ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ATTLEBOROUGH, MA · 2023
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.
Yearly Traffic Safety Analysis
499 CRASHES IN
NORTH ATTLEBOROUGH, MA
2023
In 2023, North Attleborough recorded 499 total traffic crashes, a 3.9% decrease from the 519 crashes reported in 2022. While overall crashes and injuries declined, the most significant change was the increase in fatalities, which rose from zero in the prior year to three in the current period.
499
▼ -3.9%was 519
Total Crash Events
3
Persons Killed
156
▼ -18.3%was 191
Persons Injured
36
▼ -20.0%was 45
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 11 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic collisions shows a modest decline year-over-year. Total crashes decreased by 3.9% from 519 in 2022 to 499 in 2023, and the number of people injured fell by 18.3% from 191 to 156. However, this downward trend in crashes and injuries was contrasted by an increase in fatalities from zero to three.
36
Hit-and-Run Crashes — 2023
▼ -20.0% vs prior (45)
Hit-and-run incidents decreased in both count and as a percentage of total crashes. The number of hit-and-run crashes fell from 45 in 2022 to 36 in 2023. This represents a downward trend in the hit-and-run rate, which declined from 8.7% of all crashes in the prior year to 7.2% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
154
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In 2023, the peak day for crashes was Wednesday with 85 incidents, a change from 2022 when Friday was the peak day with 94 incidents. The peak hour for crashes also shifted slightly later, from the 4 p.m. hour in 2022 (46 crashes) to the 5 p.m. hour in 2023 (49 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
In 2023, crash severity increased at the highest level, with 3 fatal crashes (0.6% of all crashes) compared to zero in 2022. Conversely, the number of crashes resulting in serious injuries decreased from 9 in the prior year to 3 in the current year. The overall proportion of crashes involving any type of injury (fatal, serious, minor, or possible) decreased from 27.7% in 2022 to 23.8% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors shifted between 2022 and 2023. "Followed too closely" became the leading factor in 2023, with its count increasing by 23.9% from 67 to 83 crashes. "Failed to yield right of way" also saw a 23.0% increase in count from 61 to 75 incidents, moving it from third to second place. Conversely, crashes attributed to "Inattention" decreased by 25.6%, falling from 90 incidents in 2022 to 67 in 2023, and dropping from the top-ranked factor to the third.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions under which crashes occurred remained largely consistent year-over-year. In both 2022 and 2023, the vast majority of crashes happened in daylight (66.3% and 67.3%, respectively) and on dry roads (78.6% and 77.0%). Crashes during clear weather conditions also accounted for a similar share in both periods, at 71.3% in 2022 and 69.0% in 2023. There was a slight increase in the proportion of crashes occurring on wet roads, rising from 16.8% of crashes in 2022 to 19.6% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford being the most common in both years, though Ford and Honda swapped second and third positions. Analysis of person age distribution shows the 35-44 age group was the most represented in both periods, with 209 individuals in 2022 and 214 in 2023. A notable shift occurred in the 16-20 age group, which saw its involvement increase from 121 persons in 2022 to 147 in 2023, while the 65+ age group's involvement decreased from 149 to 130 persons.
Top Vehicle Makes (924 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
64 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,090 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
While 2022 had no fatal crashes in any speed zone, 2023 saw three fatalities occur in higher speed zones: one in a 40 mph zone and two in a 65 mph zone. The distribution of crashes across speed zones also shifted, with crashes in 30 mph zones increasing from 119 to 139 incidents. Conversely, crashes in 40 mph zones decreased from 146 in 2022 to 132 in 2023.
Fatal crashes by zone: 40 mph: 1 of 132 (0.758%) · 65 mph: 2 of 98 (2.041%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: NORTH ATTLEBOROUGH, MA
- Total crash records analyzed: 499
- Total persons involved: 1,197
- Total vehicles involved: 924
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-attleborough/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved