Yearly Traffic Safety Analysis

1,410 CRASHES IN
BURLINGTON, VT
2017

All metrics benchmarked against2016

In 2017, Burlington recorded 1,410 total traffic crashes, an increase of 12.3% from the 1,256 crashes documented in 2016. Despite the rise in overall collisions, the number of people injured decreased by 20.5%, falling from 151 in 2016 to 120 in 2017. This indicates that while crashes became more frequent, they resulted in fewer injuries than in the prior year.

1,410

12.3%was 1,256

Total Crash Events

0

Fatal Crashes

120

-20.5%was 151

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

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Burlington shows a rising trend, with total collisions increasing from 1,256 in 2016 to 1,410 in 2017, a 12.3% year-over-year increase. This rise in crash volume was accompanied by a notable decrease in injuries, which fell from 151 to 120 during the same period. While more crashes occurred, the number of resulting injuries declined.

When Crashes Happen

Temporal analysis reveals a shift in daily crash patterns between the two years. The peak day for crashes moved from Friday (247 crashes) in 2016 to Tuesday (249 crashes) in 2017. The peak hour also shifted slightly earlier, from 3 p.m. (110 crashes) in 2016 to 2 p.m. (130 crashes) in 2017. Weekday afternoons remained the most common time for collisions in both periods.

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes recorded in Burlington in either 2017 or 2016. However, the severity of non-fatal crashes decreased year-over-year. The proportion of collisions resulting in an injury dropped from 12.0% in 2016 to 8.5% in 2017. This corresponds with a 20.5% reduction in the total number of people injured, which fell from 151 to 120.

Outcome by Severity (Crash Events)

Injury120minor injury crashes8.5%
-20.5%prior 151
No Injury1,211no injury crashes85.9%
10.9%prior 1,092

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The conditions under which crashes occurred shifted between 2016 and 2017. The proportion of crashes happening on dry roads during clear weather decreased significantly; crashes on dry roads accounted for 75.1% of incidents in 2016 but only 58.9% in 2017. Correspondingly, there was an increase in the number of crashes reported during adverse weather, with collisions in rain increasing from 53 to 84 and those involving freezing precipitation rising from 50 to 74. Lighting conditions remained consistent, with daylight crashes accounting for approximately 79% of all incidents in both years.

Weather

Clear758 (68.7%)
-11.4%prior 856
Cloudy187 (17.0%)
-1.6%prior 190
Rain84 (7.6%)
58.5%prior 53
Freezing Precipitation74 (6.7%)
48.0%prior 50

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight1,119 (79.6%)
13.5%prior 986
Dark286 (20.4%)
6.7%prior 268

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry831 (75.8%)
-11.9%prior 943
Wet167 (15.2%)
19.3%prior 140
Snow64 (5.8%)
33.3%prior 48
Ice16 (1.5%)
23.1%prior 13
Slush16 (1.5%)
77.8%prior 9
Water (standing / moving)1 (0.1%)
Sand, mud, dirt, oil, gravel1 (0.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: Burlington, VT
  • Total crash records analyzed: 1,410

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: 2017." Published July 5, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/burlington/2017-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 — 2017 | ThatCarHitMe.com