Monthly Traffic Safety Analysis

37 CRASHES IN
DRACUT, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, Dracut, MA recorded 37 total crashes, an increase of 5.7% from the 35 crashes reported in April 2022. A notable positive shift was the complete absence of serious injuries (Severity A) in April 2023, down from 5 serious injuries in the prior year. Minor injuries, however, increased from 3 to 8.

37

5.7%was 35

Total Crash Events

0

Persons Killed

13

8.3%was 12

Persons Injured

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight increase in total crashes year-over-year, rising from 35 in April 2022 to 37 in April 2023. Total injuries also saw a minor increase from 12 to 13, while fatalities remained at zero in both periods, indicating a stable trend in the most severe outcomes.

2

Hit-and-Run Crashes — April 2023

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 in both April 2022 and April 2023. However, the hit-and-run rate slightly decreased from 5.7% in the prior period to 5.4% in the current period, reflecting the overall increase in total crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

12

Motorists Injured

Prior: 120.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted significantly year-over-year. The peak day for crashes moved from Monday in April 2022 (9 crashes) to Saturday in April 2023 (11 crashes). Similarly, the peak hour for crashes shifted from 1 PM (5 crashes) in the prior period to 8 AM (6 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both April 2022 and April 2023, with no change in the fatal crash rate. A significant change was the absence of serious injuries (Severity A) in April 2023, compared to 5 serious injuries in April 2022. Minor injuries, however, increased from 3 in the prior year to 8 in the current year, while possible injuries remained stable at 2.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes21.6%
166.7%prior 3
Possible Injury2possible injury crashes5.4%
0.0%prior 2
No Injury25no injury crashes67.6%
8.7%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' decreased from 10 crashes in April 2022 to 9 crashes in April 2023, with its share decreasing from 28.6% to 24.3%. 'Failed to yield right of way' increased from 3 crashes to 5 crashes, and 'Followed too closely' increased from 1 crash to 2 crashes. Notably, 'Glare' appeared as a factor in 2 crashes in April 2023, whereas it was not present in the prior year's data.

Officer-Reported Primary Contributing Cause

Inattention9 (24.3%)-10.0%prior 10
No improper driving8 (21.6%)0.0%prior 8
Failed to yield right of way5 (13.5%)
Other improper action3 (8.1%)
Followed too closely2 (5.4%)
Failure to keep in proper lane or running off road2 (5.4%)
Glare2 (5.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.7%)
Disregarded traffic signs, signals, road markings1 (2.7%)
Over-correcting/over-steering1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under clear weather conditions increased from 24 in April 2022 to 28 in April 2023, while crashes during rain decreased from 5 to 3. For lighting conditions, daylight crashes rose from 24 to 29, and crashes on dry road surfaces increased from 30 to 33. Conversely, crashes on wet road surfaces decreased from 5 to 4.

Weather

Clear28 (75.7%)
16.7%prior 24
Cloudy5 (13.5%)
-16.7%prior 6
Rain3 (8.1%)
-40.0%prior 5
Cloudy/Sleet, hail (freezing rain or drizzle)1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight29 (80.6%)
20.8%prior 24
Dark - lighted roadway2 (5.6%)
Dark - roadway not lighted2 (5.6%)
-60.0%prior 5
Dark - unknown roadway lighting2 (5.6%)
Other1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry33 (89.2%)
10.0%prior 30
Wet4 (10.8%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 56 in April 2022 to 71 in April 2023. Toyota became the most frequently involved make, increasing from 9 to 13, while Honda decreased from 11 to 9. Significant shifts in age distribution were observed, with persons aged 16-20 increasing from 5 to 12, and those aged 65+ increasing from 5 to 13.

Top Vehicle Makes (71 vehicles)

1
TOYOTA13 (18.3%)
44.4%prior 9
2
HONDA9 (12.7%)
-18.2%prior 11
3
FORD8 (11.3%)
4
HYUNDAI5 (7%)
5
CHEVROLET5 (7%)
-50.0%prior 10
6
KIA4 (5.6%)
7
NISSAN4 (5.6%)
8
GMC3 (4.2%)
9
INFI2 (2.8%)
10
LEXUS2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (83 persons with recorded sex)

Male52 (62.7%)
44.4%prior 36
Female31 (37.3%)
29.2%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 23 in April 2022 to 20 in April 2023, while crashes in 35 mph zones increased from 3 to 5. The 20 mph zone, which had 1 crash in the prior period, had no crashes in the current period. Fatal crash rates remained at zero across all speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: DRACUT, MA
  • Total crash records analyzed: 37
  • Total persons involved: 91
  • Total vehicles involved: 71

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). "DRACUT, MA Crash Intelligence Report: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dracut/april-2023-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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Dracut, MA Crash Report — April 2023 | ThatCarHitMe.com