ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ATTLEBOROUGH, MA · MARCH 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.
Monthly Traffic Safety Analysis
38 CRASHES IN
NORTH ATTLEBOROUGH, MA
MARCH 2025
In March 2025, NORTH ATTLEBOROUGH experienced 38 total crashes, a decrease of 15.6% compared to the 45 crashes reported in March 2024. Fatalities remained at 0 in both periods, while total injuries were stable at 11. Notably, there were no serious injuries reported in March 2025, down from 2 serious injuries in March 2024.
38
▼ -15.6%was 45
Total Crash Events
0
Persons Killed
11
Persons Injured
3
▼ -25.0%was 4
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in crash data for NORTH ATTLEBOROUGH shows a decrease year-over-year, with total crashes falling from 45 in March 2024 to 38 in March 2025. This represents a 15.6% reduction in total crash incidents. Fatalities remained consistent at 0 in both periods, and total injuries also remained stable at 11.
3
Hit-and-Run Crashes — March 2025
▼ -25.0% vs prior (4)
The number of hit-and-run crashes decreased from 4 in March 2024 to 3 in March 2025. Concurrently, the hit-and-run rate decreased from 8.9% of total crashes to 7.9% of total crashes. This indicates a downward trend in both the count and rate of hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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 Thursday in both periods, with 9 crashes recorded on this day in both March 2024 and March 2025. However, the peak hour for crashes shifted from 6 p.m. with 5 crashes in March 2024 to 4 p.m. with 10 crashes in March 2025. Crashes on Tuesday decreased from 9 to 5, while crashes on Monday increased from 5 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities and fatal crashes remained at 0 in both March 2024 and March 2025, with total injuries stable at 11 in both periods. Serious injuries (severity 'A') decreased from 2 in March 2024 to 0 in March 2025. Minor injuries increased from 5 (11.1% of crashes) to 7 (18.4% of crashes), and possible injuries increased from 2 (4.4% of crashes) to 3 (7.9% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'Followed too closely', decreased slightly from 10 crashes in March 2024 to 9 crashes in March 2025. 'No improper driving' decreased by 4 crashes, from 9 to 5, while 'Inattention' increased from 5 crashes to 6 crashes. 'Failed to yield right of way' saw a notable increase from 2 crashes to 5 crashes, and 'Other improper action' increased from 1 crash to 5 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 19 to 14, and those in 'Rain' conditions decreased from 7 to 2. The proportion of crashes on dry road surfaces increased significantly from 27 (60%) to 34 (89.5%). Conversely, crashes on wet road surfaces decreased from 17 to 4. Daylight remained the dominant lighting condition for crashes, accounting for 33 crashes in March 2024 and 30 in March 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 87 in March 2024 to 70 in March 2025. Toyota became the most frequently involved make, with its count increasing from 11 vehicles to 17 vehicles. Honda's involvement decreased from 13 vehicles to 7 vehicles, and Chevrolet's decreased from 12 vehicles to 5 vehicles.
Top Vehicle Makes (70 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (79 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 9 to 2, and those in the 40 mph speed zone decreased from 14 to 5. Crashes in the 65 mph speed zone also decreased, from 14 to 6. The 25 mph speed zone, not present in the prior period's data, accounted for 2 crashes in March 2025. Fatal crashes remained at 0 across all reported speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-03-01 through 2025-03-31 (31 days)
- Geographic scope: NORTH ATTLEBOROUGH, MA
- Total crash records analyzed: 38
- Total persons involved: 83
- Total vehicles involved: 70
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). "NORTH ATTLEBOROUGH, MA Crash Intelligence Report: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/march-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-03-01 – 2025-03-31
Generated: June 21, 2026 · All rights reserved