Monthly Traffic Safety Analysis

21 CRASHES IN
DUXBURY, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, Duxbury experienced 21 crashes, marking a 40% increase compared to the 15 crashes recorded in April 2021. Despite this rise in total incidents, total injuries saw a slight decrease from 9 to 8. The most notable shift was the increase in DUI-related crashes, which rose from 0 in April 2021 to 3 in April 2022.

21

40.0%was 15

Total Crash Events

0

Persons Killed

8

-11.1%was 9

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 · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Duxbury show an upward trend year-over-year, with total crashes increasing by 40% from 15 in April 2021 to 21 in April 2022. However, total injuries decreased slightly by 11.1%, from 9 in the prior period to 8 in the current period. Fatalities remained at zero for both periods.

1

Hit-and-Run Crashes — April 2022

0.0% vs prior (1)

The number of hit-and-run crashes remained consistent at 1 in both April 2021 and April 2022. However, the proportion of total crashes that were hit-and-run incidents decreased from 6.7% in the prior period to 4.8% in the current period. This reflects a stable count of hit-and-run incidents within an increased overall crash volume.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 9-11.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak hour for crashes shifted from 11a with 2 crashes in April 2021 to 4p with 4 crashes in April 2022. While April 2021 saw multiple peak days with 3 crashes each, April 2022 had two peak days, Wednesday and Friday, each with 5 crashes. Crashes on Tuesdays decreased from 1 in April 2021 to 0 in April 2022, while Saturday crashes increased from 0 to 3.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the distribution of injury severities changed. Serious injuries (code A) were reported in 2 crashes in April 2022, accounting for 9.5% of incidents, whereas none were reported in April 2021. Conversely, possible injuries (code C) were present in 3 crashes (20%) in April 2021 but not in April 2022.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes9.5%
Minor Injury4minor injury crashes19%
0.0%prior 4
No Injury14no injury crashes66.7%
100.0%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes year-over-year. Crashes attributed to 'Followed too closely' increased from 0 in April 2021 to 3 in April 2022, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' rose from 1 to 3 crashes. Meanwhile, incidents where 'No improper driving' was cited decreased from 5 crashes in April 2021 to 3 crashes in April 2022.

Officer-Reported Primary Contributing Cause

Followed too closely3 (14.3%)
No improper driving3 (14.3%)-40.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (14.3%)
Failed to yield right of way2 (9.5%)
Illness2 (9.5%)
Distracted2 (9.5%)
Physical impairment1 (4.8%)
Driving too fast for conditions1 (4.8%)
Failure to keep in proper lane or running off road1 (4.8%)
Inattention1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 11 in April 2021 to 17 in April 2022, and incidents during 'Daylight' hours rose from 10 to 15. The number of crashes on 'Dry' road surfaces also increased, from 13 to 19. The count of crashes occurring in 'Rain' conditions remained stable at 2 for both periods.

Weather

Clear17 (81.0%)
54.5%prior 11
Cloudy2 (9.5%)
Rain2 (9.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight15 (71.4%)
50.0%prior 10
Dark - roadway not lighted5 (23.8%)
Dusk1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry19 (90.5%)
46.2%prior 13
Wet2 (9.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (34 vehicles)

1
TOYOTA8 (23.5%)
2
FORD5 (14.7%)
3
HONDA3 (8.8%)
4
NISSAN3 (8.8%)
5
JEEP2 (5.9%)
-60.0%prior 5
6
HD2 (5.9%)
7
CHEVROLET2 (5.9%)
8
SUBARU2 (5.9%)
9
KIA1 (2.9%)
10
MERCEDES-BENZ1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

Sex Distribution (36 persons with recorded sex)

Male26 (72.2%)
100.0%prior 13
Female10 (27.8%)
-28.6%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 6 in April 2021 to 8 in April 2022, while those in 40 mph zones rose from 1 to 4. Incidents in 60 mph zones also increased, from 4 to 6 crashes year-over-year. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: DUXBURY, MA
  • Total crash records analyzed: 21
  • Total persons involved: 37
  • Total vehicles involved: 34

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 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/duxbury/april-2022-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 2022 | ThatCarHitMe.com