Monthly Traffic Safety Analysis

39 CRASHES IN
DRACUT, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in DRACUT, MA decreased by 15.2%, from 46 in December 2023 to 39 in December 2024. Despite this reduction in overall crash incidents, the number of total injuries increased by 55.6%, rising from 9 to 14. This suggests a notable shift towards more injurious crashes even as crash frequency declined.

39

-15.2%was 46

Total Crash Events

0

Persons Killed

14

55.6%was 9

Persons Injured

3

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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in total crashes, with a 15.2% reduction from 46 crashes in December 2023 to 39 crashes in December 2024. This represents a decrease of 7 crashes year-over-year. However, total injuries increased by 55.6% during the same period.

3

Hit-and-Run Crashes — December 2024

0.0% vs prior (3)

The number of hit-and-run crashes remained constant at 3 in both periods. However, the hit-and-run rate increased from 6.5% in the prior period to 7.7% in the current period. This indicates an upward trend in the proportion of crashes that are hit-and-runs.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

13

Motorists Injured

Prior: 944.4%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 Friday, with 9 incidents in the prior period, to Tuesday, with 12 incidents in the current period. The peak hour also changed, moving from 3 PM with 7 crashes in the prior period to 5 PM with 6 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes or fatalities were recorded in either period. Total injuries increased by 55.6%, from 9 in the prior period to 14 in the current period. The proportion of crashes resulting in minor injuries remained stable at approximately 13%, while possible injury crashes increased from 2.2% to 10.3% of all crashes.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes12.8%
-16.7%prior 6
Possible Injury4possible injury crashes10.3%
300.0%prior 1
No Injury28no injury crashes71.8%
-24.3%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, "No improper driving," decreased by 8 crashes, from 23 in the prior period to 15 in the current period. Conversely, crashes attributed to "Failed to yield right of way" increased by 4, rising from 2 to 6. "Inattention" also saw an increase, from 2 crashes in the prior period to 5 in the current period.

Officer-Reported Primary Contributing Cause

No improper driving15 (38.5%)-34.8%prior 23
Failed to yield right of way6 (15.4%)
Inattention5 (12.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (7.7%)
Failure to keep in proper lane or running off road2 (5.1%)
Fatigued/asleep1 (2.6%)
Other improper action1 (2.6%)
Over-correcting/over-steering1 (2.6%)
Driving too fast for conditions1 (2.6%)
History heart/epilepsy/fainting1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under clear weather conditions remained the most frequent, with 26 in the current period compared to 25 in the prior period. Crashes in rainy conditions decreased notably from 11 in the prior period to 4 in the current period. Crashes on dry road surfaces decreased from 30 to 25, while those on wet surfaces also decreased from 14 to 12.

Weather

Clear26 (66.7%)
4.0%prior 25
Rain4 (10.3%)
-63.6%prior 11
Clear/Other3 (7.7%)
Cloudy2 (5.1%)
Fog, smog, smoke1 (2.6%)
Rain/Cloudy1 (2.6%)
Snow1 (2.6%)
Snow/Rain1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway15 (38.5%)
-21.1%prior 19
Daylight15 (38.5%)
-28.6%prior 21
Dark - roadway not lighted5 (12.8%)
Dusk3 (7.7%)
Dawn1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry25 (64.1%)
-16.7%prior 30
Wet12 (30.8%)
-14.3%prior 14
Ice1 (2.6%)
Snow1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Honda became the most frequent vehicle make involved in crashes, with 14 vehicles, up from 10 in the prior period, while Ford decreased from 12 to 6. The 35-44 age group saw a decrease in persons involved from 20 to 14. Conversely, the 65+ age group experienced an increase from 10 to 13 persons involved in crashes.

Top Vehicle Makes (69 vehicles)

1
HONDA14 (20.3%)
40.0%prior 10
2
TOYOTA13 (18.8%)
44.4%prior 9
3
CHEVROLET6 (8.7%)
4
FORD6 (8.7%)
-50.0%prior 12
5
KIA4 (5.8%)
6
HYUNDAI3 (4.3%)
7
SUBARU3 (4.3%)
8
JEEP2 (2.9%)
-60.0%prior 5
9
BMW2 (2.9%)
10
GMC2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (77 persons with recorded sex)

Male48 (62.3%)
-5.9%prior 51
Female29 (37.7%)
-21.6%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed zone for either period. Crashes in 30 MPH zones decreased from 33 in the prior period to 21 in the current period. Conversely, crashes in 25 MPH zones increased from 1 to 4, and crashes in 45 MPH zones also increased from 1 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: DRACUT, MA
  • Total crash records analyzed: 39
  • Total persons involved: 87
  • Total vehicles involved: 69

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dracut/december-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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Dracut, MA Crash Report — December 2024 | ThatCarHitMe.com