Yearly Traffic Safety Analysis

608 CRASHES IN
SOUTH BURLINGTON, VT
2022

All metrics benchmarked against2021

In 2022, South Burlington recorded 608 total crashes, a decrease of 5.44% from the 643 crashes reported in 2021. Despite this overall reduction, bicycle-involved crashes saw a significant increase, rising by 200% from 3 incidents in 2021 to 9 in 2022.

608

-5.4%was 643

Total Crash Events

1

Fatal Crashes

72

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. 14 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight decrease in total crashes year-over-year, with 608 crashes in 2022 compared to 643 in 2021, representing a 5.44% reduction. Fatalities remained stable at 1 in both years, and total injuries also remained unchanged at 72.

When Crashes Happen

The temporal patterns of crashes shifted between 2021 and 2022. The peak day for crashes moved from Friday in 2021 (123 crashes) to Thursday in 2022 (113 crashes), while the peak hour shifted from 4 p.m. (68 crashes in 2021) to 5 p.m. (64 crashes in 2022). Notably, Friday crashes decreased by 18.7% from 123 to 100 incidents.

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained constant at 1 in both 2021 and 2022, with the fatal crash rate holding steady at 0.16% in both periods. The number of injury crashes also remained stable at 72. However, the proportion of injury crashes increased from 11.2% in 2021 to 11.8% in 2022, while the proportion of no-injury crashes increased from 82.4% to 85.7%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Injury72minor injury crashes11.8%
0.0%prior 72
No Injury521no injury crashes85.7%
-1.7%prior 530

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 309 in 2021 to 322 in 2022, and crashes on dry road surfaces also rose from 328 to 344. Conversely, crashes on wet road surfaces decreased by 14.3%, from 63 in 2021 to 54 in 2022. Crashes on snowy roads increased from 17 to 22, a 29.4% rise, and crashes on slushy roads doubled from 3 to 6.

Weather

Clear322 (74.9%)
4.2%prior 309
Cloudy65 (15.1%)
4.8%prior 62
Rain26 (6.0%)
-7.1%prior 28
Freezing Precipitation17 (4.0%)
-5.6%prior 18

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight518 (85.5%)
-4.3%prior 541
Dark88 (14.5%)
-12.9%prior 101

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry344 (79.3%)
4.9%prior 328
Wet54 (12.4%)
-14.3%prior 63
Snow22 (5.1%)
29.4%prior 17
Slush6 (1.4%)
Ice5 (1.2%)
0.0%prior 5
Other - Explain in Narrative2 (0.5%)
-66.7%prior 6
Water (standing / moving)1 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: South Burlington, VT
  • Total crash records analyzed: 608

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: 2022." Published July 5, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/south-burlington/2022-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 — 2022 | ThatCarHitMe.com