Yearly Traffic Safety Analysis

1,439 CRASHES IN
BURLINGTON, VT
2018

All metrics benchmarked against2017

In 2018, Burlington recorded 1,439 total vehicle crashes, a 2.1% increase from the 1,410 crashes reported in 2017. While overall crash volume remained relatively stable, the most significant year-over-year change was the occurrence of two fatal crashes in 2018, resulting in two fatalities, compared to zero in the prior year. Another notable shift was a 58.3% decrease in crashes involving suspected driving under the influence (DUI), which fell from 24 incidents in 2017 to 10 in 2018.

1,439

▲ 2.1%was 1,410

Total Crash Events

2

Fatal Crashes

122

▲ 1.7%was 120

Injury Crashes

2

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 12 crashes with unreported severity are not shown in the severity breakdown.

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 traffic crash volume in Burlington saw a slight increase from 2017 to 2018. The total number of crashes rose by 2.1%, from 1,410 to 1,439. The number of injuries resulting from these crashes also increased marginally by 1.7%, from 120 to 122, indicating a relatively stable trend in crash frequency and outcomes.

When Crashes Happen

The temporal patterns of crashes showed a distinct shift between the two periods. In 2018, the peak day for crashes was Friday, with 293 incidents, whereas in 2017, the peak day was Tuesday with 249 crashes. The busiest hour also shifted later in the day, from the 2 p.m. hour in 2017 (130 crashes) to the 5 p.m. hour in 2018 (134 crashes).

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

Crash severity outcomes worsened in 2018, primarily due to the introduction of fatal incidents. Two crashes in 2018 were fatal, resulting in two deaths, compared to zero fatal crashes in 2017. The number of injury-resulting crashes remained nearly constant, with 122 in 2018 versus 120 in the prior year. As a proportion of all collisions, injury crashes accounted for 8.5% in both periods.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.1%
Injury122minor injury crashes8.5%
↑1.7%prior 120
No Injury1,303no injury crashes90.5%
↑7.6%prior 1,211

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

When comparing crash conditions, the most reliable data points to a minor shift in lighting. Crashes occurring in the dark accounted for 18.8% of the total in 2018 (271 incidents), down from 20.3% in 2017 (286 incidents). Consequently, a slightly higher proportion of crashes occurred during daylight hours in 2018. Data for weather and road surface conditions was not sufficiently consistent across both years to support a direct comparison.

Weather

Clear309 (63.2%)
↓-59.2%prior 758
Cloudy99 (20.2%)
↓-47.1%prior 187
Rain42 (8.6%)
↓-50.0%prior 84
Freezing Precipitation37 (7.6%)
↓-50.0%prior 74
Wind2 (0.4%)

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

Lighting

Daylight1,166 (81.1%)
↑4.2%prior 1,119
Dark271 (18.9%)
↓-5.2%prior 286

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

Road Surface

Dry348 (70.3%)
↓-58.1%prior 831
Wet80 (16.2%)
↓-52.1%prior 167
Snow43 (8.7%)
↓-32.8%prior 64
Ice10 (2.0%)
↓-37.5%prior 16
Slush9 (1.8%)
↓-43.8%prior 16
Other - Explain in Narrative4 (0.8%)
Sand, mud, dirt, oil, gravel1 (0.2%)

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: Burlington, VT
  • Total crash records analyzed: 1,439

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: 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/burlington/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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Burlington, VT Crash Report — 2018 | ThatCarHitMe.com