Monthly Traffic Safety Analysis

27 CRASHES IN
DUXBURY, MA
MAY 2025

All metrics benchmarked againstMay 2024

Total crashes in DUXBURY increased by 22.7% from 22 in May 2024 to 27 in May 2025. This period also saw a notable increase in crashes where 'No improper driving' was listed as a contributing factor, rising from 5 to 9 incidents.

27

22.7%was 22

Total Crash Events

0

Persons Killed

11

10.0%was 10

Persons Injured

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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in DUXBURY showed an upward trend, increasing by 5 incidents year-over-year. This represents a 22.7% rise in total crashes from May 2024 to May 2025.

1

Hit-and-Run Crashes — May 2025

3.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 1010.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday in May 2024, with 8 incidents, to Friday in May 2025, with 6 incidents. While the peak hour remained 3 p.m. with 4 crashes in both periods, Saturday crashes increased from 0 to 5, and Thursday crashes decreased by 50% from 8 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero for both May 2024 and May 2025. Total injuries slightly increased from 10 to 11, while the proportion of crashes resulting in 'No Injury' rose from 59.1% in May 2024 to 70.4% in May 2025.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes18.5%
-28.6%prior 7
Possible Injury2possible injury crashes7.4%
100.0%prior 1
No Injury19no injury crashes70.4%
46.2%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', increased by 80%, from 5 incidents in May 2024 to 9 in May 2025. 'Failed to yield right of way' incidents doubled from 2 to 4, while 'Other improper action' decreased by 66.7% from 3 to 1. Factors such as 'Visibility obstructed', 'Emotional', and 'Failure to keep in proper lane or running off road' were present in May 2025 but not in May 2024, while 'Made an improper turn', 'Distracted', and 'Exceeded authorized speed limit' were present in May 2024 but not in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving9 (33.3%)80.0%prior 5
Failed to yield right of way4 (14.8%)
Inattention3 (11.1%)
Emotional1 (3.7%)
Followed too closely1 (3.7%)
Other improper action1 (3.7%)
Visibility obstructed1 (3.7%)
Failure to keep in proper lane or running off road1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased slightly in proportion from 86.4% in May 2024 to 81.5% in May 2025. Conversely, crashes during dark lighting conditions saw an increase in proportion from 13.6% to 18.5%, with no crashes recorded at dawn in May 2025 compared to one in May 2024.

Weather

Clear14 (51.9%)
-26.3%prior 19
Clear/Clear8 (29.6%)
Cloudy2 (7.4%)
Cloudy/Rain2 (7.4%)
Rain1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight22 (81.5%)
22.2%prior 18
Dark - roadway not lighted4 (14.8%)
Dark - lighted roadway1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry23 (85.2%)
21.1%prior 19
Wet4 (14.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (43 vehicles)

1
FORD7 (16.3%)
40.0%prior 5
2
TOYOTA7 (16.3%)
-12.5%prior 8
3
HONDA6 (14%)
4
JEEP4 (9.3%)
5
CHEVROLET2 (4.7%)
6
NISSAN2 (4.7%)
7
KIA1 (2.3%)
8
KIA MOTORS CORP1 (2.3%)
9
LINC1 (2.3%)
10
MERCEDES-BENZ1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (63 persons with recorded sex)

Male32 (50.8%)
68.4%prior 19
Female30 (47.6%)
42.9%prior 21
X / Unspecified1 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

The 60 mph speed zone continued to account for the highest number of crashes in both periods, with 9 incidents each. Crashes in the 30 mph zone saw a significant increase, more than doubling from 3 incidents in May 2024 to 7 in May 2025. Additionally, crashes were recorded in 15 mph, 20 mph, and 50 mph zones in May 2025, which had no crashes in May 2024, while crashes in 5 mph and 10 mph zones were present in May 2024 but not in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: DUXBURY, MA
  • Total crash records analyzed: 27
  • Total persons involved: 67
  • Total vehicles involved: 43

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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/duxbury/may-2025-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

Duxbury, MA Crash Report — May 2025 | ThatCarHitMe.com