Monthly Traffic Safety Analysis

26 CRASHES IN
DUXBURY, MA
JUNE 2024

All metrics benchmarked againstJune 2023

In DUXBURY, MA, total crashes increased slightly from 24 in June 2023 to 26 in June 2024, representing an 8.3% rise. Despite this, total injuries saw a significant decrease, falling from 10 to 5, a 50% reduction year-over-year. This reduction in injuries is the most notable shift in safety outcomes for the period.

26

8.3%was 24

Total Crash Events

0

Persons Killed

5

-50.0%was 10

Persons Injured

2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in DUXBURY saw a slight increase of 8.3% year-over-year, rising from 24 crashes in June 2023 to 26 crashes in June 2024. Conversely, total injuries experienced a substantial downward trend, decreasing by 50% from 10 injuries in the prior period to 5 injuries in the current period.

2

Hit-and-Run Crashes — June 2024

100.0% vs prior (1)

Hit-and-run crashes increased from 1 in June 2023 to 2 in June 2024, representing a 100% rise. Concurrently, the hit-and-run rate increased from 4.2% of total crashes in the prior period to 7.7% in the current period, indicating an upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 2-50.0%

4

Motorists Injured

Prior: 8-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes in DUXBURY showed shifts in peak periods. The peak day for crashes moved from Tuesday with 8 crashes in June 2023 to Thursday with 8 crashes in June 2024. Similarly, the peak hour for crashes changed from 10 PM with 3 crashes in the prior period to 7 PM with 2 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both June 2023 and June 2024. The proportion of minor injury crashes (severity B) decreased from 29.2% (7 crashes) in the prior period to 11.5% (3 crashes) in the current period. Crashes with no injuries (severity O) increased their share from 66.7% (16 crashes) to 80.8% (21 crashes) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes11.5%
-57.1%prior 7
Possible Injury2possible injury crashes7.7%
100.0%prior 1
No Injury21no injury crashes80.8%
31.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' increased from 10 crashes in June 2023 to 11 crashes in June 2024, a 10% increase, remaining the most frequent factor. 'Inattention' crashes saw a 400% increase, rising from 1 crash to 5 crashes, while 'Failed to yield right of way' crashes decreased by 60%, from 5 crashes to 2 crashes. Crashes attributed to 'Disregarded traffic signs, signals, road markings' decreased by 50%, from 2 crashes to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving11 (42.3%)10.0%prior 10
Inattention5 (19.2%)
Failure to keep in proper lane or running off road2 (7.7%)
Other improper action2 (7.7%)
Failed to yield right of way2 (7.7%)-60.0%prior 5
Followed too closely1 (3.8%)
Exceeded authorized speed limit1 (3.8%)
Driving too fast for conditions1 (3.8%)
Disregarded traffic signs, signals, road markings1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased slightly from 21 in June 2023 to 20 in June 2024. Crashes during 'Cloudy' conditions increased by 100%, from 2 to 4 crashes. For road surface conditions, 'Dry' conditions remained constant with 23 crashes in both periods, while crashes on 'Wet' road surfaces increased from 0 to 2. Crashes occurring in 'Daylight' increased from 15 to 21, while those in 'Dark - lighted roadway' decreased from 5 to 0.

Weather

Clear20 (76.9%)
-4.8%prior 21
Cloudy4 (15.4%)
Rain1 (3.8%)
Rain/Severe crosswinds1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight21 (80.8%)
40.0%prior 15
Dark - roadway not lighted5 (19.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry23 (88.5%)
0.0%prior 23
Wet2 (7.7%)
Water (standing, moving)1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (42 vehicles)

1
HONDA6 (14.3%)
2
JEEP6 (14.3%)
3
FORD5 (11.9%)
4
NISSAN3 (7.1%)
5
TOYOTA3 (7.1%)
-50.0%prior 6
6
CHEVROLET3 (7.1%)
7
KIA2 (4.8%)
8
MITS2 (4.8%)
9
VOLKSWAGEN2 (4.8%)
10
BUIC1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

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

Sex Distribution (46 persons with recorded sex)

Male26 (56.5%)
4.0%prior 25
Female20 (43.5%)
-16.7%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 60 mph zones saw an 80% increase, rising from 5 in June 2023 to 9 in June 2024. Conversely, crashes in 30 mph zones decreased by 75%, falling from 8 to 2. Crashes in 20 mph zones increased by 200%, from 1 to 3, while 40 mph zones experienced a 42.8% decrease, from 7 to 4 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: DUXBURY, MA
  • Total crash records analyzed: 26
  • Total persons involved: 50
  • Total vehicles involved: 42

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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/duxbury/june-2024-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 — June 2024 | ThatCarHitMe.com