Monthly Traffic Safety Analysis

38 CRASHES IN
WILMINGTON, MA
AUGUST 2022

All metrics benchmarked againstAugust 2021

Total crashes in Wilmington decreased from 46 in August 2021 to 38 in August 2022, representing a 17.4% reduction. The most notable year-over-year shift was the absence of traffic fatalities in August 2022, down from one fatality in August 2021.

38

-17.4%was 46

Total Crash Events

0

-100.0%was 1

Persons Killed

12

-7.7%was 13

Persons Injured

1

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 · 2022-08-01 to 2022-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Wilmington trended downwards year-over-year, with a 17.4% decrease in total crashes, falling from 46 in August 2021 to 38 in August 2022. This period also saw a decrease in total fatalities from 1 to 0 and a slight reduction in total injuries from 13 to 12.

1

Hit-and-Run Crashes — August 2022

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both August 2021 and August 2022. The hit-and-run rate slightly increased from 2.2% in the prior period to 2.6% in the current period, despite the total number of crashes decreasing.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

12

Motorists Injured

Prior: 13-7.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · 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 Tuesday with 11 crashes in August 2021 to Monday with 10 crashes in August 2022. The peak hour also changed, moving from 8 AM with 7 crashes in the prior period to 12 PM with 6 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in August 2021 to 0 in August 2022. While minor injuries remained relatively stable (6 in August 2022 vs. 5 in August 2021), possible injury crashes saw a significant reduction from 7 to 2, and serious injury crashes increased from 0 to 2.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes5.3%
Minor Injury6minor injury crashes15.8%
20.0%prior 5
Possible Injury2possible injury crashes5.3%
-71.4%prior 7
No Injury26no injury crashes68.4%
-21.2%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving', increased by 42.9% from 7 crashes in August 2021 to 10 crashes in August 2022. Conversely, 'Inattention' decreased by 57.1% from 7 crashes to 3 crashes, and 'Distracted' crashes fell by 80% from 5 crashes to 1 crash. 'Driving too fast for conditions' also saw a decrease, from 3 crashes to 0 crashes.

Officer-Reported Primary Contributing Cause

No improper driving10 (26.3%)42.9%prior 7
Failed to yield right of way5 (13.2%)0.0%prior 5
Followed too closely4 (10.5%)
Failure to keep in proper lane or running off road3 (7.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (7.9%)
Inattention3 (7.9%)-57.1%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (5.3%)
Physical impairment2 (5.3%)
Distracted1 (2.6%)-80.0%prior 5
Made an improper turn1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in 'Clear' weather decreased from 31 to 27, and crashes in 'Daylight' conditions decreased from 40 to 29. Crashes on 'Dry' road surfaces also saw a reduction from 39 to 31. There was a slight increase in crashes during 'Dark - lighted roadway' conditions, rising from 3 to 5.

Weather

Clear27 (71.1%)
-12.9%prior 31
Cloudy4 (10.5%)
-55.6%prior 9
Cloudy/Rain2 (5.3%)
Rain2 (5.3%)
Clear/Rain1 (2.6%)
Clear/Other1 (2.6%)
Rain/Cloudy1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Weather condition at time of crash

Lighting

Daylight29 (76.3%)
-27.5%prior 40
Dark - lighted roadway5 (13.2%)
Dark - roadway not lighted4 (10.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Lighting condition field

Road Surface

Dry31 (81.6%)
-20.5%prior 39
Wet6 (15.8%)
0.0%prior 6
Sand, mud, dirt, oil, gravel1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Road surface condition field

Vehicles & Demographics

The number of Honda vehicles involved in crashes increased from 10 to 12, while Toyota vehicles decreased slightly from 13 to 12. There was a notable decrease in Chevrolet vehicles involved, from 11 to 7. The age group 65+ saw an increase in persons involved in crashes, rising from 4 to 10, while the 16-20 age group decreased from 10 to 4.

Top Vehicle Makes (73 vehicles)

1
HONDA12 (16.4%)
20.0%prior 10
2
TOYOTA12 (16.4%)
-7.7%prior 13
3
CHEVROLET7 (9.6%)
-36.4%prior 11
4
FORD7 (9.6%)
40.0%prior 5
5
JEEP6 (8.2%)
6
NISSAN5 (6.8%)
-37.5%prior 8
7
SUBARU4 (5.5%)
8
MACK2 (2.7%)
9
HYUNDAI2 (2.7%)
10
CADI2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Vehicle unit records

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

Sex Distribution (70 persons with recorded sex)

Male41 (58.6%)
-16.3%prior 49
Female29 (41.4%)
-12.1%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 16 to 10, and the single fatal crash in the prior period occurred in this zone. Crashes in the 35 mph zone also saw a decrease, from 16 to 6. Conversely, crashes in the 25 mph zone increased from 3 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · 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: 2022-08-01 through 2022-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-08-01 through 2022-08-31 (31 days)
  • Geographic scope: WILMINGTON, MA
  • Total crash records analyzed: 38
  • Total persons involved: 89
  • Total vehicles involved: 73

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: August 2022." Published June 21, 2026. Reporting period: 2022-08-01 to 2022-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/august-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 — August 2022 | ThatCarHitMe.com