Monthly Traffic Safety Analysis

141 CRASHES IN
TAUNTON, MA
APRIL 2025

All metrics benchmarked againstApril 2024

In April 2025, TAUNTON, MA experienced 141 crashes, marking a 21.23% decrease compared to the 179 crashes reported in April 2024. The most notable shift was a 41.67% reduction in hit-and-run crashes, decreasing from 24 to 14 incidents.

141

▼ -21.2%was 179

Total Crash Events

0

Persons Killed

36

▼ -25.0%was 48

Persons Injured

14

▼ -41.7%was 24

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. 8 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year. Total crashes fell by 38 incidents, from 179 in April 2024 to 141 in April 2025, representing a 21.23% reduction.

14

Hit-and-Run Crashes — April 2025

▼ -41.7% vs prior (24)

Hit-and-run crashes decreased significantly, dropping from 24 incidents in April 2024 to 14 incidents in April 2025, a reduction of 10 crashes. This also led to a decrease in the hit-and-run rate, which fell from 13.4% to 9.9% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

35

Motorists Injured

Prior: 45↓-22.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 Tuesday (44 crashes) in April 2024 to Wednesday (26 crashes) in April 2025. Similarly, the peak crash hour moved from 4 PM (24 crashes) in April 2024 to 2 PM (15 crashes) in April 2025, indicating a shift in daily crash patterns.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either April 2024 or April 2025. Total injuries decreased from 48 in April 2024 to 36 in April 2025. Serious injuries (Severity A) saw a 50% reduction, decreasing from 4 incidents to 2 incidents year-over-year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.4%
↓-50.0%prior 4
Minor Injury17minor injury crashes12.1%
↓-22.7%prior 22
Possible Injury11possible injury crashes7.8%
→0.0%prior 11
No Injury103no injury crashes73%
↓-24.3%prior 136

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'No improper driving' was cited decreased by 12, from 38 in April 2024 to 26 in April 2025. Conversely, crashes attributed to 'Inattention' increased by 6, from 36 to 42 incidents, and 'Followed too closely' increased by 9, from 15 to 24 incidents. 'Failed to yield right of way' decreased by 6 incidents, from 17 to 11.

Officer-Reported Primary Contributing Cause

Inattention42 (29.8%)↑16.7%prior 36
No improper driving26 (18.4%)↓-31.6%prior 38
Followed too closely24 (17%)↑60.0%prior 15
Failed to yield right of way11 (7.8%)↓-35.3%prior 17
Other improper action6 (4.3%)↓-25.0%prior 8
Failure to keep in proper lane or running off road4 (2.8%)↓-63.6%prior 11
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2.1%)↓-57.1%prior 7
Driving too fast for conditions3 (2.1%)
Disregarded traffic signs, signals, road markings2 (1.4%)↓-60.0%prior 5
Over-correcting/over-steering2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 147 in April 2024 to 103 in April 2025, while crashes in 'Dark - lighted roadway' conditions increased from 22 to 29. The number of crashes on 'Dry' road surfaces decreased from 144 to 105, while crashes on 'Wet' surfaces remained relatively stable, with 33 in April 2024 and 34 in April 2025.

Weather

Clear58 (41.7%)
↓-31.8%prior 85
Clear/Clear44 (31.7%)
↓-8.3%prior 48
Rain14 (10.1%)
↓-26.3%prior 19
Rain/Rain8 (5.8%)
↑33.3%prior 6
Cloudy7 (5.0%)
↓-46.2%prior 13
Cloudy/Cloudy3 (2.2%)
Rain/Cloudy2 (1.4%)
Clear/Cloudy1 (0.7%)
Cloudy/Rain1 (0.7%)
Rain/Clear1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight103 (74.6%)
↓-29.9%prior 147
Dark - lighted roadway29 (21.0%)
↑31.8%prior 22
Dawn3 (2.2%)
Dark - unknown roadway lighting1 (0.7%)
Dark - roadway not lighted1 (0.7%)
Dusk1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry105 (75.5%)
↓-27.1%prior 144
Wet34 (24.5%)
↑3.0%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 311 in April 2024 to 257 in April 2025. Among top makes, TOYOTA saw a decrease of 11 vehicles (from 52 to 41), and HYUNDAI decreased by 15 vehicles (from 25 to 10). CHEVROLET and HONDA both saw increases in involvement, with CHEVROLET rising by 8 (from 20 to 28) and HONDA by 5 (from 20 to 25).

Top Vehicle Makes (257 vehicles)

1
TOYOTA41 (16%)
↓-21.2%prior 52
2
FORD29 (11.3%)
↓-23.7%prior 38
3
CHEVROLET28 (10.9%)
↑40.0%prior 20
4
HONDA25 (9.7%)
↑25.0%prior 20
5
NISSAN20 (7.8%)
→0.0%prior 20
6
HYUNDAI10 (3.9%)
↓-60.0%prior 25
7
KIA9 (3.5%)
↑28.6%prior 7
8
GMC9 (3.5%)
↓-30.8%prior 13
9
JEEP6 (2.3%)
↓-53.8%prior 13
10
MERCEDES-BENZ6 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

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

Sex Distribution (285 persons with recorded sex)

Male169 (59.3%)
↓-8.6%prior 185
Female116 (40.7%)
↓-41.4%prior 198

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph zones decreased by 4, from 61 in April 2024 to 57 in April 2025. Crashes in 35 mph zones decreased by 5, from 22 to 17, and in 20 mph zones by 6, from 16 to 10. There were no fatal crashes recorded in any speed limit zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: TAUNTON, MA
  • Total crash records analyzed: 141
  • Total persons involved: 328
  • Total vehicles involved: 257

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: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/april-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 — April 2025 | ThatCarHitMe.com