Monthly Traffic Safety Analysis

69 CRASHES IN
MILTON, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, MILTON experienced 69 total crashes, a 30.2% increase from the 53 crashes reported in December 2023. Notably, the number of fatalities decreased from 1 in the prior period to 0 in the current period, despite an overall rise in crash incidents.

69

30.2%was 53

Total Crash Events

0

-100.0%was 1

Persons Killed

33

17.9%was 28

Persons Injured

7

250.0%was 2

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in MILTON show an upward trend year-over-year, with total crashes increasing by 16, from 53 in December 2023 to 69 in December 2024. This represents a 30.2% rise in total crashes for the month.

7

Hit-and-Run Crashes — December 2024

250.0% vs prior (2)

Hit-and-run crashes increased significantly year-over-year, rising from 2 incidents in December 2023 to 7 incidents in December 2024. Consequently, the hit-and-run rate increased from 3.8% to 10.1% of all crashes, indicating an upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

32

Motorists Injured

Prior: 2814.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with current crashes on Friday increasing to 19 from 11 in the prior year. The peak hour for crashes shifted from 5 PM with 8 crashes in December 2023 to 7 PM with 6 crashes in December 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in December 2023 to 0 in December 2024. Total injuries increased from 28 to 33 year-over-year, with minor injuries rising from 7 to 13, while possible injuries decreased from 14 to 8.

Outcome by Severity (Crash Events)

Minor Injury13minor injury crashes18.8%
85.7%prior 7
Possible Injury8possible injury crashes11.6%
-42.9%prior 14
No Injury44no injury crashes63.8%
46.7%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'Followed too closely' (12 crashes) in the prior period to 'No improper driving' (22 crashes) in the current period, representing a 175% increase in 'No improper driving' incidents. 'Followed too closely' crashes decreased by 3, from 12 to 9, a 25% reduction in count. 'Inattention' crashes increased from 5 to 7, a 40% rise in count.

Officer-Reported Primary Contributing Cause

No improper driving22 (31.9%)175.0%prior 8
Followed too closely9 (13%)-25.0%prior 12
Inattention7 (10.1%)40.0%prior 5
Failure to keep in proper lane or running off road6 (8.7%)
Failed to yield right of way4 (5.8%)-20.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (4.3%)
Disregarded traffic signs, signals, road markings2 (2.9%)
Made an improper turn1 (1.4%)
Driving too fast for conditions1 (1.4%)
Operating defective equipment1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces increased from 34 to 43 year-over-year, while crashes on wet surfaces decreased from 17 to 10. The current period saw 13 crashes on snow, ice, or slush, compared to only 1 crash on ice in the prior period, indicating a shift towards more winter-weather related incidents.

Weather

Clear/Clear31 (44.9%)
158.3%prior 12
Clear14 (20.3%)
-17.6%prior 17
Snow/Blowing sand, snow4 (5.8%)
Snow/Snow3 (4.3%)
Snow3 (4.3%)
Cloudy/Rain2 (2.9%)
Cloudy2 (2.9%)
-75.0%prior 8
Rain/Cloudy2 (2.9%)
Snow/Sleet, hail (freezing rain or drizzle)2 (2.9%)
Unknown/Unknown1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight29 (42.0%)
52.6%prior 19
Dark - lighted roadway25 (36.2%)
0.0%prior 25
Dark - roadway not lighted9 (13.0%)
Dark - unknown roadway lighting3 (4.3%)
Dusk2 (2.9%)
Other1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry43 (64.2%)
26.5%prior 34
Wet10 (14.9%)
-41.2%prior 17
Snow8 (11.9%)
Ice3 (4.5%)
Slush2 (3.0%)
Other1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The representation of different vehicle makes saw some shifts, with HONDA vehicles involved in crashes increasing from 11 to 18. The 16-20 age group saw a significant increase in involvement, rising from 1 person in the prior period to 13 persons in the current period. The 26-34 age group also experienced a notable increase, from 28 to 38 persons.

Top Vehicle Makes (134 vehicles)

1
TOYOTA22 (16.4%)
-4.3%prior 23
2
HONDA18 (13.4%)
63.6%prior 11
3
FORD10 (7.5%)
-9.1%prior 11
4
NISSAN8 (6%)
-27.3%prior 11
5
JEEP7 (5.2%)
16.7%prior 6
6
INFI7 (5.2%)
7
CHEVROLET6 (4.5%)
0.0%prior 6
8
MERCEDES-BENZ5 (3.7%)
9
VOLKSWAGEN5 (3.7%)
10
GMC4 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (155 persons with recorded sex)

Male84 (54.2%)
13.5%prior 74
Female71 (45.8%)
54.3%prior 46

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 55 mph speed zones decreased from 18 in December 2023 to 12 in December 2024. There were 2 crashes in 20 mph zones and 3 crashes in 65 mph zones in the current period, categories not present in the prior period's data. The single fatal crash in the prior period occurred in a 55 mph zone, with no fatal crashes recorded in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: MILTON, MA
  • Total crash records analyzed: 69
  • Total persons involved: 170
  • Total vehicles involved: 134

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 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/december-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 — December 2024 | ThatCarHitMe.com