ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MILTON, MA · OCTOBER 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/october-2022-report
Monthly Traffic Safety Analysis
53 CRASHES IN
MILTON, MA
OCTOBER 2022
In October 2022, MILTON experienced a notable decrease in overall crash incidents compared to October 2021. Total crashes fell by 22, from 75 to 53, representing a 29.3% reduction year-over-year. A significant positive shift was observed in hit-and-run incidents, which decreased from 8 crashes in the prior period to just 1 in the current period.
53
▼ -29.3%was 75
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
21
▼ -12.5%was 24
Persons Injured
1
▼ -87.5%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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in MILTON shows a significant decline year-over-year, with total incidents dropping from 75 in October 2021 to 53 in October 2022. This represents a 29.3% decrease in crashes. Fatalities also decreased from 1 to 0, and total injuries saw a modest reduction from 24 to 21.
1
Hit-and-Run Crashes — October 2022
▼ -87.5% vs prior (8)
Hit-and-run incidents significantly decreased in October 2022 compared to the prior year. The number of hit-and-run crashes dropped from 8 to 1. Consequently, the hit-and-run rate fell from 10.7% of all crashes in October 2021 to 1.9% in October 2022, indicating a downward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
1
Cyclists Injured
18
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns shifted year-over-year, with the peak day for crashes moving from Wednesday in October 2021 (14 crashes) to Sunday in October 2022 (11 crashes). The peak hour also changed, occurring at 8 PM in October 2021 with 7 crashes, and at 5 PM in October 2022 with 6 crashes. This indicates a shift in high-frequency crash times and days.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a positive shift, with zero fatalities reported in October 2022 compared to 1 fatality in October 2021, resulting in a fatal crash rate decrease from 1.3% to 0%. Total injuries also decreased from 24 to 21 year-over-year. While minor injury crashes (severity B) increased from 7 (9.3% share) to 11 (20.8% share), possible injury crashes (severity C) decreased from 11 (14.7% share) to 4 (7.5% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors showed notable shifts year-over-year. 'No improper driving' decreased from 28 crashes in October 2021 to 11 crashes in October 2022, a 60.7% decrease in count, and its share fell from 37.3% to 20.8%. Conversely, 'Followed too closely' incidents increased significantly from 3 to 10 crashes, representing a 233.3% increase in count, and its share rose from 4% to 18.9%, moving it to the second most frequent factor. 'Failed to yield right of way' also decreased from 10 crashes to 4 crashes, a 60% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions (Clear or Clear/Clear) decreased in count from 51 in October 2021 to 40 in October 2022, but their proportion of total crashes increased from 68% to 75.5%. Conversely, crashes in rainy conditions (various rain-related conditions) decreased in count from 19 to 5, and their proportion of total crashes fell from 25.3% to 9.4%. Crashes occurring during daylight hours increased proportionally from 46.7% to 62.3% of total crashes, while crashes in 'Dark - lighted roadway' conditions decreased from 34 to 17. The proportion of crashes on dry road surfaces increased from 72% to 83%, with wet road crashes decreasing from 21 to 9.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field
Vehicles & Demographics
The composition of top vehicle makes involved in crashes shifted year-over-year. Honda, the top make in October 2021 with 21 vehicles, saw a decrease to 12 vehicles, moving it to third place. Toyota became the most frequently involved make in October 2022 with 15 vehicles, a slight decrease from 16 in the prior year. Chevrolet vehicles involved in crashes increased from 10 to 13, moving it up in the rankings.
Top Vehicle Makes (110 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (126 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events
Speed Limit Zones
The total number of crashes with recorded speed limits decreased from 59 in October 2021 to 44 in October 2022. Crashes in 30 mph zones decreased from 15 to 8, and in 55 mph zones from 22 to 20. There was one fatal crash in a 40 mph zone in October 2021, while no fatal crashes occurred in any speed zone in October 2022. A new crash was recorded in a 65 mph zone in the current period, which was not present in the prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-10-01 through 2022-10-31 (31 days)
- Geographic scope: MILTON, MA
- Total crash records analyzed: 53
- Total persons involved: 134
- Total vehicles involved: 110
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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/october-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: 2022-10-01 – 2022-10-31
Generated: June 21, 2026 · All rights reserved