Monthly Traffic Safety Analysis

15 CRASHES IN
DUXBURY, MA
APRIL 2026

All metrics benchmarked againstApril 2025

In April 2026, Duxbury recorded 15 total crashes, a decrease of 21.1% compared to the 19 crashes reported in April 2025. Despite fewer crashes, total injuries saw a substantial increase, rising from 2 in April 2025 to 6 in April 2026, marking a 200% increase year-over-year. Fatalities remained at zero in both periods.

15

-21.1%was 19

Total Crash Events

0

Persons Killed

6

200.0%was 2

Persons Injured

0

-100.0%was 2

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 · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, Duxbury experienced a downward trend in total crashes, decreasing by 21.1% from 19 crashes in April 2025 to 15 crashes in April 2026. Fatalities remained at zero in both periods. However, total injuries significantly increased by 200%, from 2 to 6, suggesting that while crash frequency decreased, the severity of some crashes leading to injuries intensified.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 2200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Duxbury shifted year-over-year. The peak day for crashes moved from Thursday, which had 6 crashes in April 2025, to Saturday, which recorded 4 crashes in April 2026. Concurrently, Saturday crashes increased from 0 to 4, while Wednesday and Thursday crashes decreased from 5 to 2 and 6 to 3, respectively. The peak crash hour also shifted slightly from 8 AM in April 2025 to 7 AM in April 2026, with both hours recording 3 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both April 2025 and April 2026. However, the overall injury landscape changed significantly, with total injuries rising from 2 to 6. Minor injury crashes increased from 1 in April 2025 (5.3% share of crashes) to 4 in April 2026 (26.7% share of crashes). Correspondingly, crashes resulting in no injuries decreased from 17 (89.5% share) to 10 (66.7% share) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes26.7%
300.0%prior 1
Possible Injury1possible injury crashes6.7%
0.0%prior 1
No Injury10no injury crashes66.7%
-41.2%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts year-over-year. 'Failed to yield right of way' increased from 1 crash in April 2025 to 3 crashes in April 2026. Conversely, 'No improper driving' decreased from 4 crashes to 2 crashes, and 'Followed too closely' decreased from 3 crashes to 2 crashes. 'Inattention', 'Disregarded traffic signs, signals, road markings', 'Failure to keep in proper lane or running off road', and 'Fatigued/asleep' remained consistent with 2, 1, 1, and 1 crash respectively in both periods.

Officer-Reported Primary Contributing Cause

Failed to yield right of way3 (20%)
No improper driving2 (13.3%)
Followed too closely2 (13.3%)
Inattention2 (13.3%)
Visibility obstructed1 (6.7%)
Disregarded traffic signs, signals, road markings1 (6.7%)
Failure to keep in proper lane or running off road1 (6.7%)
Fatigued/asleep1 (6.7%)
Other improper action1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in daylight conditions increased from 11 in April 2025 to 13 in April 2026, while those in dark or dawn conditions decreased. Crashes on wet road surfaces decreased by 50%, from 6 in April 2025 to 3 in April 2026. Similarly, crashes during rainy conditions (Cloudy/Rain + Rain) decreased from a combined 3 to 2 year-over-year.

Weather

Clear8 (53.3%)
33.3%prior 6
Clear/Clear2 (13.3%)
-66.7%prior 6
Cloudy2 (13.3%)
Cloudy/Rain2 (13.3%)
Cloudy/Cloudy1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash

Lighting

Daylight13 (86.7%)
18.2%prior 11
Dark - roadway not lighted1 (6.7%)
Dawn1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field

Road Surface

Dry12 (80.0%)
-7.7%prior 13
Wet3 (20.0%)
-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
TOYOTA5 (15.6%)
0.0%prior 5
2
FORD5 (15.6%)
3
NISSAN4 (12.5%)
4
JEEP4 (12.5%)
5
VOLVO3 (9.4%)
6
MERCEDES-BENZ2 (6.3%)
7
CHEVROLET2 (6.3%)
8
HYUNDAI2 (6.3%)
9
SUBARU2 (6.3%)
10
BMW1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records

Sex Distribution (33 persons with recorded sex)

Female16 (48.5%)
14.3%prior 14
Male16 (48.5%)
-33.3%prior 24
X / Unspecified1 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 3 in April 2025 to 5 in April 2026. Conversely, crashes in the 60 mph zone decreased from 6 to 4, and in the 40 mph zone, they decreased from 3 to 2. The 25 mph zone also saw a decrease from 2 crashes to 1 crash year-over-year. No fatalities were recorded in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2026-04-01 through 2026-04-30 (30 days)
  • Geographic scope: DUXBURY, MA
  • Total crash records analyzed: 15
  • Total persons involved: 34
  • Total vehicles involved: 32

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