ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILTON, MA · DECEMBER 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/milton/december-2025-report
Monthly Traffic Safety Analysis
68 CRASHES IN
MILTON, MA
DECEMBER 2025
In December 2025, MILTON recorded 68 total crashes, a slight decrease from the 69 crashes reported in December 2024. This represents a 1.5% reduction in total crashes year-over-year. The most notable shift was a significant 45.5% decrease in total injuries, falling from 33 in the prior year to 18 in the current period.
68
▼ -1.4%was 69
Total Crash Events
0
Persons Killed
18
▼ -45.5%was 33
Persons Injured
8
▲ 14.3%was 7
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 · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for December in MILTON shows a stable trend in total crash count, with a minor decrease of 1 crash from 69 in the prior year to 68 in the current year. However, total injuries saw a substantial decline, dropping by 15 injuries from 33 to 18, indicating a positive trend in crash severity outcomes.
8
Hit-and-Run Crashes — December 2025
▲ 14.3% vs prior (7)
Hit-and-run crashes increased by 1, from 7 in December 2024 to 8 in December 2025. The hit-and-run rate also saw an increase, rising from 10.1% in the prior period to 11.8% in the current period, indicating an upward trend in these incidents.
Vulnerable Road User Casualties
0
Motorists Killed
18
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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 Friday in December 2024 (19 crashes) to Saturday in December 2025 (15 crashes). While the peak hour remained relatively consistent with 6 crashes, the prior year's peak was at 7 PM and the current year's at 8 PM. Monday maintained a high crash count, with 12 crashes in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both December 2024 and December 2025, indicating no change in the fatal crash rate. Total injuries decreased significantly by 45.5%, from 33 in the prior period to 18 in the current period. Minor injuries decreased from 13 (18.8% share) to 7 (10.3% share), while possible injuries slightly increased from 8 (11.6% share) to 9 (13.2% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased by 4 crashes from 22 in the prior period to 26 in the current period. 'Inattention' crashes saw a notable decrease of 5, falling from 7 to 2, while 'Failed to yield right of way' crashes increased by 2, from 4 to 6. 'Followed too closely' decreased slightly by 1 crash, from 9 to 8.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear/Clear' weather conditions decreased from 31 in the prior period to 24 in the current period, while 'Clear' conditions remained at 14 crashes. Daylight crashes decreased from 29 to 22, making 'Dark - lighted roadway' the most frequent lighting condition with 35 crashes, up from 25. Crashes on 'Ice' road surfaces increased from 3 to 8, while those on 'Snow' surfaces decreased from 8 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 134 in December 2024 to 126 in December 2025. Toyota remained the top vehicle make, with its involvement increasing from 22 vehicles to 34 vehicles, while Honda's involvement decreased from 18 to 9. The age group 26-34 saw a decrease of 9 persons involved, from 38 to 29, and the 55-64 age group decreased by 6 persons, from 18 to 12.
Top Vehicle Makes (126 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (136 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones saw the largest increase, rising from 4 in the prior period to 11 in the current period. Conversely, crashes in 35 mph zones decreased from 6 to 2, and 65 mph zones decreased from 3 to 1. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: MILTON, MA
- Total crash records analyzed: 68
- Total persons involved: 161
- Total vehicles involved: 126
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). "MILTON, MA Crash Intelligence Report: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/december-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: 2025-12-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved