ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TAUNTON, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/taunton/2025-annual-report
Yearly Traffic Safety Analysis
1,869 CRASHES IN
TAUNTON, MA
2025
In 2025, Taunton recorded 1,869 total traffic crashes, a 16.2% decrease from the 2,229 crashes reported in 2024. Despite this significant drop in overall incidents, the total number of injuries remained unchanged at 601 for both years. The number of fatalities also held steady at 5.
1,869
▼ -16.2%was 2,229
Total Crash Events
5
Persons Killed
601
Persons Injured
194
▼ -10.2%was 216
Hit-and-Run Crashes
Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 86 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data indicates a downward trend in the total number of crashes in Taunton, with a 16.2% reduction from 2,229 in 2024 to 1,869 in 2025. However, this decrease in crash frequency did not correspond to a decrease in severe outcomes. The number of total fatalities remained constant at 5, and the total number of injuries was also unchanged at 601 in both periods.
194
Hit-and-Run Crashes — 2025
▼ -10.2% vs prior (216)
The total number of hit-and-run crashes decreased by 10.2%, from 216 incidents in 2024 to 194 in 2025. However, the hit-and-run rate, which measures these incidents as a percentage of total crashes, trended upward. Hit-and-runs constituted 10.4% of all crashes in 2025, an increase from the 9.7% rate recorded in the prior year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
5
Motorists Killed
0
Other Killed
17
Pedestrians Injured
8
Cyclists Injured
573
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Taunton remained consistent year-over-year. Friday was the peak day for crashes in both 2025 (293 crashes) and 2024 (359 crashes). Similarly, the 4 p.m. hour was the peak time for incidents in both periods, accounting for 168 crashes in 2025 and 212 in 2024. While the peak times did not shift, the volume of crashes during these peaks decreased in line with the overall trend.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the fatal crash rate increased from 0.22% in 2024 to 0.27% in 2025, as the number of fatal crashes held steady at 5 against a smaller total. The proportion of crashes resulting in minor or possible injuries grew, with minor injury crashes rising from a 12.6% share to a 15.1% share of all incidents. Conversely, the share of crashes with no reported injuries fell from 75.3% in 2024 to 71.3% in 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors were identical in both periods: 'Inattention,' 'No improper driving,' and 'Failed to yield right of way.' The number of crashes attributed to 'Inattention' decreased by 9.2% from 436 in 2024 to 396 in 2025, though its share of total crashes increased from 19.6% to 21.2%. Crashes involving 'Failed to yield right of way' saw a larger count reduction, falling 18.1% from 315 to 258.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions at the time of crashes showed little variation between the two years. In both 2025 and 2024, the vast majority of incidents occurred in clear weather (80.3% and 78.4% of crashes, respectively) and on dry roads (83.2% and 83.3%, respectively). Crashes during daylight hours also remained the dominant scenario, accounting for 69.4% of crashes in 2025 compared to 70.1% in 2024, indicating no significant shift in conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics involved in crashes remained stable year-over-year. The top three vehicle makes involved in collisions were Toyota, Honda, and Ford in both 2025 and 2024, with no change in their ranking. Similarly, the age distribution of persons involved in crashes showed minimal change, with the 35-44 age group representing the largest cohort in both periods (19.8% in 2025 and 19.4% in 2024).
Top Vehicle Makes (3,388 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
464 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,776 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes remained concentrated in the 30 mph speed zone, which accounted for a larger share of incidents in 2025 (48.7%) compared to 2024 (41.5%), despite a nearly identical count of crashes (910 vs. 925). The distribution of fatal crashes changed; in 2025, three fatalities occurred in 30 mph zones and one in a 65 mph zone. In contrast, 2024's fatalities were more dispersed across various speed zones, including 20, 25, 30, and 50 mph areas.
Fatal crashes by zone: 30 mph: 3 of 910 (0.33%) · 65 mph: 1 of 133 (0.752%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: TAUNTON, MA
- Total crash records analyzed: 1,869
- Total persons involved: 4,253
- Total vehicles involved: 3,388
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/2025-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved