Yearly Traffic Safety Analysis

39 CRASHES IN
NORTHFIELD, VT
2015

All metrics benchmarked against2014

In 2015, Northfield experienced 39 total crashes, an 11.43% increase from the 35 crashes recorded in 2014. The most notable shift was a 77.78% rise in total injuries, from 9 in 2014 to 16 in 2015.

39

11.4%was 35

Total Crash Events

0

Fatal Crashes

16

77.8%was 9

Injury Crashes

0

Fatal Crash Events

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

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Northfield increased year-over-year, with 39 crashes reported in 2015 compared to 35 in 2014, representing an 11.43% rise. Total injuries also saw a significant increase of 77.78%, from 9 in 2014 to 16 in 2015.

When Crashes Happen

The peak day for crashes shifted from Sunday in 2014 (7 crashes) to Tuesday in 2015 (9 crashes). The peak crash hour also changed, moving from 4 PM in 2014 (7 crashes) to 10 AM in 2015 (5 crashes).

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both 2014 and 2015. However, the proportion of injury crashes increased from 25.7% (9 crashes) in 2014 to 41% (16 crashes) in 2015, indicating a higher severity outcome for a larger share of incidents.

Outcome by Severity (Crash Events)

Injury16minor injury crashes41%
77.8%prior 9
No Injury23no injury crashes59%
-11.5%prior 26

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather increased from 22 in 2014 to 26 in 2015, while those in freezing precipitation decreased from 8 to 3. Crashes in daylight conditions increased from 27 to 33, whereas crashes in dark conditions decreased from 8 to 6. Regarding road surface, dry road crashes slightly decreased from 22 to 21, and snow-related crashes increased from 8 to 10.

Weather

Clear26 (66.7%)
18.2%prior 22
Cloudy8 (20.5%)
60.0%prior 5
Freezing Precipitation3 (7.7%)
-62.5%prior 8
Rain2 (5.1%)

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight33 (84.6%)
22.2%prior 27
Dark6 (15.4%)
-25.0%prior 8

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry21 (53.8%)
-4.5%prior 22
Snow10 (25.6%)
25.0%prior 8
Wet5 (12.8%)
Ice2 (5.1%)
Sand, mud, dirt, oil, gravel1 (2.6%)

Source: Vermont Crash Data · Arcgis Open Data · 2015-01-01 to 2015-12-31 · 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: 2015-01-01 through 2015-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: Northfield, VT
  • Total crash records analyzed: 39

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). "Northfield, VT Crash Intelligence Report: 2015." Published July 6, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/northfield/2015-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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Northfield, VT Crash Report — 2015 | ThatCarHitMe.com