Yearly Traffic Safety Analysis

322 CRASHES IN
MILLBURY, MA
2022

All metrics benchmarked against2021

In 2022, Millbury recorded 322 total traffic crashes, a 5.6% decrease from the 341 crashes reported in 2021. While overall crashes and injuries declined, the most significant year-over-year change was the elimination of crash-related fatalities, which dropped from two in the prior period to zero in the current period.

322

-5.6%was 341

Total Crash Events

0

-100.0%was 2

Persons Killed

80

-11.1%was 90

Persons Injured

14

7.7%was 13

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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Millbury showed improvement from 2021 to 2022. The total number of crashes decreased by 5.6%, from 341 to 322. This downward trend extended to crash severity, with total injuries falling by 11.1% from 90 to 80, and fatalities decreasing from two to zero.

14

Hit-and-Run Crashes — 2022

7.7% vs prior (13)

The number of hit-and-run incidents saw a slight increase from 13 in 2021 to 14 in 2022. Correspondingly, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, edged up from 3.8% to 4.3%. This indicates a slight upward trend in this specific crash type over the one-year period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 2-100.0%

1

Cyclists Injured

Prior: 10.0%

79

Motorists Injured

Prior: 88-10.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 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 remained broadly consistent year-over-year, with Friday being the peak day for crashes in both 2021 (60 crashes) and 2022 (66 crashes). However, the peak hour for crashes shifted from a broader afternoon window in 2021, which had peaks at 2 PM and 4 PM, to a more concentrated evening commute peak at 5 PM in 2022, which saw 36 crashes.

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

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

Crash Severity Breakdown

Crash severity decreased significantly from 2021 to 2022, with fatal crashes dropping from two to zero. The count of serious injury crashes also fell from six to two. Conversely, the number of crashes resulting in minor injuries increased from 32 in 2021 to 47 in 2022, representing a shift in the injury distribution from more severe categories to less severe ones. The proportion of non-injury crashes remained stable at approximately 78% in both periods.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes0.6%
-66.7%prior 6
Minor Injury47minor injury crashes14.6%
46.9%prior 32
Possible Injury15possible injury crashes4.7%
-34.8%prior 23
No Injury252no injury crashes78.3%
-5.3%prior 266

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

While 'No improper driving' was the most cited factor in both years, its count decreased from 75 to 61. The most significant shift was in crashes attributed to 'Failed to yield right of way,' which increased by 160% from 15 incidents in 2021 to 39 in 2022, becoming the third most common factor. Speed-related factors also saw an increase; crashes involving 'Driving too fast for conditions' rose from 11 to 19, and those for 'Exceeded authorized speed limit' doubled from 5 to 10.

Officer-Reported Primary Contributing Cause

No improper driving61 (18.9%)-18.7%prior 75
Inattention41 (12.7%)-14.6%prior 48
Failed to yield right of way39 (12.1%)160.0%prior 15
Followed too closely36 (11.2%)5.9%prior 34
Failure to keep in proper lane or running off road27 (8.4%)17.4%prior 23
Driving too fast for conditions19 (5.9%)72.7%prior 11
Other improper action13 (4%)8.3%prior 12
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner13 (4%)116.7%prior 6
Exceeded authorized speed limit10 (3.1%)100.0%prior 5
Made an improper turn7 (2.2%)

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

Road & Environmental Conditions

The majority of crashes in both 2021 and 2022 occurred in clear weather on dry roads during daylight hours. There were no significant shifts in the distribution of conditions between the two periods. Crashes on dry roads accounted for 76.8% of incidents in 2021 and 73.6% in 2022, while daylight crashes made up 69.2% of the total in 2021 and 65.5% in 2022, indicating stable patterns.

Weather

Clear222 (70.0%)
-8.6%prior 243
Cloudy34 (10.7%)
54.5%prior 22
Rain30 (9.5%)
15.4%prior 26
Snow15 (4.7%)
25.0%prior 12
Cloudy/Rain7 (2.2%)
-22.2%prior 9
Sleet, hail (freezing rain or drizzle)2 (0.6%)
Cloudy/Snow2 (0.6%)
Snow/Cloudy1 (0.3%)
Other1 (0.3%)
Clear/Cloudy1 (0.3%)

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

Lighting

Daylight211 (65.7%)
-10.6%prior 236
Dark - lighted roadway68 (21.2%)
-1.4%prior 69
Dark - roadway not lighted25 (7.8%)
25.0%prior 20
Dusk11 (3.4%)
10.0%prior 10
Dawn5 (1.6%)
0.0%prior 5
Dark - unknown roadway lighting1 (0.3%)

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

Road Surface

Dry237 (74.1%)
-9.5%prior 262
Wet56 (17.5%)
-1.8%prior 57
Snow14 (4.4%)
27.3%prior 11
Ice11 (3.4%)
57.1%prior 7
Slush2 (0.6%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda being the most frequent in both years. While Toyota-involved incidents decreased from 103 to 93, Honda-involved incidents rose from 50 to 64. Analysis of persons involved shows a demographic shift, with the 26-34 age group's involvement increasing from 119 individuals in 2021 to 132 in 2022, while the 35-44 age group's involvement decreased from 117 to 90.

Top Vehicle Makes (579 vehicles)

1
TOYOTA93 (16.1%)
-9.7%prior 103
2
FORD68 (11.7%)
4.6%prior 65
3
HONDA64 (11.1%)
28.0%prior 50
4
CHEVROLET40 (6.9%)
-14.9%prior 47
5
NISSAN34 (5.9%)
-17.1%prior 41
6
SUBARU28 (4.8%)
47.4%prior 19
7
JEEP27 (4.7%)
68.8%prior 16
8
HYUNDAI21 (3.6%)
-30.0%prior 30
9
DODGE16 (2.8%)
33.3%prior 12
10
GMC15 (2.6%)
66.7%prior 9

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

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

Sex Distribution (648 persons with recorded sex)

Male376 (58.0%)
-7.8%prior 408
Female272 (42.0%)
1.1%prior 269

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

Speed Limit Zones

The distribution of crashes across different speed zones saw minimal changes between 2021 and 2022. The 30 MPH and 65 MPH zones continued to be the locations with the highest number of crashes, recording 97 and 78 incidents in 2022, respectively, compared to 98 and 76 in the prior year. Notably, one of the two fatalities recorded in 2021 occurred in a 35 MPH zone, while 2022 saw no fatalities in any speed zone.

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

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: MILLBURY, MA
  • Total crash records analyzed: 322
  • Total persons involved: 705
  • Total vehicles involved: 579

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

ThatCarHitMe.com · An Injuria.ai Company

Millbury, MA Crash Report — 2022 | ThatCarHitMe.com