Monthly Traffic Safety Analysis

17 CRASHES IN
LUNENBURG, MA
OCTOBER 2024

All metrics benchmarked againstOctober 2023

In October 2024, Lunenburg experienced 17 total crashes, a 30.8% increase compared to 13 crashes in October 2023. Total injuries saw a substantial rise of 300%, increasing from 2 to 8 year-over-year. This significant increase in injuries is the most notable shift between the two periods.

17

30.8%was 13

Total Crash Events

0

Persons Killed

8

300.0%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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Lunenburg indicates an upward trend year-over-year. Total crashes increased from 13 in October 2023 to 17 in October 2024, representing a 30.8% rise. Additionally, total injuries escalated from 2 to 8, marking a 300% increase during the same period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 2300.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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 in October 2023 to Friday in October 2024, both recording 4 crashes. The peak hour also changed, from 9 PM with 2 crashes in October 2023 to 11 AM with 4 crashes in October 2024. This indicates a shift in crash concentration to earlier hours of the day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both October 2023 and October 2024 recorded zero fatalities. However, total injuries increased significantly from 2 in October 2023 to 8 in October 2024. In October 2024, 2 crashes involved possible injuries, while October 2023 reported 1 serious injury crash and 1 minor injury crash.

Outcome by Severity (Crash Events)

Possible Injury2possible injury crashes11.8%
No Injury13no injury crashes76.5%
85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Followed too closely" increased from 1 in October 2023 to 3 in October 2024, a 200% increase in count. Similarly, "Inattention" crashes also rose from 1 to 3 during the same period, a 200% increase in count. The number of crashes where "No improper driving" was a factor remained constant at 3 for both years. Factors such as "Failure to keep in proper lane or running off road," "Other improper action," and "Exceeded authorized speed limit" were each associated with 1 crash in October 2023 but were not present in October 2024.

Officer-Reported Primary Contributing Cause

Followed too closely3 (17.6%)
Inattention3 (17.6%)
No improper driving3 (17.6%)
Disregarded traffic signs, signals, road markings1 (5.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.9%)
Failed to yield right of way1 (5.9%)
Over-correcting/over-steering1 (5.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 9 in October 2023 to 15 in October 2024. Similarly, incidents in 'Daylight' conditions rose from 6 to 16 year-over-year. Conversely, crashes in 'Rain' weather decreased from 3 to 0, and those in 'Dark - roadway not lighted' conditions decreased from 4 to 0. Road surface condition data was not available for October 2024.

Weather

Clear15 (88.2%)
66.7%prior 9
Cloudy2 (11.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash

Lighting

Daylight16 (94.1%)
166.7%prior 6
Dark - lighted roadway1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (27 vehicles)

1
HYUNDAI4 (14.8%)
2
HONDA4 (14.8%)
3
NISSAN3 (11.1%)
4
TOYOTA2 (7.4%)
5
PTRB2 (7.4%)
6
KIA2 (7.4%)
7
RAM2 (7.4%)
8
SUBARU1 (3.7%)
9
MACK1 (3.7%)
10
FORD1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records

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

Sex Distribution (33 persons with recorded sex)

Male20 (60.6%)
42.9%prior 14
Female13 (39.4%)
225.0%prior 4

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in 30 mph zones remained stable at 6 in both October 2023 and October 2024. Crashes in 40 mph zones saw a decrease, falling from 7 in October 2023 to 3 in October 2024. October 2024 data also shows crashes occurring in 10, 15, 25, 35, and 45 mph zones, which were not recorded in October 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-10-01 through 2024-10-31 (31 days)
  • Geographic scope: LUNENBURG, MA
  • Total crash records analyzed: 17
  • Total persons involved: 35
  • Total vehicles involved: 27

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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lunenburg/october-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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Lunenburg, MA Crash Report — October 2024 | ThatCarHitMe.com