Monthly Traffic Safety Analysis

1,413 CRASHES IN
VERMONT, VT
MARCH 2014

All metrics benchmarked againstMarch 2013

In March 2014, there were 1,413 total crashes recorded in Vermont, representing a 21.0% increase from the 1,168 crashes documented in March 2013. While the number of fatalities was stable with one death in each period, total reported injuries rose from 136 to 151. The most significant year-over-year change was the overall increase in the volume of collisions, which occurred alongside a shift in the daily peak time for crashes from the evening to the morning commute.

1,413

▲ 21.0%was 1,168

Total Crash Events

1

Fatal Crashes

151

▲ 11.0%was 136

Injury Crashes

1

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 436 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for March 2014 indicates an upward trend compared to the same month in the prior year. Total crashes increased by 21.0%, from 1,168 in March 2013 to 1,413 in March 2014. This increase was accompanied by a rise in total injuries from 136 to 151, while fatalities held steady at one for both periods.

When Crashes Happen

The temporal patterns of crashes showed a notable shift between the two periods. The peak hour for collisions moved from the 5 p.m. hour in March 2013 (87 crashes) to the 8 a.m. hour in March 2014 (132 crashes). While Friday remained the day with the most crashes in both years, the volume on Friday increased from 211 to 286. Crashes on Wednesdays also saw a significant year-over-year increase, rising from 168 in 2013 to 285 in 2014.

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained unchanged at one in both March 2013 and March 2014, though the fatal crash rate decreased slightly from 0.09% to 0.07% of total crashes due to the higher overall volume. The absolute number of injury-related incidents rose from 136 to 151. However, as a proportion of all crashes, injury crashes decreased from 11.6% in 2013 to 10.7% in 2014.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
→0.0%prior 1
Injury151minor injury crashes10.7%
↑11.0%prior 136
No Injury825no injury crashes58.4%
↑0.5%prior 821

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Most severe injury per crash record

Road & Environmental Conditions

There was a noticeable shift in the conditions under which crashes occurred. The proportion of crashes taking place in daylight increased from 65.1% of all incidents in March 2013 (760 crashes) to 74.0% in March 2014 (1,045 crashes). In terms of road surface, the proportion of crashes on non-dry surfaces remained relatively stable, accounting for 32.4% of crashes in 2014 compared to 33.1% in the prior year.

Weather

Clear474 (53.9%)
↑16.2%prior 408
Cloudy195 (22.2%)
↓-19.8%prior 243
Freezing Precipitation172 (19.6%)
↓-14.0%prior 200
Rain20 (2.3%)
↓-23.1%prior 26
Wind18 (2.0%)

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Weather condition at time of crash

Lighting

Daylight1,045 (74.3%)
↑37.5%prior 760
Dark362 (25.7%)
↓-6.7%prior 388

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · Lighting condition field

Road Surface

Dry438 (48.9%)
↓-13.1%prior 504
Snow203 (22.7%)
↑19.4%prior 170
Wet104 (11.6%)
↓-10.3%prior 116
Ice103 (11.5%)
↑45.1%prior 71
Slush32 (3.6%)
↑88.2%prior 17
Sand, mud, dirt, oil, gravel8 (0.9%)
↑14.3%prior 7
Other - Explain in Narrative7 (0.8%)
Water (standing / moving)1 (0.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2014-03-01 to 2014-03-31 · 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: 2014-03-01 through 2014-03-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2014-03-01 through 2014-03-31 (31 days)
  • Geographic scope: vermont, VT
  • Total crash records analyzed: 1,413

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: March 2014." Published July 5, 2026. Reporting period: 2014-03-01 to 2014-03-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/statewide/march-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

ThatCarHitMe.com · An Injuria.ai Company

Vermont (Statewide) Crash Report — March 2014 | ThatCarHitMe.com