Monthly Traffic Safety Analysis

13 CRASHES IN
MILLBURY, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

MILLBURY experienced a significant decrease in total crashes in December 2024 compared to December 2023, with crashes falling by 50% from 26 to 13. Total injuries also decreased by 37.5%, from 8 to 5. One notable shift was the substantial increase in the hit-and-run crash rate.

13

-50.0%was 26

Total Crash Events

0

Persons Killed

5

-37.5%was 8

Persons Injured

3

200.0%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

The overall trend indicates a significant decrease in crash activity year-over-year. Total crashes decreased by 50%, from 26 in December 2023 to 13 in December 2024. Similarly, total injuries decreased by 37.5%, from 8 to 5.

3

Hit-and-Run Crashes — December 2024

200.0% vs prior (1)

Hit-and-run incidents increased in December 2024 compared to the prior year. The number of hit-and-run crashes rose from 1 to 3, causing the hit-and-run rate to increase from 3.8% of all crashes in December 2023 to 23.1% in December 2024.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 8-37.5%

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 year-over-year. The peak crash day moved from Sunday with 6 crashes in December 2023 to Thursday with 3 crashes in December 2024. The peak crash hour also changed, moving from 8 PM with 4 crashes in the prior period to 1 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

There were no fatal crashes in either December 2023 or December 2024. Serious injuries decreased from 2 crashes (7.7% of total crashes) in the prior period to 1 crash (7.7%) in the current period. Minor injury crashes also saw a reduction from 3 (11.5%) to 2 (15.4%), while possible injury crashes remained at 1 in both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.7%
-50.0%prior 2
Minor Injury2minor injury crashes15.4%
-33.3%prior 3
Possible Injury1possible injury crashes7.7%
0.0%prior 1
No Injury9no injury crashes69.2%
-50.0%prior 18

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 changes year-over-year. Crashes attributed to 'Followed too closely' increased from 1 in December 2023 to 3 in December 2024. Conversely, 'No improper driving' decreased from 7 crashes to 2 crashes, and 'Inattention' decreased from 4 crashes to 2 crashes. 'Driving too fast for conditions' was a factor in 2 crashes in the current period, but was not a primary factor in the prior period's top list.

Officer-Reported Primary Contributing Cause

Followed too closely3 (23.1%)
Driving too fast for conditions2 (15.4%)
Inattention2 (15.4%)
No improper driving2 (15.4%)-71.4%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (7.7%)
Failure to keep in proper lane or running off road1 (7.7%)
Exceeded authorized speed limit1 (7.7%)

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

Changes were observed in crash conditions. Crashes on wet road surfaces decreased significantly from 8 in December 2023 to 1 in December 2024, while crashes on icy surfaces increased from 0 to 3. The proportion of crashes occurring in daylight increased from 30.8% (8 of 26 crashes) in the prior period to 69.2% (9 of 13 crashes) in the current period.

Weather

Clear/Clear8 (61.5%)
Clear3 (23.1%)
-80.0%prior 15
Cloudy1 (7.7%)
Snow/Snow1 (7.7%)

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 (69.2%)
12.5%prior 8
Dark - roadway not lighted3 (23.1%)
Dawn1 (7.7%)

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

Road Surface

Dry9 (69.2%)
-50.0%prior 18
Ice3 (23.1%)
Wet1 (7.7%)
-87.5%prior 8

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 (27 vehicles)

1
HONDA4 (14.8%)
2
FORD4 (14.8%)
-20.0%prior 5
3
TOYOTA3 (11.1%)
-66.7%prior 9
4
VOLVO2 (7.4%)
5
AUDI1 (3.7%)
6
MAZDA1 (3.7%)
7
NISSAN1 (3.7%)
8
RAM1 (3.7%)
9
TESL1 (3.7%)
10
LEXUS1 (3.7%)

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

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

Sex Distribution (27 persons with recorded sex)

Male19 (70.4%)
-40.6%prior 32
Female8 (29.6%)
-60.0%prior 20

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, with crashes at 30 mph decreasing from 8 to 1. Crashes in the 65 mph zone increased from 3 to 4, representing a higher proportion of total crashes in the current period (50%) compared to the prior period (14.3%). There were no fatal crashes in any speed zone during 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: MILLBURY, MA
  • Total crash records analyzed: 13
  • 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). "MILLBURY, 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/millbury/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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Millbury, MA Crash Report — December 2024 | ThatCarHitMe.com