ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ATTLEBOROUGH, MA · OCTOBER 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
49 CRASHES IN
NORTH ATTLEBOROUGH, MA
OCTOBER 2024
In October 2024, NORTH ATTLEBOROUGH experienced 49 crashes, a 25.64% increase from the 39 crashes recorded in October 2023. A notable shift is the presence of 1 fatality in the current period, compared to zero fatalities in the prior year. Total injuries also increased by 60%, from 10 to 16.
49
▲ 25.6%was 39
Total Crash Events
1
Persons Killed
16
▲ 60.0%was 10
Persons Injured
1
▼ -80.0%was 5
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for October shows an upward trend year-over-year in NORTH ATTLEBOROUGH, with total crashes increasing by 25.64% from 39 to 49. Fatalities rose from 0 in October 2023 to 1 in October 2024, and total injuries increased by 60% from 10 to 16 during the same period.
1
Hit-and-Run Crashes — October 2024
▼ -80.0% vs prior (5)
Hit-and-run crashes decreased significantly year-over-year, dropping from 5 crashes in October 2023 to 1 crash in October 2024. This change resulted in the hit-and-run rate falling from 12.8% to 2%, indicating a downward trend.
Vulnerable Road User Casualties
1
Cyclists Killed
0
Motorists Killed
0
Cyclists Injured
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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 Tuesday with 9 crashes in October 2023 to Monday with 12 crashes in October 2024. The peak hour remained consistent at 6 crashes, occurring at 5 PM in the prior period and 4 PM in the current period. Crash distribution across other days of the week also changed, with Monday crashes increasing from 1 to 12.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution saw a significant change with the occurrence of 1 fatal crash in October 2024, compared to 0 fatal crashes in October 2023. Minor injury crashes increased in count from 4 to 11, raising their share from 10.3% to 22.4% of total crashes. Conversely, the proportion of no-injury crashes decreased from 79.5% to 69.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Followed too closely' saw a substantial increase, rising by 7 crashes from 6 to 13, representing a 116.7% increase in count and growing its share from 15.4% to 26.5%. 'Failure to keep in proper lane or running off road' also surged, increasing by 6 crashes from 1 to 7, a 600% increase in count, and its share rose from 2.6% to 14.3%. In contrast, 'No improper driving' decreased by 4 crashes, from 8 to 4, a 50% decrease in count, and its share fell from 20.5% to 8.2%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear or clear-like weather conditions increased from 34 in October 2023 to 41 in October 2024. The number of crashes on dry road surfaces also increased, from 36 to 43. Crashes occurring during daylight hours rose from 26 to 36, while those in dark-lighted roadway conditions decreased from 8 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 69 in October 2023 to 96 in October 2024. Among top makes, HONDA and TOYOTA saw increases, with HONDA rising from 11 to 16 and TOYOTA from 9 to 16. The age distribution of persons involved showed a decrease in the 16-20 age group (from 10 to 5) but significant increases in the 21-25 age group (from 5 to 20) and 26-34 age group (from 14 to 25).
Top Vehicle Makes (96 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (109 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones increased from 12 to 14, and those in 65 mph zones increased from 7 to 9. A new speed limit of 35 mph appeared in the current period with 1 crash, while 20 mph zones, which had 2 crashes in the prior period, were not recorded in the current period. Crashes in 40 mph zones decreased from 12 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-10-01 through 2024-10-31 (31 days)
- Geographic scope: NORTH ATTLEBOROUGH, MA
- Total crash records analyzed: 49
- Total persons involved: 115
- Total vehicles involved: 96
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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/october-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: 2024-10-01 – 2024-10-31
Generated: June 21, 2026 · All rights reserved