Monthly Traffic Safety Analysis

1,009 CRASHES IN
VERMONT, VT
NOVEMBER 2014

All metrics benchmarked againstNovember 2013

In November 2014, there were 1,009 total crashes, a 26.2% decrease from the 1,367 crashes recorded in November 2013. While overall collisions declined, the proportion of crashes resulting in injury increased from 13.8% to 18.4%. The most notable shift in crash circumstances was the significant increase in collisions occurring on snowy roads and during freezing precipitation.

1,009

▼ -26.2%was 1,367

Total Crash Events

5

▼ -16.7%was 6

Fatal Crashes

186

▼ -1.6%was 189

Injury Crashes

5

▼ -16.7%was 6

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for November 2014 indicates a significant downward trend compared to the same month in the previous year. Total crashes fell by 26.2%, from 1,367 in November 2013 to 1,009 in November 2014. This overall decrease was also reflected in slight reductions in both fatalities, which dropped from 6 to 5, and total injuries, which decreased from 189 to 186.

When Crashes Happen

The temporal patterns of crashes remained broadly consistent year-over-year, with Friday being the peak day for collisions in both November 2014 (174 crashes) and November 2013 (273 crashes). The 5 p.m. hour was also the peak time for crashes in both periods, with 98 incidents in 2014 and 127 in 2013. While most days saw a decrease in crashes, Monday was a notable exception, with collisions increasing from 157 to 170 year-over-year.

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Although the total number of crashes decreased, the proportion of collisions resulting in injury or death increased. The fatal crash rate rose from 0.4% of all incidents in November 2013 to 0.5% in November 2014. Similarly, the share of crashes causing non-fatal injuries increased from 13.8% to 18.4% over the same period, indicating that a greater percentage of crashes in the more recent period involved some level of physical harm.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.5%
↓-16.7%prior 6
Injury186minor injury crashes18.4%
↓-1.6%prior 189
No Injury817no injury crashes81%
↓-4.9%prior 859

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Most severe injury per crash record

Road & Environmental Conditions

Year-over-year data shows a shift in the conditions under which crashes occurred. The proportion of collisions happening on snowy road surfaces more than doubled, increasing from 6.4% in November 2013 to 14.9% in November 2014. This corresponds with a rise in crashes during freezing precipitation, which accounted for 18.3% of incidents in 2014, up from 9.8% the prior year. In contrast, the percentage of crashes occurring in darkness decreased from 37.0% to 28.7%.

Weather

Clear397 (43.3%)
↓-15.5%prior 470
Cloudy260 (28.4%)
↑3.2%prior 252
Freezing Precipitation185 (20.2%)
↑38.1%prior 134
Rain71 (7.7%)
↑14.5%prior 62
Wind4 (0.4%)

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Weather condition at time of crash

Lighting

Daylight712 (71.1%)
↓-16.7%prior 855
Dark290 (28.9%)
↓-42.6%prior 505

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · Lighting condition field

Road Surface

Dry538 (58.0%)
↓-9.3%prior 593
Snow150 (16.2%)
↑70.5%prior 88
Wet138 (14.9%)
↓-0.7%prior 139
Ice68 (7.3%)
↓-18.1%prior 83
Slush25 (2.7%)
↑4.2%prior 24
Water (standing / moving)4 (0.4%)
Other - Explain in Narrative3 (0.3%)
↓-40.0%prior 5
Sand, mud, dirt, oil, gravel2 (0.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2014-11-01 to 2014-11-30 · 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: 2014-11-01 through 2014-11-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2014-11-01 through 2014-11-30 (30 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,009

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: November 2014." Published July 5, 2026. Reporting period: 2014-11-01 to 2014-11-30. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/november-2014-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 — November 2014 | ThatCarHitMe.com