Monthly Traffic Safety Analysis

26 CRASHES IN
WILMINGTON, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

WILMINGTON experienced a decrease in total crashes in February 2024 compared to February 2023, with 26 crashes versus 33 crashes, marking a 21.21% reduction. The most notable year-over-year shift was the significant decrease in crashes attributed to 'Inattention,' which dropped from 6 crashes in the prior period to 1 crash in the current period. Fatalities remained at zero in both periods, indicating no change in the fatal crash outcome.

26

-21.2%was 33

Total Crash Events

0

Persons Killed

6

-14.3%was 7

Persons Injured

3

50.0%was 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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for total crashes in WILMINGTON is downward, with a 21.21% decrease from 33 crashes in February 2023 to 26 crashes in February 2024. This reduction suggests a decline in overall crash incidents year-over-year for the selected month.

3

Hit-and-Run Crashes — February 2024

50.0% vs prior (2)

Hit-and-run crashes increased from 2 in February 2023 to 3 in February 2024. Consequently, the hit-and-run rate rose from 6.1% of total crashes in the prior period to 11.5% in the current period, indicating an upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

5

Motorists Injured

Prior: 6-16.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 Thursday in February 2023, which saw 11 crashes, to Friday in February 2024, with 7 crashes. Similarly, the peak hour changed from 2 PM with 6 crashes in the prior period to 5 PM with 5 crashes in the current period, indicating a shift in the busiest times for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 for both February 2023 and February 2024. The total number of injured persons decreased slightly from 7 in February 2023 to 6 in February 2024. In February 2024, 6 crashes (23.1% of total crashes) resulted in injury (1 serious, 2 minor, 3 possible), compared to 6 minor injury crashes (18.2% of total crashes) in February 2023.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
Minor Injury2minor injury crashes7.7%
-66.7%prior 6
Possible Injury3possible injury crashes11.5%
No Injury20no injury crashes76.9%
-25.9%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw changes in crash counts year-over-year. 'Inattention' crashes decreased significantly from 6 to 1, and 'Followed too closely' crashes dropped from 5 to 2. Conversely, 'Failed to yield right of way' crashes increased from 3 to 4, and 'Other improper action' crashes increased from 1 to 2.

Officer-Reported Primary Contributing Cause

No improper driving8 (30.8%)0.0%prior 8
Failed to yield right of way4 (15.4%)
Failure to keep in proper lane or running off road3 (11.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (7.7%)
Other improper action2 (7.7%)
Followed too closely2 (7.7%)-60.0%prior 5
Distracted1 (3.8%)
Inattention1 (3.8%)-83.3%prior 6
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.8%)
Disregarded traffic signs, signals, road markings1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions slightly increased from 22 in February 2023 to 23 in February 2024, while 'Dry' road surface crashes decreased from 25 to 20. Crashes in 'Daylight' conditions decreased from 18 to 13, and 'Wet' road surface crashes increased from 2 to 5, indicating a shift towards more crashes on wet roads.

Weather

Clear23 (88.5%)
4.5%prior 22
Cloudy1 (3.8%)
Rain1 (3.8%)
Sleet, hail (freezing rain or drizzle)1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight13 (52.0%)
-27.8%prior 18
Dark - lighted roadway8 (32.0%)
-11.1%prior 9
Dark - roadway not lighted3 (12.0%)
Dark - unknown roadway lighting1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry20 (76.9%)
-20.0%prior 25
Wet5 (19.2%)
Ice1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (45 vehicles)

1
FORD8 (17.8%)
-11.1%prior 9
2
HONDA7 (15.6%)
16.7%prior 6
3
CHEVROLET5 (11.1%)
4
TOYOTA4 (8.9%)
-60.0%prior 10
5
HYUNDAI2 (4.4%)
6
ACURA2 (4.4%)
7
MERCEDES-BENZ2 (4.4%)
8
NISSAN2 (4.4%)
9
JEEP2 (4.4%)
10
VOLKSWAGEN1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

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

Sex Distribution (48 persons with recorded sex)

Male31 (64.6%)
-35.4%prior 48
Female17 (35.4%)
-19.0%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 12 in February 2023 to 7 in February 2024. Meanwhile, crashes in the 30 mph speed zone increased from 4 to 6, and crashes in the 35 mph speed zone increased from 8 to 9. All speed zones reported zero fatal crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: WILMINGTON, MA
  • Total crash records analyzed: 26
  • Total persons involved: 51
  • Total vehicles involved: 45

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). "WILMINGTON, MA Crash Intelligence Report: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/february-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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Wilmington, MA Crash Report — February 2024 | ThatCarHitMe.com