Yearly Traffic Safety Analysis

1,015 CRASHES IN
ATTLEBORO, MA
2025

All metrics benchmarked against2024

In 2025, Attleboro recorded 1,015 total traffic crashes, a 6.1% decrease from the 1,081 crashes in 2024. While total crashes and injuries declined, the number of fatal crashes remained stable at one. The most notable shift was a 28.3% decrease in hit-and-run crashes, which fell from 60 in the prior year to 43 in the current year.

1,015

-6.1%was 1,081

Total Crash Events

1

Persons Killed

368

-7.1%was 396

Persons Injured

43

-28.3%was 60

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic safety trends in Attleboro showed improvement year-over-year. Total crashes decreased by 6.1%, from 1,081 to 1,015, and total injuries fell by 7.1% from 396 to 368. The number of fatalities, however, remained unchanged with one person killed in a crash in both 2024 and 2025.

43

Hit-and-Run Crashes — 2025

-28.3% vs prior (60)

Hit-and-run incidents saw a notable decrease year-over-year. The total count of hit-and-run crashes fell by 28.3%, from 60 in 2024 to 43 in 2025. The hit-and-run rate, as a percentage of all crashes, also trended down, decreasing from 5.6% to 4.2%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

8

Pedestrians Injured

Prior: 633.3%

5

Cyclists Injured

Prior: 50.0%

351

Motorists Injured

Prior: 383-8.4%

4

Other Injured

Prior: 2100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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. The peak day for crashes moved from Friday and Saturday (166 crashes each) in 2024 to Monday (173 crashes) in 2025. The peak hour for collisions remained consistent, occurring at 3 p.m. in both years, with a slight increase in crashes during that hour from 99 to 104.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of fatal crashes was unchanged at one, the fatal crash rate increased slightly from 0.09% to 0.10% due to the lower overall crash volume. The count of serious injury crashes rose from 17 to 21, an increase of 23.5%, and their share of total crashes grew from 1.6% to 2.1%. Crashes resulting in minor or possible injuries saw a decrease in total count but remained proportionally similar to the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
0.0%prior 1
Serious Injury21serious injury crashes2.1%
23.5%prior 17
Minor Injury158minor injury crashes15.6%
-5.4%prior 167
Possible Injury103possible injury crashes10.1%
-7.2%prior 111
No Injury729no injury crashes71.8%
-5.9%prior 775

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The top two contributing factors remained 'Failed to yield right of way' and 'Followed too closely' in both periods, with the count for each increasing by 6.4% and 7.1% respectively. The factor of 'Inattention' saw a significant 22.1% decrease in count, falling from 136 incidents to 106 and dropping from the 3rd to the 4th most common factor. 'Failure to keep in proper lane' moved into the top three despite its count decreasing from 120 to 111.

Officer-Reported Primary Contributing Cause

Failed to yield right of way249 (24.5%)6.4%prior 234
Followed too closely181 (17.8%)7.1%prior 169
Failure to keep in proper lane or running off road111 (10.9%)-7.5%prior 120
Inattention106 (10.4%)-22.1%prior 136
No improper driving86 (8.5%)13.2%prior 76
Disregarded traffic signs, signals, road markings58 (5.7%)16.0%prior 50
Driving too fast for conditions38 (3.7%)-17.4%prior 46
Other improper action24 (2.4%)-29.4%prior 34
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner22 (2.2%)-18.5%prior 27
Distracted18 (1.8%)-52.6%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Year-over-year, a slightly larger proportion of crashes occurred in clear and dry conditions. Crashes in daylight increased from 68.5% to 71.6% of the total, and crashes on dry road surfaces increased from 78.1% to 81.3%. Correspondingly, the proportion of crashes occurring on wet roads decreased from 16.4% to 14.9% of all incidents.

Weather

Clear/Clear548 (54.0%)
24.0%prior 442
Clear223 (22.0%)
-37.0%prior 354
Rain/Rain49 (4.8%)
36.1%prior 36
Cloudy/Cloudy44 (4.3%)
22.2%prior 36
Cloudy27 (2.7%)
-46.0%prior 50
Rain26 (2.6%)
-52.7%prior 55
Cloudy/Rain23 (2.3%)
9.5%prior 21
Rain/Cloudy21 (2.1%)
10.5%prior 19
Snow/Snow16 (1.6%)
60.0%prior 10
Snow7 (0.7%)
-63.2%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight727 (71.6%)
-1.8%prior 740
Dark - lighted roadway176 (17.3%)
-21.8%prior 225
Dark - roadway not lighted62 (6.1%)
-4.6%prior 65
Dusk26 (2.6%)
-16.1%prior 31
Dawn22 (2.2%)
22.2%prior 18
Dark - unknown roadway lighting2 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry825 (81.4%)
-2.3%prior 844
Wet151 (14.9%)
-14.7%prior 177
Snow22 (2.2%)
-18.5%prior 27
Slush7 (0.7%)
-22.2%prior 9
Ice5 (0.5%)
-66.7%prior 15
Other2 (0.2%)
Sand, mud, dirt, oil, gravel1 (0.1%)
Water (standing, moving)1 (0.1%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes—Toyota, Honda, Ford, Chevrolet, and Nissan—remained the same across both years, though their individual counts all decreased in 2025. The age distribution of persons involved in crashes also showed a consistent pattern, with the 26-34 age group being the most frequently involved in both periods, accounting for 400 people in 2025 compared to 430 in 2024.

Top Vehicle Makes (1,902 vehicles)

1
TOYOTA339 (17.8%)
-2.9%prior 349
2
HONDA219 (11.5%)
-8.8%prior 240
3
FORD167 (8.8%)
-5.6%prior 177
4
NISSAN133 (7%)
-5.7%prior 141
5
CHEVROLET125 (6.6%)
-13.8%prior 145
6
HYUNDAI115 (6%)
22.3%prior 94
7
SUBARU84 (4.4%)
6.3%prior 79
8
JEEP77 (4%)
-23.8%prior 101
9
KIA51 (2.7%)
-29.2%prior 72
10
GMC47 (2.5%)
9.3%prior 43

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (2,389 persons with recorded sex)

Male1,369 (57.3%)
-0.7%prior 1,378
Female1,019 (42.7%)
1.8%prior 1,001
X / Unspecified1 (0.0%)
-50.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The speed zone where the year's single fatal crash occurred shifted from a 30 mph zone in 2024 to a 65 mph zone in 2025. Overall, crashes in 30 mph zones decreased from 400 to 349, and collisions in 65 mph zones fell from 181 to 156. Conversely, the number of crashes in 40 mph zones saw a slight increase from 153 to 159.

Fatal crashes by zone: 65 mph: 1 of 156 (0.641%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: ATTLEBORO, MA
  • Total crash records analyzed: 1,015
  • Total persons involved: 2,519
  • Total vehicles involved: 1,902

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/attleboro/2025-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

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Attleboro, MA Crash Report — 2025 | ThatCarHitMe.com