Yearly Traffic Safety Analysis

643 CRASHES IN
SOUTH BURLINGTON, VT
2021

All metrics benchmarked against2020

In 2021, South Burlington experienced 643 total crashes, an increase from the 551 crashes recorded in 2020. This represents a 16.7% rise in overall crash incidents year-over-year. A notable shift was the substantial decrease in total fatalities, dropping from 3 in 2020 to 1 in 2021.

643

▲ 16.7%was 551

Total Crash Events

1

▼ -66.7%was 3

Fatal Crashes

72

▲ 75.6%was 41

Injury Crashes

1

▼ -66.7%was 3

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 40 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in South Burlington showed an upward trend, increasing by 16.7% from 551 crashes in 2020 to 643 crashes in 2021. Despite this rise in total crashes, there was a significant positive trend in fatalities, which decreased by 66.7% from 3 to 1. Conversely, total injuries saw a substantial increase of 75.6%, rising from 41 to 72.

When Crashes Happen

The temporal distribution of crashes showed some shifts year-over-year. The peak day for crashes moved from Wednesday in 2020 (106 crashes) to Friday in 2021 (123 crashes). While the peak hour remained 4 PM for both years, the number of crashes at this hour increased from 61 in 2020 to 68 in 2021. Monthly crash trends also changed, with 2020 showing higher crashes in January and February, whereas 2021 saw higher numbers in the latter half of the year, particularly from June to December.

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Regarding crash severity, there was a positive trend in fatal incidents, with the fatal crash rate decreasing from 0.54% in 2020 to 0.16% in 2021. However, injury-involved crashes saw an increase, with their proportion rising from 7.4% of all crashes in 2020 to 11.2% in 2021. Concurrently, the proportion of crashes resulting in no injuries slightly decreased from 84.8% to 82.4% year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
↓-66.7%prior 3
Injury72minor injury crashes11.2%
↑75.6%prior 41
No Injury530no injury crashes82.4%
↑13.5%prior 467

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes by conditions saw some shifts between 2020 and 2021. Crashes occurring in clear weather conditions slightly increased from 46.46% to 48.06% of all incidents, while those in cloudy conditions decreased from 12.34% to 9.64%. Notably, crashes on snowy road surfaces saw a significant decrease in proportion, falling from 5.44% in 2020 to 2.64% in 2021. Crashes occurring in daylight conditions slightly increased in proportion from 82.94% to 84.14%, with a corresponding decrease in dark condition crashes from 16.88% to 15.71%.

Weather

Clear309 (74.1%)
↑20.7%prior 256
Cloudy62 (14.9%)
↓-8.8%prior 68
Rain28 (6.7%)
↑75.0%prior 16
Freezing Precipitation18 (4.3%)
↓-33.3%prior 27

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight541 (84.3%)
↑18.4%prior 457
Dark101 (15.7%)
↑8.6%prior 93

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry328 (77.5%)
↑13.5%prior 289
Wet63 (14.9%)
↑21.2%prior 52
Snow17 (4.0%)
↓-43.3%prior 30
Other - Explain in Narrative6 (1.4%)
Ice5 (1.2%)
→0.0%prior 5
Slush3 (0.7%)
Sand, mud, dirt, oil, gravel1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: South Burlington, VT
  • Total crash records analyzed: 643

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). "South Burlington, VT Crash Intelligence Report: 2021." Published July 5, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/south-burlington/2021-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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South Burlington, VT Crash Report — 2021 | ThatCarHitMe.com