ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ATTLEBOROUGH, MA · APRIL 2024
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
41 CRASHES IN
NORTH ATTLEBOROUGH, MA
APRIL 2024
Total crashes in NORTH ATTLEBOROUGH decreased from 45 in April 2023 to 41 in April 2024, representing an 8.9% reduction. Fatalities remained at zero in both periods. The most notable year-over-year shift was a 27.3% decrease in total injuries, falling from 22 to 16.
41
▼ -8.9%was 45
Total Crash Events
0
Persons Killed
16
▼ -27.3%was 22
Persons Injured
5
▲ 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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for April 2024 indicates a downward trend compared to April 2023, with total crashes decreasing by 8.9% from 45 to 41. Total injuries also saw a significant reduction, dropping by 27.3% from 22 to 16. Fatal crashes remained stable at zero in both periods.
5
Hit-and-Run Crashes — April 2024
▲ 25.0% vs prior (4)
Hit-and-run crashes increased from 4 in April 2023 to 5 in April 2024. Consequently, the hit-and-run rate rose from 8.9% of total crashes in the prior period to 12.2% in the current period. This represents an increase of 1 crash and a 3.3 percentage point rise in the hit-and-run rate.
Vulnerable Road User Casualties
0
Motorists Killed
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In April 2023, Thursday was the peak day with 11 crashes, while April 2024 saw Saturday as the peak day with 10 crashes. The peak hour for crashes also changed, moving from 12 PM with 7 crashes in April 2023 to 3 PM with 6 crashes in April 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both April 2023 and April 2024. While total injuries decreased from 22 to 16, the proportion of crashes resulting in serious injury (A) increased from 0% to 2.4% (1 crash). Minor injury (B) crashes decreased from 11 (24.4% share) to 3 (7.3% share), while possible injury (C) crashes increased from 4 (8.9% share) to 6 (14.6% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
The count of "Followed too closely" crashes decreased from 12 in April 2023 to 10 in April 2024, a 16.7% reduction. Crashes attributed to "Failed to yield right of way" and "Inattention" remained constant at 7 and 5 crashes, respectively, in both periods. Notably, crashes involving "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased from 4 in April 2023 to 0 in April 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring on wet road surfaces increased significantly, rising from 8.9% (4 crashes) in April 2023 to 29.3% (12 crashes) in April 2024. Conversely, the share of crashes occurring in daylight conditions increased from 77.8% to 85.4%. While overall clear weather conditions remained dominant, crashes during rainy conditions saw a slight increase in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 87 in April 2023 to 80 in April 2024. Honda remained the top vehicle make involved in crashes with 13 vehicles in both periods. There was a notable shift in the age distribution of persons involved, with the 0-15 age group decreasing from 12 to 3, and the 65+ age group decreasing from 16 to 7. Conversely, the 55-64 age group saw an increase from 5 to 13 persons involved.
Top Vehicle Makes (80 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (85 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 40 MPH speed zones increased from 10 in April 2023 to 17 in April 2024. Conversely, crashes in 30 MPH zones decreased from 12 to 5. Crashes in 20 MPH zones also decreased from 4 to 1, indicating a shift in crash distribution towards higher speed limits where data was available.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: NORTH ATTLEBOROUGH, MA
- Total crash records analyzed: 41
- Total persons involved: 96
- Total vehicles involved: 80
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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/april-2024-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: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved