Monthly Traffic Safety Analysis

60 CRASHES IN
WILMINGTON, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

WILMINGTON experienced a 30.4% increase in total crashes, rising from 46 in December 2021 to 60 in December 2022. The most significant shift was a 125% increase in total injuries, from 8 to 18, alongside a notable emergence of 5 hit-and-run crashes in the current period compared to none in the prior period.

60

30.4%was 46

Total Crash Events

0

Persons Killed

18

125.0%was 8

Persons Injured

5

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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in WILMINGTON showed an upward trend, with total crashes increasing by 30.4% from 46 to 60. This was accompanied by a substantial 125% rise in total injuries, climbing from 8 to 18 year-over-year.

5

Hit-and-Run Crashes — December 2022

8.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

18

Motorists Injured

Prior: 8125.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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 Monday (9 crashes) in December 2021 to Friday (12 crashes) in December 2022. The peak hour also changed significantly, moving from 11 AM with 6 crashes in the prior period to 5 PM with 10 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the total number of injuries increased by 125%, from 8 in December 2021 to 18 in December 2022. Serious injuries (code A) emerged with 3 occurrences in the current period, compared to none in the prior period, indicating a worsening injury profile.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes5%
Minor Injury12minor injury crashes20%
200.0%prior 4
Possible Injury1possible injury crashes1.7%
-66.7%prior 3
No Injury43no injury crashes71.7%
10.3%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The factor 'No improper driving' saw a 128.6% increase in count, rising from 7 to 16 crashes. Conversely, 'Inattention' decreased by 22.2% in count, from 9 to 7 crashes. 'Distracted' crashes saw a 300% increase, from 1 to 4 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving16 (26.7%)128.6%prior 7
Inattention7 (11.7%)-22.2%prior 9
Driving too fast for conditions7 (11.7%)
Followed too closely5 (8.3%)
Distracted4 (6.7%)
Exceeded authorized speed limit4 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5%)
Glare2 (3.3%)
Failed to yield right of way2 (3.3%)-60.0%prior 5
Visibility obstructed2 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Rain' conditions increased from 3 to 11, and those in 'Cloudy' conditions rose from 6 to 11. Regarding road surface, crashes on 'Wet' roads nearly doubled, increasing from 11 to 21, while 'Ice' as a road condition for crashes was present 5 times in the prior period but not at all in the current period. Crashes occurring in 'Dark - lighted roadway' conditions increased significantly from 9 to 23.

Weather

Clear22 (37.9%)
0.0%prior 22
Rain11 (19.0%)
Cloudy11 (19.0%)
83.3%prior 6
Rain/Cloudy3 (5.2%)
Clear/Cloudy2 (3.4%)
Snow/Sleet, hail (freezing rain or drizzle)2 (3.4%)
Snow2 (3.4%)
Snow/Blowing sand, snow2 (3.4%)
Clear/Unknown1 (1.7%)
Cloudy/Rain1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight25 (42.4%)
4.2%prior 24
Dark - lighted roadway23 (39.0%)
155.6%prior 9
Dark - roadway not lighted8 (13.6%)
14.3%prior 7
Dark - unknown roadway lighting2 (3.4%)
Dawn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry33 (55.0%)
17.9%prior 28
Wet21 (35.0%)
90.9%prior 11
Snow6 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 86 to 106. HONDA vehicles involved in crashes surged by 200%, from 6 to 18, making it the most frequent make in the current period, while TOYOTA remained constant at 13 vehicles. The 21-25 age group saw a rise in persons involved, from 14 to 20, and the 35-44 age group increased from 16 to 21.

Top Vehicle Makes (106 vehicles)

1
HONDA18 (17%)
200.0%prior 6
2
TOYOTA13 (12.3%)
0.0%prior 13
3
CHEVROLET12 (11.3%)
50.0%prior 8
4
DODGE8 (7.5%)
5
NISSAN7 (6.6%)
-30.0%prior 10
6
FORD6 (5.7%)
-40.0%prior 10
7
GMC5 (4.7%)
8
JEEP5 (4.7%)
0.0%prior 5
9
SUBARU4 (3.8%)
-20.0%prior 5
10
AUDI3 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (109 persons with recorded sex)

Male67 (61.5%)
24.1%prior 54
Female42 (38.5%)
-6.7%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones doubled, increasing from 8 in December 2021 to 16 in December 2022. Crashes in 25 mph zones also increased from 8 to 11, and 65 mph zones saw an increase from 10 to 13 crashes. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: WILMINGTON, MA
  • Total crash records analyzed: 60
  • Total persons involved: 120
  • Total vehicles involved: 106

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: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/december-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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Wilmington, MA Crash Report — December 2022 | ThatCarHitMe.com