Monthly Traffic Safety Analysis

17 CRASHES IN
ROCKLAND, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

In March 2025, Rockland recorded 17 crashes, a decrease from the 22 crashes reported in March 2024. This represents a 22.7% reduction in total crashes year-over-year. The most notable shift was an 85.7% decrease in total injuries, falling from 14 injuries in March 2024 to 2 in March 2025.

17

-22.7%was 22

Total Crash Events

0

Persons Killed

2

-85.7%was 14

Persons Injured

0

Fatal Crash Events

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 · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Rockland decreased year-over-year, with total crashes dropping by 22.7% from 22 to 17. This downward trend is also reflected in a significant 85.7% reduction in total injuries, decreasing from 14 to 2. No fatalities were recorded in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 13-84.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

While Friday remained a peak day for crashes in both periods, the number of crashes on Fridays decreased from 8 in March 2024 to 3 in March 2025. The peak hour for crashes shifted from 7 PM with 3 crashes in March 2024 to 10 AM with 3 crashes in March 2025. Monday and Thursday also saw a decrease in crashes, while Sunday saw an increase from 1 to 3 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity showed a significant decrease in injury crashes year-over-year. In March 2024, there were 1 serious injury and 8 minor injuries, totaling 14 injuries, compared to March 2025 which reported 1 minor injury and 1 possible injury, totaling 2 injuries. The proportion of crashes resulting in no injuries increased from 59.1% in March 2024 to 88.2% in March 2025.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes5.9%
-87.5%prior 8
Possible Injury1possible injury crashes5.9%
No Injury15no injury crashes88.2%
15.4%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors saw shifts, with 'Inattention' crashes increasing from 2 in March 2024 to 6 in March 2025, a 200% rise in count. 'Followed too closely' also increased from 2 crashes to 3 crashes, a 50% increase. Conversely, 'Failed to yield right of way,' which was the leading factor in March 2024 with 9 crashes, was not a reported factor in March 2025.

Officer-Reported Primary Contributing Cause

Inattention6 (35.3%)
Followed too closely3 (17.6%)
No improper driving2 (11.8%)
Fatigued/asleep2 (11.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.9%)
Illness1 (5.9%)
Made an improper turn1 (5.9%)
Failure to keep in proper lane or running off road1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 13 in March 2024 to 10 in March 2025, while crashes in 'Rain' conditions decreased from 2 to 1. The number of crashes on 'Wet' road surfaces decreased significantly from 6 in March 2024 to 2 in March 2025. Crashes occurring in 'Dark - lighted roadway' conditions also decreased from 5 to 1.

Weather

Clear10 (58.8%)
-23.1%prior 13
Clear/Cloudy4 (23.5%)
Cloudy2 (11.8%)
Rain1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight14 (82.4%)
-6.7%prior 15
Dark - roadway not lighted2 (11.8%)
Dark - lighted roadway1 (5.9%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry15 (88.2%)
-6.3%prior 16
Wet2 (11.8%)
-66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (29 vehicles)

1
TOYOTA4 (13.8%)
-50.0%prior 8
2
HONDA4 (13.8%)
-33.3%prior 6
3
NISSAN3 (10.3%)
4
CHEVROLET3 (10.3%)
-57.1%prior 7
5
FORD3 (10.3%)
6
SUBARU2 (6.9%)
7
LINC1 (3.4%)
8
RAM1 (3.4%)
9
VOLKSWAGEN1 (3.4%)
10
CADI1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (40 persons with recorded sex)

Female23 (57.5%)
15.0%prior 20
Male17 (42.5%)
-29.2%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in 25 mph zones decreased from 4 in March 2024 to 2 in March 2025. Similarly, crashes in 35 mph zones decreased from 7 to 5. The 30 mph zone maintained a consistent count of 10 crashes across both periods, and no crashes occurred in the 60 mph zone in March 2025, which had one crash in March 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: ROCKLAND, MA
  • Total crash records analyzed: 17
  • Total persons involved: 41
  • Total vehicles involved: 29

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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rockland/march-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 — March 2025 | ThatCarHitMe.com