Monthly Traffic Safety Analysis

182 CRASHES IN
TAUNTON, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

In December 2025, TAUNTON, MA experienced 182 crashes, an increase of 7.69% compared to the 169 crashes recorded in December 2024. Despite this rise in total crashes, the number of total injuries decreased by 19.4%, from 67 to 54. There were no traffic fatalities reported in either period.

182

7.7%was 169

Total Crash Events

0

Persons Killed

54

-19.4%was 67

Persons Injured

19

11.8%was 17

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. 10 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

Total crashes in TAUNTON, MA are rising year-over-year, with an increase from 169 crashes in December 2024 to 182 crashes in December 2025. This represents a 7.69% increase in crash incidents for the month.

19

Hit-and-Run Crashes — December 2025

11.8% vs prior (17)

Hit-and-run crashes increased from 17 in December 2024 to 19 in December 2025, a rise of 2 incidents. The hit-and-run rate also saw a slight increase, moving from 10.1% to 10.4% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

51

Motorists Injured

Prior: 67-23.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with 33 crashes in December 2025 and 32 in December 2024. However, the peak hour shifted from 5 PM in December 2024 (17 crashes) to 6 PM in December 2025 (15 crashes). Crashes on Mondays increased from 24 to 31, while Sunday crashes decreased from 21 to 14.

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)

Crash Severity Breakdown

Fatalities remained at 0 in both December 2024 and December 2025. Total injuries decreased from 67 to 54, representing a 19.4% reduction year-over-year. Serious injuries (code A) decreased from 3 (1.8% of crashes) to 1 (0.5% of crashes), and minor injuries (code B) decreased from 32 (18.9%) to 26 (14.3%).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.5%
-66.7%prior 3
Minor Injury26minor injury crashes14.3%
-18.8%prior 32
Possible Injury9possible injury crashes4.9%
-30.8%prior 13
No Injury136no injury crashes74.7%
21.4%prior 112

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'Inattention' in December 2024 (36 crashes) to 'No improper driving' in December 2025 (41 crashes). 'Inattention' crashes decreased by 11 incidents (a 30.6% reduction), while 'No improper driving' crashes increased by 11 incidents (a 36.7% increase). 'Failed to yield right of way' crashes increased by 7 incidents, from 25 to 32.

Officer-Reported Primary Contributing Cause

No improper driving41 (22.5%)36.7%prior 30
Failed to yield right of way32 (17.6%)28.0%prior 25
Inattention25 (13.7%)-30.6%prior 36
Failure to keep in proper lane or running off road17 (9.3%)142.9%prior 7
Followed too closely15 (8.2%)-11.8%prior 17
Other improper action6 (3.3%)-25.0%prior 8
Driving too fast for conditions4 (2.2%)
Over-correcting/over-steering4 (2.2%)
Disregarded traffic signs, signals, road markings3 (1.6%)
Fatigued/asleep3 (1.6%)-40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions (including 'Clear/Clear') increased from 119 in December 2024 to 143 in December 2025. Crashes on 'Dry' road surfaces also increased from 117 to 135. Conversely, crashes on 'Wet' road surfaces decreased from 37 to 29, while those on 'Ice' more than doubled from 4 to 9.

Weather

Clear/Clear76 (42.0%)
58.3%prior 48
Clear67 (37.0%)
-5.6%prior 71
Cloudy8 (4.4%)
-27.3%prior 11
Rain7 (3.9%)
-12.5%prior 8
Snow5 (2.8%)
Sleet, hail (freezing rain or drizzle)4 (2.2%)
Rain/Rain4 (2.2%)
-33.3%prior 6
Snow/Snow3 (1.7%)
Clear/Severe crosswinds1 (0.6%)
Rain/Cloudy1 (0.6%)
-80.0%prior 5

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

Lighting

Daylight100 (55.6%)
22.0%prior 82
Dark - lighted roadway65 (36.1%)
-1.5%prior 66
Dark - roadway not lighted8 (4.4%)
-11.1%prior 9
Dusk4 (2.2%)
-20.0%prior 5
Dawn3 (1.7%)

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

Road Surface

Dry135 (74.6%)
15.4%prior 117
Wet29 (16.0%)
-21.6%prior 37
Ice9 (5.0%)
Snow7 (3.9%)
-12.5%prior 8
Other1 (0.6%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 313 to 325, a 3.8% rise. NISSAN vehicles involved in crashes increased by 12, moving from 19 to 31, while HONDA vehicles decreased by 14, from 38 to 24. The 35-44 age group saw a notable increase in persons involved, rising from 62 to 91, whereas the 16-20 age group decreased from 48 to 32.

Top Vehicle Makes (325 vehicles)

1
TOYOTA52 (16%)
-1.9%prior 53
2
FORD38 (11.7%)
15.2%prior 33
3
NISSAN31 (9.5%)
63.2%prior 19
4
CHEVROLET28 (8.6%)
64.7%prior 17
5
HONDA24 (7.4%)
-36.8%prior 38
6
HYUNDAI19 (5.8%)
-13.6%prior 22
7
JEEP16 (4.9%)
0.0%prior 16
8
SUBARU11 (3.4%)
83.3%prior 6
9
KIA9 (2.8%)
-43.8%prior 16
10
VOLKSWAGEN8 (2.5%)
60.0%prior 5

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

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

Sex Distribution (361 persons with recorded sex)

Male214 (59.3%)
5.9%prior 202
Female147 (40.7%)
0.7%prior 146

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

There were no fatal crashes reported in any speed zone during either period. Crashes in the 30 mph speed zone, the most common, saw a slight increase from 88 to 91. Conversely, crashes in the 65 mph speed zone decreased from 15 to 11. Crashes in the 10 mph zone increased from 5 to 9, while those in the 15 mph zone decreased from 6 to 2.

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: TAUNTON, MA
  • Total crash records analyzed: 182
  • Total persons involved: 413
  • Total vehicles involved: 325

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). "TAUNTON, 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/taunton/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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Taunton, MA Crash Report — December 2025 | ThatCarHitMe.com