The most significant year-over-year shift was the complete elimination of crash fatalities, decreasing from 2 to 0.

1,404

-2.4%was 1,439

Total Crash Events

0

-100.0%was 2

Fatal Crashes

119

-2.5%was 122

Injury Crashes

0

-100.0%was 2

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 7 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, crashes in Burlington showed a slight downward trend year-over-year, with total crashes decreasing by 2.4% from 1439 to 1404. This was accompanied by a 2.5% decrease in total injuries, from 122 to 119, and a 100% reduction in fatalities from 2 to 0.

When Crashes Happen

The peak day for crashes shifted from Friday with 293 crashes in the prior period to Wednesday with 246 crashes in the current period. Similarly, the peak crash hour moved from 5p (134 crashes) in the prior period to 3p (123 crashes) in the current period.

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

Fatalities decreased significantly from 2 in the prior period to 0 in the current period, representing a 100% reduction in fatal crashes. The proportion of injury crashes remained stable at 8.5% in both periods, with the absolute number of injury crashes slightly decreasing from 122 to 119.

Outcome by Severity (Crash Events)

Injury119minor injury crashes8.5%
-2.5%prior 122
No Injury1,278no injury crashes91%
-1.9%prior 1,303

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

Crashes in clear weather conditions increased from 309 to 343, while crashes in rainy conditions decreased from 42 to 34. There was a decrease in crashes during daylight hours from 1166 to 1114, and an increase in crashes during dark hours from 271 to 286. Crashes on dry road surfaces increased from 348 to 378, while crashes on wet surfaces slightly decreased from 80 to 77.

Weather

Clear343 (66.1%)
11.0%prior 309
Cloudy98 (18.9%)
-1.0%prior 99
Freezing Precipitation42 (8.1%)
13.5%prior 37
Rain34 (6.6%)
-19.0%prior 42
Wind2 (0.4%)

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

Lighting

Daylight1,114 (79.6%)
-4.5%prior 1,166
Dark286 (20.4%)
5.5%prior 271

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

Road Surface

Dry378 (72.8%)
8.6%prior 348
Wet77 (14.8%)
-3.8%prior 80
Snow41 (7.9%)
-4.7%prior 43
Ice15 (2.9%)
50.0%prior 10
Slush7 (1.3%)
-22.2%prior 9
Other - Explain in Narrative1 (0.2%)

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: Burlington, VT
  • Total crash records analyzed: 1,404

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). "Burlington, 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/burlington/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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Burlington, VT Crash Report — 2019 | ThatCarHitMe.com