Monthly Traffic Safety Analysis

26 CRASHES IN
FRANKLIN, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

Total crashes in Franklin decreased by 23.5% from 34 in November 2024 to 26 in November 2025. Concurrently, total injuries saw a 37.5% reduction, falling from 8 to 5. The most notable shift was a 200% increase in DUI-related crashes, rising from 1 in the prior period to 3 in the current period.

26

-23.5%was 34

Total Crash Events

0

Persons Killed

5

-37.5%was 8

Persons Injured

1

Hit-and-Run Crashes

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Franklin show a declining trend year-over-year, with total crashes decreasing by 23.5% from 34 to 26. This reduction is accompanied by a significant 37.5% decrease in total injuries, falling from 8 to 5. Despite the overall decline, DUI crashes saw a substantial increase.

1

Hit-and-Run Crashes — November 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both November 2024 and November 2025. However, due to a decrease in total crashes, the hit-and-run rate increased from 2.9% in the prior period to 3.8% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 8-37.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Sunday with 9 crashes in November 2024 to Thursday with 6 crashes in November 2025. Similarly, the peak crash hour moved from 12p with 5 crashes in the prior period to 4p with 4 crashes in the current period. This indicates a change in the temporal distribution of crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either period. The number of serious injury crashes remained constant at 1, though its proportion of total crashes increased from 2.9% to 3.8%. Minor injury crashes decreased from 5 (14.7% of total crashes) to 2 (7.7% of total crashes), contributing to the overall 37.5% reduction in total injuries.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
0.0%prior 1
Minor Injury2minor injury crashes7.7%
-60.0%prior 5
Possible Injury2possible injury crashes7.7%
No Injury21no injury crashes80.8%
-22.2%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Several key contributing factors saw notable changes: 'Inattention' crashes decreased significantly from 11 to 3, a 72.7% reduction in count, dropping its share from 32.4% to 11.5%. 'No improper driving' also decreased from 9 to 5 crashes, a 44.4% reduction in count, while 'Failure to keep in proper lane or running off road' increased from 1 to 3 crashes, a 200% increase in count. The ranking of top factors shifted, with 'No improper driving' becoming the most frequent factor in the current period.

Officer-Reported Primary Contributing Cause

No improper driving5 (19.2%)-44.4%prior 9
Failure to keep in proper lane or running off road3 (11.5%)
Inattention3 (11.5%)-72.7%prior 11
Distracted2 (7.7%)
Followed too closely2 (7.7%)
Glare1 (3.8%)
Failed to yield right of way1 (3.8%)
Fatigued/asleep1 (3.8%)
Disregarded traffic signs, signals, road markings1 (3.8%)
Operating defective equipment1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in daylight conditions decreased from 21 in November 2024 to 10 in November 2025. Conversely, crashes occurring in 'Dark - roadway not lighted' conditions increased from 3 to 7 between the two periods. The number of crashes on dry road surfaces decreased from 26 to 23, while crashes on wet surfaces decreased from 2 to 1.

Weather

Clear13 (52.0%)
8.3%prior 12
Clear/Clear8 (32.0%)
-33.3%prior 12
Cloudy/Cloudy2 (8.0%)
Cloudy1 (4.0%)
Rain/Rain1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight10 (38.5%)
-52.4%prior 21
Dark - lighted roadway7 (26.9%)
0.0%prior 7
Dark - roadway not lighted7 (26.9%)
Dark - unknown roadway lighting1 (3.8%)
Dusk1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry23 (92.0%)
-11.5%prior 26
Ice1 (4.0%)
Wet1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
FORD7 (14.9%)
0.0%prior 7
2
TOYOTA6 (12.8%)
-33.3%prior 9
3
JEEP4 (8.5%)
-20.0%prior 5
4
VOLKSWAGEN4 (8.5%)
5
NISSAN2 (4.3%)
-60.0%prior 5
6
LEXUS2 (4.3%)
7
BMW2 (4.3%)
8
HONDA2 (4.3%)
-75.0%prior 8
9
TESL2 (4.3%)
10
LNDR1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

6 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (48 persons with recorded sex)

Male30 (62.5%)
-34.8%prior 46
Female18 (37.5%)
-28.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones decreased from 5 in November 2024 to 3 in November 2025. In contrast, crashes in 30 mph zones increased from 2 to 5, and in 40 mph zones from 2 to 3. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: FRANKLIN, MA
  • Total crash records analyzed: 26
  • Total persons involved: 55
  • Total vehicles involved: 47

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). "FRANKLIN, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/franklin/november-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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Franklin, MA Crash Report — November 2025 | ThatCarHitMe.com