ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ATTLEBOROUGH, MA · SEPTEMBER 2022
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
44 CRASHES IN
NORTH ATTLEBOROUGH, MA
SEPTEMBER 2022
In September 2022, NORTH ATTLEBOROUGH experienced 44 crashes, an increase from the 38 crashes recorded in September 2021, representing a 15.8% rise. The most significant year-over-year shift was a 54.5% increase in total injuries, from 11 to 17.
44
▲ 15.8%was 38
Total Crash Events
0
Persons Killed
17
▲ 54.5%was 11
Persons Injured
3
▲ 50.0%was 2
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 · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Total crashes in NORTH ATTLEBOROUGH increased from 38 in September 2021 to 44 in September 2022. This represents an upward trend, with a 15.8% increase in crash incidents year-over-year.
3
Hit-and-Run Crashes — September 2022
▲ 50.0% vs prior (2)
Hit-and-run crashes increased from 2 incidents in September 2021 to 3 in September 2022. Concurrently, the hit-and-run rate rose from 5.3% to 6.8% year-over-year, indicating an upward trend in the proportion of crashes involving a hit-and-run.
Vulnerable Road User Casualties
0
Motorists Killed
0
Other Killed
15
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
In September 2022, the peak day for crashes was Friday with 13 incidents, shifting from Wednesday in September 2021 which had 9 incidents. The peak hour remained consistent with 6 crashes in both periods, but shifted from 10a in September 2021 to 11a in September 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Both September 2021 and September 2022 reported 0 fatalities and 0 fatal crashes. Total injuries increased from 11 in September 2021 to 17 in September 2022, a 54.5% increase. While serious injury crashes (severity A) decreased from 2 to 0, possible injury crashes (severity C) saw a notable rise from 3 incidents (7.9% share) to 8 incidents (18.2% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record
Top Contributing Factors
“No improper driving” increased from 7 incidents in September 2021 to 11 in September 2022, a 57.1% rise. “Failed to yield right of way” also saw a substantial increase from 3 incidents to 8, a 166.7% increase. Conversely, “Inattention” decreased from 9 incidents to 6, a 33.3% reduction, shifting from the top contributing factor in September 2021 (23.7% share) to third in September 2022 (13.6% share).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions (Clear or Clear/Clear) remained stable, with 31 incidents in September 2021 and 32 in September 2022. The number of crashes on dry road surfaces increased from 33 in September 2021 to 37 in September 2022. Similarly, crashes during daylight hours rose from 27 to 30 year-over-year, while crashes on wet road surfaces increased from 5 to 7.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes remained stable, decreasing slightly from 80 in September 2021 to 79 in September 2022. Toyota remained the top make involved, increasing from 11 vehicles in September 2021 to 18 in September 2022. Among persons involved, the 45-54 age group saw a notable decrease from 20 in September 2021 to 6 in September 2022, while the 65+ age group increased from 5 to 13.
Top Vehicle Makes (79 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (93 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 MPH zones increased significantly from 4 in September 2021 to 13 in September 2022. Incidents in 40 MPH zones also rose from 7 to 14 year-over-year. Conversely, crashes in 65 MPH zones decreased from 11 in September 2021 to 7 in September 2022, indicating a shift in crash distribution towards lower posted speed limits.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-09-01 through 2022-09-30 (30 days)
- Geographic scope: NORTH ATTLEBOROUGH, MA
- Total crash records analyzed: 44
- Total persons involved: 107
- Total vehicles involved: 79
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: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/september-2022-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: 2022-09-01 – 2022-09-30
Generated: June 21, 2026 · All rights reserved