ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILTON, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
718 CRASHES IN
MILTON, MA
2023
In 2023, Milton recorded 718 total traffic crashes, a 1.7% increase from the 706 crashes reported in 2022. While total collisions remained relatively stable, the number of crashes attributed to speeding saw a significant year-over-year increase, rising 95% from 20 incidents in 2022 to 39 in 2023. Total fatalities decreased from 3 to 2, while total injuries rose by 4.4%.
718
▲ 1.7%was 706
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
330
▲ 4.4%was 316
Persons Injured
49
▼ -7.5%was 53
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 25 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash volume in Milton remained stable, with a slight increase of 1.7% from 706 incidents in 2022 to 718 in 2023. While the number of fatalities decreased from 3 to 2, the number of persons injured in crashes increased by 4.4% year-over-year, from 316 to 330.
49
Hit-and-Run Crashes — 2023
▼ -7.5% vs prior (53)
The number of hit-and-run incidents in Milton decreased from 53 in 2022 to 49 in 2023, representing a 7.5% reduction in count. The hit-and-run rate, which measures the number of such incidents per 100 total crashes, also trended downward. The rate fell from 7.5 in 2022 to 6.8 in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
3
Pedestrians Injured
7
Cyclists Injured
318
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Milton showed some consistency and minor shifts between 2022 and 2023. Monday remained the peak day for crashes in both years, with 116 incidents in 2023 compared to 119 in 2022. The peak hour for collisions shifted slightly later in the day, from the 3 PM hour in 2022 (57 crashes) to the 4 PM hour in 2023 (62 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes saw a slight improvement, with the fatal crash rate decreasing from 0.42 per 100 crashes in 2022 to 0.28 in 2023. The number of fatal crashes fell from 3 to 2. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) remained nearly constant, accounting for 32.3% of all crashes in 2023, compared to 31.9% in the prior year. Crashes with no reported injuries constituted 63.9% of the total in 2023, a similar share to 2022's 63.5%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes in Milton remained consistent year-over-year, with 'No improper driving,' 'Followed too closely,' and 'Inattention' as the most cited reasons. However, the counts for several key factors shifted, with crashes attributed to 'Followed too closely' increasing from 109 to 119, and 'Inattention' rising from 61 to 69 incidents. The most significant percentage change in count among major factors was a 34% increase in crashes due to 'Failed to yield right of way,' which grew from 50 to 67. Additionally, crashes related to 'Driving too fast for conditions' more than doubled, from 9 in 2022 to 23 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred during daylight hours on dry roads. In 2023, 59.9% of crashes happened in daylight, compared to 61.3% in 2022. There was a notable increase in crashes occurring on wet road surfaces, which rose from 107 incidents in 2022 to 137 in 2023, a 28% increase. Consequently, the proportion of crashes on dry roads decreased from 80.2% in 2022 to 77.3% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford being the top three in both 2022 and 2023. The number of Toyotas involved increased from 246 to 270, while Fords decreased from 151 to 124. An analysis of persons involved in crashes shows a shift in age demographics, with the representation of individuals aged 65 and older increasing from 6.6% of all persons in 2022 to 8.2% in 2023.
Top Vehicle Makes (1,417 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
117 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,610 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Analysis of crashes by posted speed limit reveals a shift towards higher-speed zones. In 2023, crashes in 55 mph zones increased to 218 from 205 in the previous year, representing 43.0% of all crashes with speed data, up from 37.3% in 2022. Conversely, the number of crashes in 30 mph zones decreased from 148 to 117. In 2023, one fatal crash occurred in a 35 mph zone and another in a 55 mph zone, whereas in 2022, the single fatal crash with speed data occurred in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 92 (1.087%) · 55 mph: 1 of 218 (0.459%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: MILTON, MA
- Total crash records analyzed: 718
- Total persons involved: 1,808
- Total vehicles involved: 1,417
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved