Monthly Traffic Safety Analysis

1,085 CRASHES IN
VERMONT, VT
JANUARY 2017

All metrics benchmarked againstJanuary 2016

In January 2017, Vermont recorded 1,085 total vehicle crashes, a 3.0% increase from the 1,053 crashes reported in January 2016. Despite the rise in total incidents, the number of reported injuries saw a significant decrease, falling 24.1% from 195 to 148 year-over-year. The number of fatalities remained unchanged at three for both periods.

1,085

▲ 3.0%was 1,053

Total Crash Events

3

Fatal Crashes

148

▼ -24.1%was 195

Injury Crashes

3

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 223 crashes with unreported severity are not shown in the severity breakdown.

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

Trend Summary

Overall crash totals in Vermont saw a slight increase in January 2017 compared to the same month in the prior year, rising by 3.0% from 1,053 to 1,085 incidents. However, this increase in total crashes was accompanied by a notable 24.1% decrease in the number of people injured, which fell from 195 to 148. The number of fatalities held steady at three in both periods.

When Crashes Happen

The temporal patterns of crashes showed some shifts between January 2016 and January 2017. While Tuesday remained the peak day for crashes in both periods, the peak hour shifted from the 5 p.m. evening commute in 2016 (83 crashes) to the 8 a.m. morning commute in 2017 (78 crashes). Crashes during the 7 a.m. and 8 a.m. hours increased from a combined 119 in 2016 to 151 in 2017.

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

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

Crash Severity Breakdown

The severity of crashes shifted toward less severe outcomes in January 2017 compared to the previous year. While the number of fatal crashes remained constant at three for both periods, the number of crashes resulting in an injury decreased from 195 to 148. Consequently, the proportion of total crashes involving an injury fell from 18.5% in January 2016 to 13.6% in January 2017.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.3%
→0.0%prior 3
Injury148minor injury crashes13.6%
↓-24.1%prior 195
No Injury711no injury crashes65.5%
↓-11.7%prior 805

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

Road & Environmental Conditions

Analysis of crash conditions reveals notable year-over-year differences. The proportion of crashes occurring in dark lighting conditions increased from 26.3% of all crashes in January 2016 to 34.7% in January 2017. Regarding road surface, crashes on snowy roads saw a significant decrease, accounting for 9.9% of incidents in 2017 compared to 22.2% in 2016. Crashes on icy roads saw a slight proportional increase from 8.5% to 10.1% of the monthly total.

Weather

Clear362 (47.0%)
↓-19.9%prior 452
Cloudy240 (31.1%)
↑12.7%prior 213
Freezing Precipitation147 (19.1%)
↓-38.0%prior 237
Rain20 (2.6%)
↑122.2%prior 9
Wind2 (0.3%)

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

Lighting

Daylight694 (64.8%)
↓-9.3%prior 765
Dark377 (35.2%)
↑36.1%prior 277

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

Road Surface

Dry399 (51.4%)
↓-5.2%prior 421
Wet125 (16.1%)
↓-7.4%prior 135
Ice110 (14.2%)
↑22.2%prior 90
Snow107 (13.8%)
↓-54.3%prior 234
Slush25 (3.2%)
↑31.6%prior 19
Sand, mud, dirt, oil, gravel7 (0.9%)
↑40.0%prior 5
Other - Explain in Narrative4 (0.5%)
↓-55.6%prior 9

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

Data Coverage

  • Reporting period: 2017-01-01 through 2017-01-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,085

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: January 2017." Published July 5, 2026. Reporting period: 2017-01-01 to 2017-01-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/january-2017-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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Vermont (Statewide) Crash Report — January 2017 | ThatCarHitMe.com