Monthly Traffic Safety Analysis

30 CRASHES IN
MILLBURY, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, MILLBURY experienced 30 crashes, a 42.9% increase compared to the 21 crashes recorded in April 2021. The total number of injuries doubled year-over-year, rising from 4 in April 2021 to 8 in April 2022, representing the most significant year-over-year shift in safety outcomes.

30

42.9%was 21

Total Crash Events

0

Persons Killed

8

100.0%was 4

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in MILLBURY increased in April 2022 compared to April 2021. Total crashes rose by 9, from 21 to 30, marking a 42.9% increase. Injuries also saw a substantial increase, doubling from 4 to 8, a 100% rise year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 4100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 significantly year-over-year. In April 2021, Friday was the peak day with 10 crashes, while in April 2022, crashes were more evenly distributed, with Wednesday, Thursday, and Saturday each recording 6 crashes. The peak hour for crashes also shifted from 2 PM with 3 crashes in April 2021 to 5 PM with 7 crashes in April 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both April 2021 and April 2022. However, total injuries increased from 4 to 8, with minor injuries (B) rising from 3 to 5, and possible injuries (C) appearing with 2 cases in April 2022 compared to none in April 2021. The proportion of crashes resulting in any injury increased from 14.3% (3 of 21) in April 2021 to 23.3% (7 of 30) in April 2022.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes16.7%
66.7%prior 3
Possible Injury2possible injury crashes6.7%
No Injury22no injury crashes73.3%
46.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw changes in crash counts year-over-year. 'No improper driving' increased from 3 crashes in April 2021 to 6 crashes in April 2022, a 100% increase in count. 'Failure to keep in proper lane or running off road' rose from 1 crash to 3 crashes, a 200% increase, while 'Driving too fast for conditions' increased from 1 to 2 crashes, a 100% increase. 'Inattention' also increased by 1 crash, from 5 to 6, a 20% increase in count.

Officer-Reported Primary Contributing Cause

Inattention6 (20%)20.0%prior 5
No improper driving6 (20%)
Failure to keep in proper lane or running off road3 (10%)
Driving too fast for conditions2 (6.7%)
Followed too closely2 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.7%)
Fatigued/asleep1 (3.3%)
Made an improper turn1 (3.3%)
Failed to yield right of way1 (3.3%)
Exceeded authorized speed limit1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather remained the dominant condition for crashes, increasing from 14 crashes in April 2021 to 19 in April 2022, while cloudy conditions saw a notable rise from 1 to 6 crashes. Daylight conditions continued to account for the majority of crashes, increasing from 17 to 21 incidents. Dry road surface crashes also increased from 15 to 22, and wet road crashes rose slightly from 6 to 7.

Weather

Clear19 (65.5%)
35.7%prior 14
Cloudy6 (20.7%)
Rain3 (10.3%)
Rain/Clear1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight21 (72.4%)
23.5%prior 17
Dark - lighted roadway5 (17.2%)
Dusk2 (6.9%)
Dark - roadway not lighted1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry22 (75.9%)
46.7%prior 15
Wet7 (24.1%)
16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (51 vehicles)

1
TOYOTA11 (21.6%)
57.1%prior 7
2
FORD8 (15.7%)
3
NISSAN6 (11.8%)
4
MERCEDES-BENZ3 (5.9%)
5
SUBARU3 (5.9%)
6
ACURA2 (3.9%)
7
HONDA2 (3.9%)
8
RAM2 (3.9%)
9
VOLVO2 (3.9%)
10
LEX1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (51 persons with recorded sex)

Male31 (60.8%)
72.2%prior 18
Female20 (39.2%)
17.6%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones saw a substantial increase, rising from 6 crashes in April 2021 to 14 crashes in April 2022, a 133.3% increase. Conversely, crashes in 35 mph zones decreased from 6 to 5, and 55 mph zones decreased from 2 to 1. Notably, crashes in 50 mph zones (2 crashes) and 65 mph zones (4 crashes) were recorded in April 2022 but not in April 2021.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: MILLBURY, MA
  • Total crash records analyzed: 30
  • Total persons involved: 57
  • Total vehicles involved: 51

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: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/millbury/april-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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Millbury, MA Crash Report — April 2022 | ThatCarHitMe.com