ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ATTLEBORO, MA · MARCH 2026
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/attleboro/march-2026-report
Monthly Traffic Safety Analysis
78 CRASHES IN
ATTLEBORO, MA
MARCH 2026
ATTLEBORO experienced an 11.4% increase in total crashes, rising from 70 in March 2025 to 78 in March 2026. This period saw a critical shift with the occurrence of one fatal crash and one fatality in March 2026, compared to zero in the prior year. Additionally, hit-and-run incidents surged by 166.7%, marking a significant change in crash characteristics.
78
▲ 11.4%was 70
Total Crash Events
1
Persons Killed
29
▼ -12.1%was 33
Persons Injured
8
▲ 166.7%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash activity, with total crashes rising from 70 in March 2025 to 78 in March 2026, representing an 11.4% increase. This upward trend is also reflected in a notable increase in severe outcomes, including the emergence of fatal crashes.
8
Hit-and-Run Crashes — March 2026
▲ 166.7% vs prior (3)
Hit-and-run crashes increased significantly, rising by 166.7% from 3 incidents in March 2025 to 8 incidents in March 2026. This increase caused the hit-and-run rate to trend upward, from 4.3% of total crashes to 10.3%.
Vulnerable Road User Casualties
1
Motorists Killed
29
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Saturday (15 crashes) in March 2025 to Monday and Tuesday (both 15 crashes) in March 2026. The peak crash hour moved from 2 p.m. (10 crashes) in the prior period to 5 p.m. (12 crashes) in the current period. Crashes on Saturday decreased by 53.3% from 15 to 7, while Tuesday crashes increased by 66.7% from 9 to 15.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in March 2025 to 1 in March 2026, with total fatalities also rising from 0 to 1. Serious injury crashes increased from 0 to 1, and minor injury crashes increased from 11 to 15. However, possible injury crashes decreased from 15 to 8, resulting in a slight decrease in the overall proportion of injury crashes from 37.1% to 30.8%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Followed too closely' increased by 54.5% from 11 to 17, and 'Failed to yield right of way' increased by 30.8% from 13 to 17. 'Inattention' crashes saw a substantial 140% increase from 5 to 12. Conversely, 'Failure to keep in proper lane or running off road' decreased by 40% from 10 to 6, and 'No improper driving' decreased by 50% from 6 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions (Clear/Clear and Clear) decreased from 59 to 53. Conversely, crashes in wet road surface conditions increased by 183.3% from 6 to 17. Notably, the current period recorded 2 crashes during snow weather conditions and 3 crashes on icy road surfaces, neither of which were reported in the prior period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 120 to 169. Toyota remained the most common make, with its involvement increasing from 19 to 35 vehicles. Honda also saw a significant increase in involvement, from 10 to 24 vehicles, while Hyundai remained consistent at 15 vehicles. The age group 0-15 saw a 79.2% decrease in involved persons, from 24 to 5, whereas the 21-25 age group increased by 100% from 16 to 32 involved persons.
Top Vehicle Makes (169 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (188 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 65 mph speed zones doubled, increasing from 9 to 18, and this zone accounted for the single fatality in March 2026. Crashes in 40 mph zones increased by 77.8% from 9 to 16. Conversely, crashes in 25 mph zones decreased by 60% from 5 to 2, and 35 mph zones decreased by 33.3% from 9 to 6.
Fatal crashes by zone: 65 mph: 1 of 18 (5.556%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: ATTLEBORO, MA
- Total crash records analyzed: 78
- Total persons involved: 212
- Total vehicles involved: 169
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). "ATTLEBORO, MA Crash Intelligence Report: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/attleboro/march-2026-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: 2026-03-01 – 2026-03-31
Generated: June 21, 2026 · All rights reserved