Monthly Traffic Safety Analysis

12 CRASHES IN
DOUGLAS, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

In March 2024, Douglas recorded 12 crashes, an increase of 9.1% compared to 11 crashes in March 2023. While total crashes saw a slight rise, the most notable shift was a significant 60.0% decrease in total injuries, falling from 5 to 2 year-over-year. Fatalities remained at zero in both periods.

12

9.1%was 11

Total Crash Events

0

Persons Killed

2

-60.0%was 5

Persons Injured

0

Fatal Crash Events

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 · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Douglas showed a slight increase, with total crashes rising by 9.1% from 11 in March 2023 to 12 in March 2024. Despite this, total injuries decreased substantially by 60.0%, indicating a shift towards less severe outcomes in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 5-60.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted significantly year-over-year. In March 2023, the peak day for crashes was Thursday with 5 incidents, and the peak hour was 7 AM with 3 crashes. In contrast, March 2024 saw Saturday and Friday as peak days with 3 crashes each, and the peak hour shifted to 5 PM, also with 3 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either March 2023 or March 2024. Total injuries decreased by 60.0%, from 5 injured persons in the prior period to 2 in the current period. The proportion of crashes resulting in no injury increased from 81.8% in March 2023 to 91.7% in March 2024, while possible injuries, which accounted for 9.1% of crashes previously, were absent in the current period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes8.3%
0.0%prior 1
No Injury11no injury crashes91.7%
22.2%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

"No improper driving" as a contributing factor significantly increased by 100.0%, rising from 4 crashes in March 2023 to 8 crashes in March 2024, and its share of all crashes grew from 36.4% to 66.7%. Conversely, "Inattention" decreased by 66.7% in count, from 3 crashes to 1 crash, with its share falling from 27.3% to 8.3%. "Exceeded authorized speed limit" emerged as a factor in the current period with 1 crash, while "Physical impairment" was present in the prior period with 1 crash but absent in the current.

Officer-Reported Primary Contributing Cause

No improper driving8 (66.7%)
Exceeded authorized speed limit1 (8.3%)
Inattention1 (8.3%)
Other improper action1 (8.3%)
Over-correcting/over-steering1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under "Clear" weather conditions remained stable at 8 incidents in both periods, while incidents involving rain-related conditions increased from 3 to 4. A notable shift occurred in lighting conditions, with crashes during "Daylight" decreasing from 9 in March 2023 to 6 in March 2024. Concurrently, crashes in "Dark - roadway not lighted" conditions quadrupled from 1 to 4 year-over-year.

Weather

Clear8 (66.7%)
0.0%prior 8
Rain3 (25.0%)
Rain/Cloudy1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Lighting

Daylight6 (50.0%)
-33.3%prior 9
Dark - roadway not lighted4 (33.3%)
Dark - lighted roadway1 (8.3%)
Dawn1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field

Road Surface

Dry8 (66.7%)
14.3%prior 7
Wet4 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (13 vehicles)

1
TOYOTA4 (30.8%)
2
AUDI2 (15.4%)
3
FORD1 (7.7%)
-80.0%prior 5
4
HYUNDAI1 (7.7%)
5
INF1 (7.7%)
6
JEEP1 (7.7%)
7
PLSR1 (7.7%)
8
SUBARU1 (7.7%)
9
CADI1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

Sex Distribution (20 persons with recorded sex)

Male12 (60.0%)
33.3%prior 9
Female8 (40.0%)
-33.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph, 35 mph, and 40 mph speed zones each decreased by one incident year-over-year. The 30 mph zone maintained 4 crashes in both periods. A significant shift was observed with 4 crashes occurring in the 45 mph speed zone in March 2024, a speed limit not present in the crash data for March 2023. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: DOUGLAS, MA
  • Total crash records analyzed: 12
  • Total persons involved: 20
  • Total vehicles involved: 13

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). "DOUGLAS, MA Crash Intelligence Report: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/douglas/march-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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Douglas, MA Crash Report — March 2024 | ThatCarHitMe.com