Monthly Traffic Safety Analysis

23 CRASHES IN
LAKEVILLE, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

In December 2022, Lakeville experienced 23 crashes, marking a 35.3% increase compared to the 17 crashes recorded in December 2021. Total injuries also rose significantly, from 7 in December 2021 to 11 in December 2022, representing a 57.1% increase. A notable shift includes the increase in crashes occurring in clear weather conditions, from 9 in the prior year to 18 in the current year.

23

35.3%was 17

Total Crash Events

0

Persons Killed

11

57.1%was 7

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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Lakeville showed an upward trend year-over-year. The total number of crashes increased from 17 in December 2021 to 23 in December 2022, an increase of 35.3%. Concurrently, total injuries rose from 7 to 11, indicating a 57.1% increase, while fatalities remained stable at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 757.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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 between the two periods. In December 2021, the peak day for crashes was Thursday with 4 incidents, while in December 2022, it shifted to Friday with 5 incidents. Similarly, the peak hour for crashes moved from 2 PM with 4 incidents in the prior year to 5 PM with 5 incidents in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity saw some changes, though fatal crashes remained at zero in both periods. Serious injury crashes (severity A) remained constant at 1 crash in both December 2021 and December 2022. Minor injury crashes (severity B) increased from 2 crashes in the prior period to 3 crashes in the current period, while overall injuries (totalInjuries) increased from 7 to 11.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.3%
0.0%prior 1
Minor Injury3minor injury crashes13%
50.0%prior 2
No Injury19no injury crashes82.6%
46.2%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes in crash counts year-over-year. 'No improper driving' increased from 5 crashes in December 2021 to 9 crashes in December 2022, an 80% increase in count. 'Inattention' also rose from 3 crashes to 4 crashes, a 33.3% increase in count. Factors such as 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner', 'Fatigued/asleep', and 'Followed too closely' all doubled in count, from 1 crash each in the prior period to 2 crashes each in the current period.

Officer-Reported Primary Contributing Cause

No improper driving9 (39.1%)80.0%prior 5
Inattention4 (17.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8.7%)
Fatigued/asleep2 (8.7%)
Followed too closely2 (8.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.3%)
Failed to yield right of way1 (4.3%)
Other improper action1 (4.3%)
Driving too fast for conditions1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions significantly increased from 9 in December 2021 to 18 in December 2022, while crashes in rainy conditions decreased from 5 to 3. The number of crashes on dry road surfaces increased from 11 to 18, whereas crashes on wet surfaces decreased from 6 to 4. Notably, crashes occurring in 'Dark - roadway not lighted' conditions saw a substantial increase from 3 in the prior period to 8 in the current period.

Weather

Clear10 (43.5%)
42.9%prior 7
Clear/Clear8 (34.8%)
Rain2 (8.7%)
Cloudy/Cloudy1 (4.3%)
Rain/Severe crosswinds1 (4.3%)
Snow/Blowing sand, snow1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted8 (34.8%)
Daylight8 (34.8%)
14.3%prior 7
Dark - lighted roadway4 (17.4%)
-20.0%prior 5
Dark - unknown roadway lighting1 (4.3%)
Dawn1 (4.3%)
Dusk1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry18 (78.3%)
63.6%prior 11
Wet4 (17.4%)
-33.3%prior 6
Snow1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
TOYOTA8 (22.2%)
60.0%prior 5
2
HONDA6 (16.7%)
3
FORD4 (11.1%)
4
JEEP2 (5.6%)
5
KIA2 (5.6%)
6
CHEVROLET2 (5.6%)
7
LNDR2 (5.6%)
8
AUDI2 (5.6%)
9
VOLKSWAGEN2 (5.6%)
10
VOLVO1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records

Sex Distribution (44 persons with recorded sex)

Male23 (52.3%)
4.5%prior 22
Female21 (47.7%)
162.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 40 mph speed zone experienced a significant increase, rising from 3 crashes in December 2021 to 9 crashes in December 2022. Conversely, crashes in the 45 mph speed zone decreased from 6 to 3 during the same period. Additionally, the current period reported 2 crashes in the 30 mph zone and 2 crashes in the 65 mph zone, which had no reported crashes in the prior period's data, while fatal rates remained at zero across all speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: LAKEVILLE, MA
  • Total crash records analyzed: 23
  • Total persons involved: 52
  • Total vehicles involved: 36

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 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lakeville/december-2022-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 2022 | ThatCarHitMe.com