Monthly Traffic Safety Analysis

29 CRASHES IN
LUNENBURG, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, Lunenburg experienced 29 crashes, a substantial increase compared to the 11 crashes reported in February 2024. This represents a 163.6% rise in total crashes year-over-year. Despite the increase in crash volume, total injuries decreased from 2 in the prior period to 1 in the current period.

29

163.6%was 11

Total Crash Events

0

Persons Killed

1

-50.0%was 2

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash activity in Lunenburg, with total crashes rising from 11 in February 2024 to 29 in February 2025. This represents a 163.6% increase in the number of crashes year-over-year. Despite this rise in crashes, the total number of injuries decreased from 2 to 1 during the same period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 2-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Saturday, which had 3 crashes in February 2024, to Tuesday, which recorded 7 crashes in February 2025. Similarly, the peak crash hour shifted from 6 p.m. with 3 crashes in the prior period to 2 p.m. with 5 crashes in the current period. The current period also saw a broader distribution of crashes across weekdays, including 6 crashes on Sunday and 6 on Monday, compared to 1 crash on Sunday and 0 on Monday in the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both February 2024 and February 2025, indicating no change in the fatal crash rate. However, total injuries decreased from 2 in the prior period to 1 in the current period. The proportion of crashes resulting in any injury decreased from 18.2% in February 2024 to 3.4% in February 2025.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes3.4%
0.0%prior 1
No Injury25no injury crashes86.2%
177.8%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to 'No improper driving' increased from 6 in February 2024 to 9 in February 2025. Crashes involving 'Failed to yield right of way' also saw an increase, rising from 1 in the prior period to 4 in the current period. 'Inattention' remained a factor in 2 crashes in both periods, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' was cited in 2 crashes in the prior period but none in the current period.

Officer-Reported Primary Contributing Cause

No improper driving9 (31%)50.0%prior 6
Failed to yield right of way4 (13.8%)
Failure to keep in proper lane or running off road3 (10.3%)
Inattention2 (6.9%)
Made an improper turn2 (6.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (6.9%)
Followed too closely1 (3.4%)
Other improper action1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 9 in February 2024 to 17 in February 2025. Notably, snow-related weather conditions, including 'Snow' and 'Snow/Sleet, hail', accounted for 10 crashes in the current period, compared to none in the prior period. Regarding lighting, crashes during daylight hours rose from 5 to 15, while crashes in 'Dark - lighted roadway' conditions increased from 3 to 7, and 'Dark - roadway not lighted' crashes increased from 2 to 5.

Weather

Clear17 (60.7%)
88.9%prior 9
Snow5 (17.9%)
Snow/Sleet, hail (freezing rain or drizzle)2 (7.1%)
Clear/Other1 (3.6%)
Sleet, hail (freezing rain or drizzle)1 (3.6%)
Clear/Blowing sand, snow1 (3.6%)
Snow/Snow1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight15 (53.6%)
200.0%prior 5
Dark - lighted roadway7 (25.0%)
Dark - roadway not lighted5 (17.9%)
Dark - unknown roadway lighting1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry16 (55.2%)
Snow6 (20.7%)
Ice3 (10.3%)
Slush2 (6.9%)
Wet2 (6.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (46 vehicles)

1
TOYOTA11 (23.9%)
2
SUBARU5 (10.9%)
3
NISSAN5 (10.9%)
4
HONDA5 (10.9%)
5
BMW4 (8.7%)
6
FORD4 (8.7%)
7
HYUNDAI3 (6.5%)
8
KIA3 (6.5%)
9
MITS2 (4.3%)
10
JEEP1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (49 persons with recorded sex)

Male33 (67.3%)
450.0%prior 6
Female16 (32.7%)
33.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones doubled from 6 in February 2024 to 12 in February 2025. Crashes in 35 mph zones increased from 2 to 5, and crashes in 40 mph zones also rose from 2 to 5 during the same period. The current period also saw crashes in 5 mph (2 crashes), 10 mph (1 crash), and 45 mph (3 crashes) speed zones, which were not present in the prior period's data. Fatalities remained at zero across all reported speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: LUNENBURG, MA
  • Total crash records analyzed: 29
  • Total persons involved: 51
  • Total vehicles involved: 46

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). "LUNENBURG, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lunenburg/february-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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Lunenburg, MA Crash Report — February 2025 | ThatCarHitMe.com