ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WILMINGTON, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
508 CRASHES IN
WILMINGTON, MA
2024
In 2024, Wilmington recorded 508 total traffic crashes, a 1.6% decrease from the 516 crashes reported in 2023. While overall crashes and injuries declined, the most notable year-over-year shift was an increase in total fatalities, which rose from one in 2023 to three in 2024.
508
▼ -1.6%was 516
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
141
▼ -8.4%was 154
Persons Injured
37
▲ 5.7%was 35
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in Wilmington shows a slight decrease in traffic collisions, with total crashes falling by 1.6% from 516 to 508 year-over-year. This was accompanied by an 8.4% reduction in injuries, from 154 to 141. However, this downward trend in crash volume was contrasted by a rise in severity, as fatalities increased from one to three during the same period.
37
Hit-and-Run Crashes — 2024
▲ 5.7% vs prior (35)
Hit-and-run incidents saw a slight increase in both count and rate year-over-year. The number of hit-and-run crashes rose from 35 in 2023 to 37 in 2024. As a percentage of all collisions, the hit-and-run rate also trended upward, increasing from 6.8% to 7.3% over the same period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
1
Pedestrians Injured
2
Cyclists Injured
138
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash timing patterns shifted between the two periods. In 2024, Friday was the most frequent day for crashes with 92 incidents, a change from 2023 when Monday and Thursday were the peak days with 86 crashes each. The peak hour for collisions remained consistent at 2 p.m. in both years, though the number of crashes during that hour decreased from 49 in 2023 to 39 in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in 2024 compared to the prior year. The number of fatal crashes increased from one to three, raising the share of fatal crashes from 0.2% to 0.6% of all incidents. Conversely, the proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) saw a slight decrease, accounting for 20.1% of all crashes in 2024 compared to 21.7% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes shifted year-over-year. In 2024, 'Inattention' was the most cited factor with 91 crashes, up from 82 in 2023. 'Failed to yield right of way' saw a significant count increase of 48.1%, rising from 52 incidents to 77 and becoming the third-most common factor. Meanwhile, crashes attributed to 'Followed too closely' decreased by 17.3% from 81 to 67 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2024 occurred under slightly different environmental conditions than in the previous year. The proportion of collisions happening in 'Clear' weather increased, accounting for 68.3% of incidents compared to 62.0% in 2023. Proportions for crashes during daylight hours (66.7% vs. 64.5%) and on dry road surfaces (75.4% vs. 74.6%) remained relatively stable between the two periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top makes of vehicles involved in crashes changed between periods. In 2024, Toyota was the most common make with 148 vehicles, overtaking Honda, which was the top make in 2023 with 160 vehicles. The demographic profile of persons involved in crashes also shifted, with the 35-44 age group being the most represented in 2024 (188 persons), compared to the 26-34 age group in 2023 (211 persons).
Top Vehicle Makes (940 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
64 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,067 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones remained broadly consistent, with the 65 mph zone accounting for the most crashes in both 2024 (158) and 2023 (162). A notable shift occurred in lower speed zones, where crashes in 25 mph zones increased from 63 to 87, while crashes in 30 mph zones decreased from 102 to 79. In 2024, fatal crashes occurred in the 65 mph (2) and 35 mph (1) zones, whereas the single fatality in 2023 occurred in a 65 mph zone.
Fatal crashes by zone: 35 mph: 1 of 108 (0.926%) · 65 mph: 2 of 158 (1.266%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: WILMINGTON, MA
- Total crash records analyzed: 508
- Total persons involved: 1,173
- Total vehicles involved: 940
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved