Monthly Traffic Safety Analysis

24 CRASHES IN
LAKEVILLE, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, Lakeville experienced 24 total crashes, marking a 14.29% increase from the 21 crashes reported in December 2023. Total injuries saw a more significant rise, increasing by 55.56% from 9 to 14. The most notable shift was the increase in crashes occurring in dark conditions, which doubled from 6 to 12 year-over-year.

24

14.3%was 21

Total Crash Events

0

Persons Killed

14

55.6%was 9

Persons Injured

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Lakeville showed an upward trend year-over-year, with total crashes increasing by 3, from 21 in December 2023 to 24 in December 2024. This represents a 14.29% rise in crash incidents. Injuries also increased, with 14 injuries reported in December 2024 compared to 9 in the prior year.

1

Hit-and-Run Crashes — December 2024

4.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

14

Motorists Injured

Prior: 955.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 notably year-over-year. The peak day for crashes moved from Thursday with 5 crashes in December 2023 to Wednesday with 7 crashes in December 2024. Additionally, the peak crash hour shifted from 7 AM with 4 crashes in the prior period to 5 PM with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes changed, with an increase in higher-severity injuries. Serious injuries (Severity A) rose from 0 in December 2023 to 1 in December 2024, and Possible injuries (Severity C) increased from 0 to 2. Minor injuries (Severity B) saw a slight decrease, from 9 in the prior year to 8 in the current year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.2%
Minor Injury8minor injury crashes33.3%
-11.1%prior 9
Possible Injury2possible injury crashes8.3%
No Injury13no injury crashes54.2%
8.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw shifts in crash counts. 'No improper driving' decreased by 4 crashes, from 10 in December 2023 to 6 in December 2024. Crashes attributed to 'Driving too fast for conditions' increased by 2, from 1 to 3, while 'Failed to yield right of way' decreased by 1 crash, from 3 to 2. Factors such as 'Inattention,' 'Physical impairment,' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' remained stable with the same number of crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving6 (25%)-40.0%prior 10
Failure to keep in proper lane or running off road4 (16.7%)
Inattention3 (12.5%)
Driving too fast for conditions3 (12.5%)
Failed to yield right of way2 (8.3%)
Exceeded authorized speed limit1 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.2%)
Physical impairment1 (4.2%)
Disregarded traffic signs, signals, road markings1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Adverse conditions played a larger role in crashes in December 2024 compared to the prior year. Crashes occurring in dark conditions more than doubled, increasing from 6 to 12. Similarly, crashes on wet, icy, or snowy road surfaces rose from 6 to 10. While crashes in daylight decreased from 14 to 9, clear weather conditions remained the most common factor, accounting for 13 crashes in December 2024 versus 12 in December 2023.

Weather

Clear/Clear7 (29.2%)
40.0%prior 5
Clear6 (25.0%)
-14.3%prior 7
Snow2 (8.3%)
Cloudy/Cloudy2 (8.3%)
Rain/Fog, smog, smoke2 (8.3%)
Rain/Severe crosswinds2 (8.3%)
Clear/Cloudy1 (4.2%)
Cloudy/Rain1 (4.2%)
Rain1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight9 (37.5%)
-35.7%prior 14
Dark - roadway not lighted6 (25.0%)
Dark - lighted roadway5 (20.8%)
Dusk2 (8.3%)
Dark - unknown roadway lighting1 (4.2%)
Dawn1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry14 (58.3%)
-6.7%prior 15
Wet8 (33.3%)
33.3%prior 6
Ice1 (4.2%)
Snow1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (40 vehicles)

1
FORD7 (17.5%)
2
TOYOTA4 (10%)
3
NISSAN3 (7.5%)
4
JEEP3 (7.5%)
5
BUIC2 (5%)
6
KIA2 (5%)
7
CHEVROLET2 (5%)
8
GMC2 (5%)
9
MITS1 (2.5%)
10
PONT1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (47 persons with recorded sex)

Female25 (53.2%)
127.3%prior 11
Male22 (46.8%)
-15.4%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes shifted to different speed zones year-over-year, with an increase in crashes in both 35 mph and 45 mph zones. Crashes at 35 mph increased by 2, from 4 to 6, and crashes at 45 mph increased by 3, from 4 to 7. Conversely, crashes in 40 mph zones decreased by 3, from 8 to 5. There were no fatal crashes reported in any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: LAKEVILLE, MA
  • Total crash records analyzed: 24
  • Total persons involved: 50
  • 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). "LAKEVILLE, MA Crash Intelligence Report: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lakeville/december-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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Lakeville, MA Crash Report — December 2024 | ThatCarHitMe.com