Yearly Traffic Safety Analysis

304 CRASHES IN
MILLBURY, MA
2023

All metrics benchmarked against2022

In 2023, Millbury recorded 304 total traffic crashes, a 5.6% decrease from the 322 crashes reported in 2022. While the overall number of collisions declined, the severity of these incidents increased. The most notable change was the occurrence of one fatal crash in 2023, compared to zero in the prior year.

304

-5.6%was 322

Total Crash Events

1

Persons Killed

83

3.8%was 80

Persons Injured

18

28.6%was 14

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of traffic crashes in Millbury saw a modest decline of 5.6% from 2022 to 2023, with 304 incidents compared to 322 in the previous year. Despite this decrease in total crashes, the number of people injured rose slightly from 80 to 83. The data indicates a trend of fewer overall crashes but with slightly more severe outcomes.

18

Hit-and-Run Crashes — 2023

28.6% vs prior (14)

Hit-and-run incidents trended upward in 2023 compared to the previous year. The number of hit-and-run crashes increased by 28.6%, rising from 14 in 2022 to 18 in 2023. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also increased from 4.3% to 5.9% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

80

Motorists Injured

Prior: 791.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 2023, the peak days for crashes were Saturday and Sunday, each with 49 incidents, a change from 2022 when Friday was the peak day with 66 crashes. The peak hour for collisions also shifted slightly earlier, from 5 p.m. in 2022 (36 crashes) to 4 p.m. in 2023 (29 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in 2023 compared to the prior year, with one fatal crash recorded versus none in 2022. The number of serious injury crashes more than doubled, increasing from 2 to 5 incidents. This represents a growth in the share of serious injury crashes from 0.6% to 1.6% of all collisions. Consequently, the proportion of non-injury crashes decreased from 78.3% in 2022 to 75.3% in 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury5serious injury crashes1.6%
150.0%prior 2
Minor Injury48minor injury crashes15.8%
2.1%prior 47
Possible Injury17possible injury crashes5.6%
13.3%prior 15
No Injury229no injury crashes75.3%
-9.1%prior 252

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes showed notable shifts between 2022 and 2023. While 'No improper driving' remained the most cited factor, its count increased by 39.3% from 61 to 85 incidents. Crashes attributed to 'Inattention' decreased in count from 41 to 36, and those due to 'Failed to yield right of way' saw a significant 41% drop in count, from 39 to 23 incidents. This drop moved 'Failed to yield' from the third to the fourth-ranked contributing factor in 2023.

Officer-Reported Primary Contributing Cause

No improper driving85 (28%)39.3%prior 61
Inattention36 (11.8%)-12.2%prior 41
Followed too closely29 (9.5%)-19.4%prior 36
Failed to yield right of way23 (7.6%)-41.0%prior 39
Driving too fast for conditions22 (7.2%)15.8%prior 19
Failure to keep in proper lane or running off road17 (5.6%)-37.0%prior 27
Other improper action15 (4.9%)15.4%prior 13
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner12 (3.9%)-7.7%prior 13
Made an improper turn8 (2.6%)14.3%prior 7
Exceeded authorized speed limit7 (2.3%)-30.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely consistent year-over-year. In both 2023 and 2022, approximately 65.5% of crashes occurred in daylight conditions. Crashes on dry road surfaces accounted for 76.0% of the total in 2023, a slight proportional increase from 73.6% in 2022. Similarly, the proportion of crashes in clear weather was stable, at 68.1% in 2023 compared to 68.9% in the prior year.

Weather

Clear207 (73.7%)
-6.8%prior 222
Rain25 (8.9%)
-16.7%prior 30
Cloudy18 (6.4%)
-47.1%prior 34
Snow7 (2.5%)
-53.3%prior 15
Cloudy/Rain5 (1.8%)
-28.6%prior 7
Sleet, hail (freezing rain or drizzle)4 (1.4%)
Snow/Sleet, hail (freezing rain or drizzle)3 (1.1%)
Rain/Fog, smog, smoke2 (0.7%)
Cloudy/Fog, smog, smoke2 (0.7%)
Rain/Cloudy2 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight199 (65.5%)
-5.7%prior 211
Dark - lighted roadway65 (21.4%)
-4.4%prior 68
Dark - roadway not lighted26 (8.6%)
4.0%prior 25
Dusk9 (3.0%)
-18.2%prior 11
Dawn3 (1.0%)
-40.0%prior 5
Dark - unknown roadway lighting1 (0.3%)
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry231 (76.0%)
-2.5%prior 237
Wet59 (19.4%)
5.4%prior 56
Snow8 (2.6%)
-42.9%prior 14
Ice3 (1.0%)
-72.7%prior 11
Slush3 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda leading in both years, though the counts for all three decreased in 2023. Analysis of person demographics shows a shift in the age of individuals involved in crashes. The proportion of people in the 16-20 age group decreased from 15.2% of all persons in 2022 to 11.9% in 2023, while the share of those in the 21-25 age group increased from 11.9% to 14.3%.

Top Vehicle Makes (519 vehicles)

1
TOYOTA73 (14.1%)
-21.5%prior 93
2
FORD60 (11.6%)
-11.8%prior 68
3
HONDA52 (10%)
-18.8%prior 64
4
SUBARU35 (6.7%)
25.0%prior 28
5
CHEVROLET30 (5.8%)
-25.0%prior 40
6
HYUNDAI22 (4.2%)
4.8%prior 21
7
NISSAN21 (4%)
-38.2%prior 34
8
JEEP17 (3.3%)
-37.0%prior 27
9
VOLKSWAGEN16 (3.1%)
60.0%prior 10
10
GMC16 (3.1%)
6.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (578 persons with recorded sex)

Male349 (60.4%)
-7.2%prior 376
Female229 (39.6%)
-15.8%prior 272

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

There was a noticeable shift in crashes toward higher speed zones in 2023. The number of crashes in zones with speed limits of 55 mph or higher increased from 91 in 2022 to 107 in 2023, driven by a rise in incidents in 55 mph zones from 13 to 33. Conversely, crashes in zones with limits of 40 mph or lower decreased from 193 to 138. The single fatal crash in 2023 occurred in a 35 mph zone.

Fatal crashes by zone: 35 mph: 1 of 43 (2.326%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: MILLBURY, MA
  • Total crash records analyzed: 304
  • Total persons involved: 631
  • Total vehicles involved: 519

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/millbury/2023-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

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Millbury, MA Crash Report — 2023 | ThatCarHitMe.com