ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WILMINGTON, MA · MAY 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/wilmington/may-2025-report
Monthly Traffic Safety Analysis
31 CRASHES IN
WILMINGTON, MA
MAY 2025
WILMINGTON experienced a decrease in total crashes, from 41 in May 2024 to 31 in May 2025, representing a 24.4% reduction year-over-year. Despite this overall decline, total injuries remained stable at 8 in both periods, and there were no fatalities reported in either month. A notable shift was the absence of DUI crashes in May 2025, down from 2 in May 2024, while speeding-related crashes increased from 0 to 3.
31
▼ -24.4%was 41
Total Crash Events
0
Persons Killed
8
Persons Injured
1
▼ -66.7%was 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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in WILMINGTON is downward, with a 24.4% decrease in total crashes from 41 in May 2024 to 31 in May 2025. Fatalities remained stable at 0 in both periods, and total injuries also held steady at 8. This indicates a positive trend in reducing the frequency of crash events.
1
Hit-and-Run Crashes — May 2025
▼ -66.7% vs prior (3)
Hit-and-run crashes decreased from 3 in May 2024 to 1 in May 2025, representing a 66.7% reduction in count. The hit-and-run rate also decreased from 7.3% to 3.2% year-over-year. This indicates a downward trend in the occurrence of hit-and-run incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
7
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, with 8 crashes in May 2025 and 9 in May 2024; Tuesday also recorded 8 crashes in May 2025. The peak hour for crashes shifted from 12 p.m. with 6 crashes in May 2024 to 4 p.m. with 8 crashes in May 2025. May 2024 also saw a peak at 6 a.m. with 6 crashes, while May 2025 had a secondary peak at 10 a.m. with 5 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 0 in both May 2024 and May 2025. The proportion of crashes resulting in minor injuries increased from 7.3% (3 crashes) to 9.7% (3 crashes), while possible injury crashes increased from 2.4% (1 crash) to 12.9% (4 crashes). Consequently, the share of crashes with no injuries decreased from 90.2% to 77.4%, indicating a higher proportion of injury-involved crashes in May 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor shifted from 'Failed to yield right of way' and 'Inattention' (7 crashes each) in May 2024 to 'No improper driving' (8 crashes) in May 2025. Crashes attributed to 'Failed to yield right of way' decreased from 7 to 3, a 57.1% reduction in count. 'Inattention' crashes decreased from 7 to 6, a 14.3% decrease in count, while 'Followed too closely' crashes decreased from 5 to 3, a 40% reduction in count. Additionally, 'Driving too fast for conditions' and 'Exceeded authorized speed limit' emerged as new factors in May 2025, accounting for 2 and 1 crashes respectively, compared to 0 in May 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 27 in May 2024 to 16 in May 2025. Similarly, crashes during rainy conditions (including 'Cloudy/Rain' and 'Rain/Rain') decreased from 9 to 4. Crashes occurring in non-daylight conditions (Dark, Dawn, Dusk) decreased from 9 in May 2024 to 3 in May 2025, while the proportion of crashes occurring in daylight increased from 78% to 90.3%. The count of crashes on wet road surfaces decreased from 10 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
Toyota and Honda remained the top two vehicle makes involved in crashes, though their counts decreased from 14 to 11 and 12 to 9, respectively. Jeep involvement decreased from 6 to 3, while Kia involvement increased from 1 to 4. In terms of person demographics, the 55-64 age group saw the largest decrease in involvement, dropping from 14 to 6 persons, while the 26-34 and 65+ age groups each saw an increase of 2 persons involved.
Top Vehicle Makes (61 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (76 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events
Speed Limit Zones
Fatalities remained at 0 across all speed zones in both periods. The highest number of crashes in May 2025 occurred in the 65 MPH zone (10 crashes), a slight decrease from 11 crashes in May 2024. Crashes in the 35 MPH zone decreased from 9 to 5, and in the 25 MPH zone from 9 to 4. Conversely, crashes in the 30 MPH zone increased from 5 to 8, indicating a shift in crash distribution towards this speed limit.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: WILMINGTON, MA
- Total crash records analyzed: 31
- Total persons involved: 79
- Total vehicles involved: 61
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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/may-2025-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-05-01 – 2025-05-31
Generated: June 21, 2026 · All rights reserved