Monthly Traffic Safety Analysis

58 CRASHES IN
MILTON, MA
JUNE 2024

All metrics benchmarked againstJune 2023

MILTON experienced a decrease in total crashes in June 2024 compared to June 2023, with 58 crashes versus 69, marking a 15.94% reduction. Total injuries also decreased by 35.48%, falling from 31 to 20. The most notable shift was the significant reduction in injury-involved crashes, which dropped from 24 to 15.

58

-15.9%was 69

Total Crash Events

0

Persons Killed

20

-35.5%was 31

Persons Injured

6

-25.0%was 8

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in MILTON for June 2024 show a downward trajectory compared to June 2023. Total crashes decreased by 11 incidents, representing a 15.94% reduction year-over-year. Similarly, total injuries declined by 11 persons, a decrease of 35.48%.

6

Hit-and-Run Crashes — June 2024

-25.0% vs prior (8)

The number of hit-and-run crashes decreased from 8 in June 2023 to 6 in June 2024. The hit-and-run rate also saw a slight decline, moving from 11.6% of total crashes to 10.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

20

Motorists Injured

Prior: 28-28.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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 Friday in June 2023 (13 crashes) to Sunday in June 2024 (12 crashes). While the peak hour remained 5p in both periods, crash counts at 10a saw a significant drop from 8 in June 2023 to 0 in June 2024. Conversely, crashes at 1p increased from 2 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in MILTON during either June 2024 or June 2023. The proportion of crashes resulting in any injury decreased, with 15 injury-involved crashes out of 58 total crashes (25.86%) in June 2024, down from 24 injury-involved crashes out of 69 total crashes (34.78%) in June 2023. The number of persons sustaining minor injuries decreased from 26 to 16.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
Minor Injury11minor injury crashes19%
-45.0%prior 20
Possible Injury3possible injury crashes5.2%
-25.0%prior 4
No Injury42no injury crashes72.4%
-2.3%prior 43

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor 'Followed too closely' decreased by 5 incidents, from 16 in June 2023 to 11 in June 2024, and its ranking shifted from first to second. 'Failed to yield right of way' also saw a decrease of 6 incidents, dropping from 10 to 4. 'No improper driving' increased by 1 incident, moving from 17 to 18 and becoming the most cited factor.

Officer-Reported Primary Contributing Cause

No improper driving18 (31%)5.9%prior 17
Followed too closely11 (19%)-31.3%prior 16
Failed to yield right of way4 (6.9%)-60.0%prior 10
Failure to keep in proper lane or running off road3 (5.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.2%)
Inattention2 (3.4%)
Exceeded authorized speed limit2 (3.4%)
Disregarded traffic signs, signals, road markings2 (3.4%)
Physical impairment2 (3.4%)
Made an improper turn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under adverse weather conditions decreased significantly, with 6 crashes in June 2024 compared to 23 in June 2023. Similarly, crashes on wet road surfaces decreased from 17 to 5 year-over-year. Crashes during dark or low-light conditions also saw a reduction, from 17 to 12 incidents.

Weather

Clear28 (48.3%)
-3.4%prior 29
Clear/Clear24 (41.4%)
50.0%prior 16
Cloudy3 (5.2%)
Rain2 (3.4%)
-77.8%prior 9
Rain/Cloudy1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight46 (79.3%)
-9.8%prior 51
Dark - lighted roadway9 (15.5%)
-35.7%prior 14
Dark - roadway not lighted1 (1.7%)
Dawn1 (1.7%)
Dusk1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry52 (89.7%)
4.0%prior 50
Wet5 (8.6%)
-70.6%prior 17
Sand, mud, dirt, oil, gravel1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 169 in June 2023 to 145 in June 2024. The 26-34 age group experienced the largest decrease in persons involved, dropping from 42 to 28. Toyota remained a top vehicle make, though its involvement count decreased from 29 to 13, while Jeep involvement increased from 7 to 11.

Top Vehicle Makes (121 vehicles)

1
TOYOTA13 (10.7%)
-55.2%prior 29
2
JEEP11 (9.1%)
57.1%prior 7
3
HONDA11 (9.1%)
-38.9%prior 18
4
NISSAN9 (7.4%)
0.0%prior 9
5
CHEVROLET8 (6.6%)
14.3%prior 7
6
FORD7 (5.8%)
0.0%prior 7
7
SUBARU6 (5%)
-14.3%prior 7
8
BMW4 (3.3%)
9
ACURA4 (3.3%)
10
MERCEDES-BENZ4 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

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

Sex Distribution (129 persons with recorded sex)

Male94 (72.9%)
13.3%prior 83
Female34 (26.4%)
-52.1%prior 71
X / Unspecified1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 11 incidents in June 2023 to 3 in June 2024, representing the largest count reduction in any zone. Crashes in the 55 mph zone also decreased from 24 to 18 incidents. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: MILTON, MA
  • Total crash records analyzed: 58
  • Total persons involved: 145
  • Total vehicles involved: 121

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 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/june-2024-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 2024 | ThatCarHitMe.com