Monthly Traffic Safety Analysis

21 CRASHES IN
ROCKLAND, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, Rockland experienced 21 crashes, a 12.5% decrease compared to the 24 crashes recorded in May 2024. Despite the reduction in total crashes, the number of injuries rose significantly from 8 in May 2024 to 13 in May 2025, representing a 62.5% increase year-over-year.

21

-12.5%was 24

Total Crash Events

0

Persons Killed

13

62.5%was 8

Persons Injured

0

-100.0%was 1

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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Rockland decreased by 12.5% from 24 in May 2024 to 21 in May 2025. However, total injuries increased by 62.5%, rising from 8 in May 2024 to 13 in May 2025. Fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 862.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 significantly year-over-year. The peak day for crashes moved from Thursday with 7 crashes in May 2024 to Friday with 6 crashes in May 2025. The peak hour also shifted from 8 PM with 5 crashes in May 2024 to 6 PM with 3 crashes in May 2025. Notably, crashes on Thursdays decreased from 7 to 3, while crashes on Fridays increased from 2 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either May 2024 or May 2025. However, the total number of injuries increased by 62.5%, from 8 in May 2024 to 13 in May 2025. The proportion of crashes resulting in 'No Injury' decreased from 75% to 61.9% year-over-year, while crashes with 'Possible Injury' rose from 1 (4.2% share) to 4 (19% share).

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes14.3%
-25.0%prior 4
Possible Injury4possible injury crashes19%
300.0%prior 1
No Injury13no injury crashes61.9%
-27.8%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors saw shifts year-over-year. Crashes attributed to 'Failed to yield right of way' increased from 3 in May 2024 to 5 in May 2025, a 66.7% increase in count. Conversely, crashes with 'No improper driving' decreased by 40% in count, from 5 to 3. Additionally, 'Driving too fast for conditions' emerged as a factor, accounting for 2 crashes in May 2025 compared to 0 in May 2024.

Officer-Reported Primary Contributing Cause

Failed to yield right of way5 (23.8%)
No improper driving3 (14.3%)-40.0%prior 5
Followed too closely3 (14.3%)
Inattention2 (9.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (9.5%)
Driving too fast for conditions2 (9.5%)
Visibility obstructed1 (4.8%)
Other improper action1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 15 in May 2024 to 10 in May 2025, while crashes in 'Rain' or 'Rain-related' conditions increased from 3 to 5. The number of crashes occurring in 'Daylight' remained constant at 17 in both periods. Crashes on 'Wet' road surfaces increased from 4 in May 2024 to 6 in May 2025, while those on 'Dry' surfaces decreased from 20 to 15.

Weather

Clear10 (47.6%)
-33.3%prior 15
Cloudy5 (23.8%)
Rain3 (14.3%)
Clear/Clear1 (4.8%)
Cloudy/Rain1 (4.8%)
Rain/Cloudy1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight17 (81.0%)
0.0%prior 17
Dark - lighted roadway4 (19.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry15 (71.4%)
-25.0%prior 20
Wet6 (28.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (40 vehicles)

1
TOYOTA9 (22.5%)
2
FORD6 (15%)
3
HONDA5 (12.5%)
-50.0%prior 10
4
CHEVROLET3 (7.5%)
5
NISSAN3 (7.5%)
6
BUIC2 (5%)
7
HYUNDAI2 (5%)
8
JEEP2 (5%)
9
MAZDA2 (5%)
10
DODGE1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (48 persons with recorded sex)

Male28 (58.3%)
-6.7%prior 30
Female20 (41.7%)
-20.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed zone during either period. Crashes in 30 mph zones significantly decreased from 10 in May 2024 to 4 in May 2025. Conversely, crashes in 35 mph zones increased from 6 to 8, and crashes in 25 mph zones increased from 1 to 2. Additionally, 2 crashes occurred in 10 mph zones in May 2025, a speed zone not reported in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: ROCKLAND, MA
  • Total crash records analyzed: 21
  • Total persons involved: 52
  • Total vehicles involved: 40

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). "ROCKLAND, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rockland/may-2025-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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Rockland, MA Crash Report — May 2025 | ThatCarHitMe.com