Monthly Traffic Safety Analysis

57 CRASHES IN
MILTON, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, MILTON, MA experienced 57 crashes, a slight decrease of 1 crash (-1.72%) compared to the 58 crashes recorded in June 2024. The most notable year-over-year shift was an 83.33% increase in hit-and-run crashes, rising from 6 to 11 incidents.

57

▼ -1.7%was 58

Total Crash Events

0

Persons Killed

22

▲ 10.0%was 20

Persons Injured

11

▲ 83.3%was 6

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained relatively stable year-over-year, with a minor decrease of 1 crash from 58 to 57. However, total injuries increased by 10%, from 20 in June 2024 to 22 in June 2025.

11

Hit-and-Run Crashes — June 2025

▲ 83.3% vs prior (6)

Hit-and-run crashes increased significantly by 5 incidents, rising from 6 in June 2024 to 11 in June 2025. This resulted in the hit-and-run rate increasing by 9 percentage points, from 10.3% to 19.3% of all crashes.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

21

Motorists Injured

Prior: 20↑5.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Sunday in June 2024 (12 crashes) to Tuesday in June 2025 (12 crashes). The peak hour also changed, moving from 5 PM in June 2024 (8 crashes) to 3 PM in June 2025 (6 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either period. Total injuries increased by 10%, from 20 in June 2024 to 22 in June 2025, with possible injury crashes increasing from 3 to 6, while serious injury crashes decreased from 1 to 0.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes17.5%
↓-9.1%prior 11
Possible Injury6possible injury crashes10.5%
↑100.0%prior 3
No Injury36no injury crashes63.2%
↓-14.3%prior 42

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Inattention' saw a significant increase of 150%, rising from 2 crashes in June 2024 to 5 crashes in June 2025. Conversely, 'Followed too closely' decreased by 27.3%, from 11 crashes to 8 crashes. The number of crashes where 'No improper driving' was cited decreased slightly from 18 to 17.

Officer-Reported Primary Contributing Cause

No improper driving17 (29.8%)↓-5.6%prior 18
Followed too closely8 (14%)↓-27.3%prior 11
Inattention5 (8.8%)
Failure to keep in proper lane or running off road5 (8.8%)
Failed to yield right of way4 (7%)
Made an improper turn3 (5.3%)
Exceeded authorized speed limit2 (3.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.5%)
Other improper action2 (3.5%)
Disregarded traffic signs, signals, road markings1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 46 in June 2024 to 35 in June 2025. Crashes on 'Wet' road surfaces increased from 5 to 9 year-over-year. Incidents in 'Dark - lighted roadway' conditions rose from 9 to 13.

Weather

Clear/Clear29 (55.8%)
↑20.8%prior 24
Clear10 (19.2%)
↓-64.3%prior 28
Cloudy6 (11.5%)
Rain/Rain2 (3.8%)
Cloudy/Rain1 (1.9%)
Cloudy/Cloudy1 (1.9%)
Rain1 (1.9%)
Rain/Cloudy1 (1.9%)
Clear/Cloudy1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight35 (66.0%)
↓-23.9%prior 46
Dark - lighted roadway13 (24.5%)
↑44.4%prior 9
Dark - roadway not lighted3 (5.7%)
Dusk2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry44 (83.0%)
↓-15.4%prior 52
Wet9 (17.0%)
↑80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 6, from 121 in June 2024 to 115 in June 2025. Honda vehicles involved in crashes increased by 100%, from 11 to 22, becoming the most frequently involved make, while Jeep vehicles decreased by 36.4%, from 11 to 7.

Top Vehicle Makes (115 vehicles)

1
HONDA22 (19.1%)
↑100.0%prior 11
2
TOYOTA15 (13%)
↑15.4%prior 13
3
JEEP7 (6.1%)
↓-36.4%prior 11
4
FORD6 (5.2%)
↓-14.3%prior 7
5
NISSAN6 (5.2%)
↓-33.3%prior 9
6
HYUNDAI6 (5.2%)
7
CHEVROLET5 (4.3%)
↓-37.5%prior 8
8
ACURA5 (4.3%)
9
LEXUS4 (3.5%)
10
SUBARU4 (3.5%)
↓-33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (113 persons with recorded sex)

Male62 (54.9%)
↓-34.0%prior 94
Female51 (45.1%)
↑50.0%prior 34

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 55 MPH speed zones saw a notable decrease of 8 incidents, falling from 18 to 10. Conversely, crashes in 35 MPH speed zones increased by 4 incidents, rising from 5 to 9. There were no fatal crashes in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: MILTON, MA
  • Total crash records analyzed: 57
  • Total persons involved: 144
  • Total vehicles involved: 115

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/june-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

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Milton, MA Crash Report — June 2025 | ThatCarHitMe.com