Monthly Traffic Safety Analysis

70 CRASHES IN
ATTLEBORO, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

ATTLEBORO experienced a 5.41% decrease in total crashes, from 74 in February 2023 to 70 in February 2024. While overall injuries saw a minor reduction from 20 to 19, serious injuries specifically increased by 200%, from 1 to 3, during this period.

70

-5.4%was 74

Total Crash Events

0

Persons Killed

19

-5.0%was 20

Persons Injured

5

-16.7%was 6

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 · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in ATTLEBORO decreased by 5.41% year-over-year, with 70 crashes reported in February 2024 compared to 74 in February 2023. Total fatalities remained at 0 for both periods, and total injuries saw a slight decrease from 20 to 19.

5

Hit-and-Run Crashes — February 2024

-16.7% vs prior (6)

Hit-and-run crashes decreased from 6 incidents in February 2023 to 5 incidents in February 2024. The hit-and-run rate also saw a slight decrease, moving from 8.1% in February 2023 to 7.1% in February 2024.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

18

Motorists Injured

Prior: 20-10.0%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 16 incidents in February 2023 to Friday with 15 incidents in February 2024. Similarly, the peak hour for crashes changed from 12 AM with 15 incidents in February 2023 to 12 PM with 9 incidents in February 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both February 2023 and February 2024. However, serious injuries (Severity A) increased by 200%, from 1 in February 2023 to 3 in February 2024. Minor injuries (Severity B) decreased from 9 to 5, while possible injuries (Severity C) slightly rose from 6 to 7.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes4.3%
200.0%prior 1
Minor Injury5minor injury crashes7.1%
-44.4%prior 9
Possible Injury7possible injury crashes10%
16.7%prior 6
No Injury55no injury crashes78.6%
-5.2%prior 58

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' crashes increased significantly by 200%, rising from 5 incidents in February 2023 to 15 in February 2024. Conversely, crashes attributed to 'Failed to yield right of way' decreased from 19 to 15, and 'No improper driving' decreased from 13 to 6. 'Followed too closely' remained constant with 10 crashes in both periods.

Officer-Reported Primary Contributing Cause

Failed to yield right of way15 (21.4%)-21.1%prior 19
Inattention15 (21.4%)200.0%prior 5
Followed too closely10 (14.3%)0.0%prior 10
No improper driving6 (8.6%)-53.8%prior 13
Failure to keep in proper lane or running off road5 (7.1%)-16.7%prior 6
Driving too fast for conditions3 (4.3%)
Disregarded traffic signs, signals, road markings2 (2.9%)
Distracted2 (2.9%)
Illness1 (1.4%)
Made an improper turn1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 46 in February 2023 to 42 in February 2024. For road surface, crashes on 'Wet' roads decreased from 7 to 3, while crashes on 'Snow' increased from 5 to 6. Crashes in 'Clear/Clear' weather decreased from 34 to 31.

Weather

Clear/Clear31 (44.3%)
-8.8%prior 34
Clear27 (38.6%)
-3.6%prior 28
Snow/Snow3 (4.3%)
Cloudy3 (4.3%)
Cloudy/Rain2 (2.9%)
Rain1 (1.4%)
Snow1 (1.4%)
Snow/Cloudy1 (1.4%)
Clear/Cloudy1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight42 (60.0%)
-8.7%prior 46
Dark - lighted roadway15 (21.4%)
-11.8%prior 17
Dark - roadway not lighted6 (8.6%)
0.0%prior 6
Dusk4 (5.7%)
Dawn3 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry59 (84.3%)
-1.7%prior 60
Snow6 (8.6%)
20.0%prior 5
Wet3 (4.3%)
-57.1%prior 7
Ice1 (1.4%)
Sand, mud, dirt, oil, gravel1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The number of persons aged '0-15' involved in crashes decreased substantially from 11 in February 2023 to 1 in February 2024. The '21-25' age group saw an increase from 19 to 26 persons involved. Among vehicle makes, crashes involving 'Ford' vehicles decreased from 17 to 12, while 'Nissan' crashes increased from 8 to 12, and 'Chevrolet' crashes increased from 6 to 11.

Top Vehicle Makes (132 vehicles)

1
TOYOTA23 (17.4%)
4.5%prior 22
2
HONDA13 (9.8%)
-18.8%prior 16
3
FORD12 (9.1%)
-29.4%prior 17
4
NISSAN12 (9.1%)
50.0%prior 8
5
CHEVROLET11 (8.3%)
83.3%prior 6
6
JEEP9 (6.8%)
50.0%prior 6
7
SUBARU8 (6.1%)
0.0%prior 8
8
HYUNDAI7 (5.3%)
16.7%prior 6
9
KIA6 (4.5%)
10
DODGE3 (2.3%)
-40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

3 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (135 persons with recorded sex)

Male73 (54.1%)
-22.3%prior 94
Female62 (45.9%)
-3.1%prior 64

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 MPH speed zones decreased from 33 in February 2023 to 23 in February 2024. Conversely, crashes in 35 MPH speed zones increased from 4 to 13. Fatal crashes remained at 0 across all speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: ATTLEBORO, MA
  • Total crash records analyzed: 70
  • Total persons involved: 146
  • Total vehicles involved: 132

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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/attleboro/february-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

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Attleboro, MA Crash Report — February 2024 | ThatCarHitMe.com