ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILTON, MA · AUGUST 2022
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/august-2022-report
Monthly Traffic Safety Analysis
66 CRASHES IN
MILTON, MA
AUGUST 2022
Total crashes in Milton for August 2022 were 66, an increase from 63 crashes in August 2021, representing a 4.8% rise. The total number of injured persons also increased by 16.1%, from 31 to 36. A notable shift was the increase in crashes attributed to "Inattention," which rose from 2 to 9 incidents year-over-year.
66
▲ 4.8%was 63
Total Crash Events
0
Persons Killed
36
▲ 16.1%was 31
Persons Injured
3
▲ 50.0%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 · 2022-08-01 to 2022-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Milton showed an upward trend year-over-year, with total crashes increasing by 4.8%, from 63 in August 2021 to 66 in August 2022. Concurrently, the total number of injured persons increased by 16.1%, rising from 31 to 36. There were no fatal crashes in either period.
3
Hit-and-Run Crashes — August 2022
▲ 50.0% vs prior (2)
Hit-and-run crashes increased from 2 in August 2021 to 3 in August 2022. This resulted in an increase in the hit-and-run rate from 3.2% to 4.5% of all crashes. The data indicates an upward trend in both the count and rate of hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
36
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted significantly year-over-year. In August 2022, the peak day for crashes was Saturday with 15 incidents, a substantial increase from 4 on Saturdays in August 2021, which had Thursday as its peak day with 15 crashes. The peak hour for crashes also shifted from 3 PM in August 2021 (7 crashes) to 4 PM in August 2022 (7 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both August 2021 and August 2022. The number of crashes resulting in serious injury increased from 0 to 1, while minor injury crashes slightly rose from 14 to 15. Conversely, crashes involving possible injuries decreased from 12 to 5 year-over-year, and crashes with no reported injuries increased from 34 to 41.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Most severe injury per crash record
Top Contributing Factors
The distribution of contributing factors saw several shifts. Crashes attributed to "No improper driving" decreased from 25 to 13, while "Followed too closely" increased from 8 to 11 incidents. "Inattention" crashes rose significantly from 2 to 9, and "Failed to yield right of way" increased from 3 to 5 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 41 in August 2021 to 58 in August 2022. Conversely, crashes during rainy conditions decreased from 17 to 4 incidents year-over-year. The number of crashes on dry road surfaces increased from 44 to 60, while those on wet surfaces decreased from 18 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 112 in August 2021 to 123 in August 2022. The age group of 65+ experienced the largest increase in persons involved, rising from 6 to 12. Toyota became the most frequently involved make in August 2022 with 23 vehicles, surpassing Honda which had 18 in August 2021.
Top Vehicle Makes (123 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (144 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones decreased from 20 to 16, and 55 mph zones also saw a decrease from 21 to 18 crashes. Conversely, crashes in 35 mph zones increased from 8 to 11, and 40 mph zones increased from 1 to 3 incidents. There were no fatal crashes reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-08-01 to 2022-08-31 · 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: 2022-08-01 through 2022-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-08-01 through 2022-08-31 (31 days)
- Geographic scope: MILTON, MA
- Total crash records analyzed: 66
- Total persons involved: 159
- Total vehicles involved: 123
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: August 2022." Published June 21, 2026. Reporting period: 2022-08-01 to 2022-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/august-2022-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: 2022-08-01 – 2022-08-31
Generated: June 21, 2026 · All rights reserved