Monthly Traffic Safety Analysis

4 CRASHES IN
BERNARDSTON, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

In December 2025, BERNARDSTON experienced 4 total crashes, an increase of 33.33% compared to the 3 total crashes reported in December 2024. Despite the increase in total crashes, there was a significant and positive shift in safety outcomes, with total fatalities decreasing by 100% from 1 in the prior period to 0 in the current period. Similarly, total injuries also decreased by 100%, from 1 in December 2024 to 0 in December 2025.

4

33.3%was 3

Total Crash Events

0

-100.0%was 1

Persons Killed

0

-100.0%was 1

Persons Injured

0

-100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in BERNARDSTON increased by 33.33%, from 3 crashes in December 2024 to 4 crashes in December 2025. However, a positive trend was observed in crash severity, with total fatalities decreasing by 100% from 1 to 0, and total injuries also decreasing by 100% from 1 to 0 year-over-year.

When Crashes Happen

The temporal patterns of crashes showed shifts between the two periods. The peak day for crashes shifted from Tuesday in December 2024, which recorded 1 crash, to Saturday in December 2025, which recorded 2 crashes. The peak hour also shifted from 11 PM in the prior period to 10 PM in the current period, with both hours recording 1 crash each.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Road & Environmental Conditions

Weather conditions for crashes showed a notable shift towards more adverse conditions in the current period, with 3 of 4 crashes occurring in snowy or severe crosswind conditions, compared to 0 of 3 crashes in such conditions in the prior period. Road surface conditions also shifted, with 3 crashes occurring on snow in December 2025, whereas December 2024 crashes were distributed across dry, ice, and wet surfaces. Lighting conditions remained similar, with 3 of 4 crashes occurring in unlighted dark conditions in the current period, an increase from 2 of 3 in the prior period.

Weather

Clear1 (25.0%)
Severe crosswinds1 (25.0%)
Snow/Blowing sand, snow1 (25.0%)
Snow/Snow1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted3 (75.0%)
Daylight1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Snow3 (75.0%)
Dry1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (5 vehicles)

1
KIA1 (20%)
2
MACK1 (20%)
3
RAM1 (20%)
4
SUBARU1 (20%)
5
TOYOTA1 (20%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

Sex Distribution (5 persons with recorded sex)

Male3 (60.0%)
0.0%prior 3
Female2 (40.0%)
100.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes by speed limit zones shifted between the two periods. In December 2025, crashes occurred in 15 mph (1 crash), 30 mph (1 crash), and 65 mph (2 crashes) zones. In contrast, December 2024 recorded crashes in 45 mph (1 crash) and 50 mph (1 crash) zones. Notably, the prior period recorded one fatal crash in a 45 mph zone, while no fatal crashes were recorded in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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_yearly 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: BERNARDSTON, MA
  • Total crash records analyzed: 4
  • Total persons involved: 5
  • Total vehicles involved: 5

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). "BERNARDSTON, MA Crash Intelligence Report: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bernardston/december-2025-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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Bernardston, MA Crash Report — December 2025 | ThatCarHitMe.com