Monthly Traffic Safety Analysis

24 CRASHES IN
WESTMINSTER, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, WESTMINSTER experienced 24 crashes, a substantial increase compared to the 5 crashes recorded in December 2023. This represents a 380% rise in total crashes year-over-year. The most notable shift is the significant increase in both total crashes and total injuries, which rose from 0 to 8.

24

380.0%was 5

Total Crash Events

0

Persons Killed

8

Persons Injured

0

-100.0%was 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, crash activity in WESTMINSTER shows a significant upward trend year-over-year. Total crashes increased from 5 in December 2023 to 24 in December 2024, marking a 380% increase. Concurrently, total injuries rose from 0 to 8, while total fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 0%

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 distribution of crashes shifted year-over-year. In December 2023, Monday was the peak day with 2 crashes, and 10 AM was the peak hour with 2 crashes. In December 2024, crashes were more frequent, with Friday, Tuesday, and Thursday each recording 5 crashes, and 8 AM becoming the peak hour with 4 crashes.

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

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes25%
No Injury18no injury crashes75%

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

The contributing factors for crashes showed a distinct change year-over-year. In December 2023, 'Driving too fast for conditions' was the most cited factor with 2 crashes, followed by 'Exceeded authorized speed limit' with 1 crash. In December 2024, 'No improper driving' was the dominant factor, contributing to 11 crashes, and new factors like 'Inattention' (2 crashes) and 'Failure to keep in proper lane or running off road' (1 crash) emerged among the top causes.

Officer-Reported Primary Contributing Cause

No improper driving11 (45.8%)
Inattention2 (8.3%)
Failure to keep in proper lane or running off road1 (4.2%)
Fatigued/asleep1 (4.2%)
Physical impairment1 (4.2%)
Visibility obstructed1 (4.2%)
Disregarded traffic signs, signals, road markings1 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (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 more prominent role in crashes during December 2024 compared to the prior year. While 'Daylight' remained the most common lighting condition, crashes in 'Dark - roadway not lighted' increased from 2 to 6. Road surface conditions shifted significantly, with crashes on 'Snow' (7 crashes) and 'Ice' (3 crashes) being reported in December 2024, compared to 0 snow crashes and 1 ice crash in December 2023.

Weather

Clear10 (41.7%)
Snow4 (16.7%)
Sleet, hail (freezing rain or drizzle)2 (8.3%)
Snow/Blowing sand, snow2 (8.3%)
Rain/Cloudy1 (4.2%)
Rain/Sleet, hail (freezing rain or drizzle)1 (4.2%)
Snow/Cloudy1 (4.2%)
Cloudy1 (4.2%)
Cloudy/Rain1 (4.2%)
Cloudy/Snow1 (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

Daylight13 (54.2%)
Dark - roadway not lighted6 (25.0%)
Dark - lighted roadway4 (16.7%)
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

Dry9 (37.5%)
Snow7 (29.2%)
Wet4 (16.7%)
Ice3 (12.5%)
Slush1 (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 (31 vehicles)

1
TOYOTA6 (19.4%)
2
SUBARU5 (16.1%)
3
HONDA4 (12.9%)
4
FORD2 (6.5%)
5
CHEVROLET2 (6.5%)
6
KIA1 (3.2%)
7
LNDR1 (3.2%)
8
MERCEDES-BENZ1 (3.2%)
9
NISSAN1 (3.2%)
10
RAM1 (3.2%)

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

Sex Distribution (47 persons with recorded sex)

Male25 (53.2%)
Female22 (46.8%)

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

The distribution of crashes across speed zones shifted notably year-over-year. In December 2023, all 5 crashes occurred in higher speed zones (4 crashes at 55 mph and 1 crash at 65 mph). In December 2024, crashes were predominantly in lower speed zones, with 8 crashes at 30 mph and 7 crashes at 35 mph, and only 2 crashes at 55 mph. Fatalities remained at 0 across all speed zones in both periods.

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: WESTMINSTER, MA
  • Total crash records analyzed: 24
  • Total persons involved: 47
  • Total vehicles involved: 31

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). "WESTMINSTER, 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/westminster/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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Westminster, MA Crash Report — December 2024 | ThatCarHitMe.com