Yearly Traffic Safety Analysis

12,669 CRASHES IN
VERMONT, VT
2017

All metrics benchmarked against2016

In 2017, there were 12,669 total traffic crashes, a figure nearly identical to the 12,657 crashes recorded in 2016, representing a marginal increase of less than 0.1%. Despite the stable number of total incidents, the most significant year-over-year change was a 14.5% decrease in the total number of injuries, which fell from 2,301 to 1,967.

12,669

▲ 0.1%was 12,657

Total Crash Events

▲ 8.5%was 59

Fatal Crashes

1,967

▼ -14.5%was 2,301

Injury Crashes

▲ 8.5%was 59

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 2,428 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

Overall crash trends remained stable between 2016 and 2017, with total crashes increasing by only 12 incidents from 12,657 to 12,669. However, the outcomes of these crashes shifted; total fatalities rose by 8.5% from 59 to 64, while total injuries saw a significant 14.5% reduction from 2,301 to 1,967.

When Crashes Happen

The temporal patterns of crashes showed some year-over-year shifts. While Friday remained the peak day for crashes in both 2016 (2,153 crashes) and 2017 (2,342 crashes), the peak hour for incidents moved earlier from the 5 p.m. hour in 2016 to the 3 p.m. hour in 2017. December was the month with the highest crash volume in both periods, with an increase from 1,596 crashes in December 2016 to 1,858 in December 2017.

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

The severity of crashes shifted between 2016 and 2017. While the number of fatal crashes increased from 59 to 64, the fatal crash rate per 100 crashes saw a slight rise from 0.47 to 0.51. More significantly, the proportion of crashes resulting in an injury decreased from 18.2% in 2016 to 15.5% in 2017, corresponding to a drop from 2,301 total injuries to 1,967. Crashes with no reported injuries remained the largest category, accounting for approximately 65% of all incidents in both years.

Outcome by Severity (Crash Events)

Fatal64fatal crashes0.5%

↑8.5%prior 59

Injury1,967minor injury crashes15.5%

↓-14.5%prior 2,301

No Injury8,210no injury crashes64.8%

↓-0.7%prior 8,270

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

Crash conditions varied between the two periods, particularly concerning road surfaces. In 2017, crashes on dry roads accounted for 46.0% of the total, a decrease from 53.2% in 2016. Conversely, the share of crashes occurring on snowy, icy, or slush-covered roads increased from 12.2% in 2016 to 13.5% in 2017. This corresponds with a drop in crashes during 'Clear' weather conditions, which fell from 47.7% to 41.0% of all incidents. Lighting conditions remained consistent, with roughly 74% of crashes in both years occurring during daylight.

Weather

Clear5,190 (57.7%)

↓-14.0%prior 6,032

Cloudy1,887 (21.0%)

↑5.8%prior 1,783

Freezing Precipitation1,216 (13.5%)

↑7.5%prior 1,131

Rain681 (7.6%)

↓-1.0%prior 688

Wind27 (0.3%)

↑28.6%prior 21

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

Lighting

Daylight9,349 (74.5%)

↓-0.4%prior 9,387

Dark3,197 (25.5%)

↑1.7%prior 3,145

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

Road Surface

Dry5,830 (64.5%)

↓-13.5%prior 6,738

Wet1,379 (15.3%)

↑4.4%prior 1,321

Snow1,169 (12.9%)

↑21.1%prior 965

Ice416 (4.6%)

↓-4.8%prior 437

Slush129 (1.4%)

↓-5.8%prior 137

Sand, mud, dirt, oil, gravel58 (0.6%)

↓-30.1%prior 83

Other - Explain in Narrative29 (0.3%)

↓-19.4%prior 36

Water (standing / moving)24 (0.3%)

↑26.3%prior 19

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: vermont, VT
Total crash records analyzed: 12,669

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). "vermont, 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/statewide/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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12,669 CRASHES INVERMONT, VT2017