ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EASTON, MA · SEPTEMBER 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/easton/september-2022-report
Monthly Traffic Safety Analysis
49 CRASHES IN
EASTON, MA
SEPTEMBER 2022
The current period (September 2022) recorded 49 crashes, a 4.26% increase from the 47 crashes in the prior period (September 2021). Total injuries rose substantially by 300%, from 4 injuries in September 2021 to 16 injuries in September 2022. Notably, the current period saw 1 serious injury, 2 speeding-related crashes, and 1 bicycle-involved crash, none of which were reported in the prior period.
49
▲ 4.3%was 47
Total Crash Events
0
Persons Killed
16
▲ 300.0%was 4
Persons Injured
1
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash counts remained relatively stable, with a slight increase of 4.26% year-over-year from 47 to 49 crashes. However, total injuries saw a substantial increase of 300%, rising from 4 injuries in September 2021 to 16 injuries in September 2022. Fatalities remained at zero for both periods.
1
Hit-and-Run Crashes — September 2022
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained stable at 1 for both the current and prior periods. The hit-and-run crash rate saw a slight decrease from 2.1% in the prior period to 2% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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 Wednesday with 13 crashes in the prior period to Thursday with 12 crashes in the current period. The peak hour for crashes also changed, moving from 2 PM with 9 crashes in the prior period to 4 PM with 7 crashes in the current period. This indicates a shift in the most frequent crash times and days year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While both periods reported zero fatalities, the injury landscape changed significantly. The current period saw 1 serious injury, which was not present in the prior period. Minor injuries increased from 2 in the prior period to 9 in the current period, and possible injuries increased from 2 to 3. Consequently, the proportion of crashes resulting in no injuries decreased from 87.2% to 69.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record
Top Contributing Factors
Among common contributing factors, "Failed to yield right of way" decreased from 13 crashes in the prior period to 9 crashes in the current period, a 30.8% decrease in count. "No improper driving" remained constant at 9 crashes for both periods, while "Followed too closely" increased by 1 crash, from 3 to 4. The current period also reported "Failure to keep in proper lane or running off road" with 7 crashes and "Exceeded authorized speed limit" with 1 crash, which were not among the listed contributing factors in the prior period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather decreased from 40 in the prior period to 35 in the current period, while those in "Cloudy" conditions increased from 4 to 8 crashes. Crashes on "Wet" road surfaces increased from 4 in the prior period to 7 in the current period. Regarding lighting, crashes during "Dark - lighted roadway" conditions decreased from 10 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved decreased from 86 in the prior period to 81 in the current period. Among vehicle makes, TOYOTA saw an increase from 11 to 18 vehicles, while FORD decreased from 15 to 6 vehicles. A notable shift occurred in the age distribution of persons involved, with the 65+ age group increasing significantly from 8 persons in the prior period to 19 persons in the current period.
Top Vehicle Makes (81 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (95 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones increased from 11 to 13, and in 40 mph zones from 16 to 19. Conversely, crashes in 35 mph zones decreased from 11 to 7, and in 45 mph zones from 5 to 1. There were no reported fatalities in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-09-01 through 2022-09-30 (30 days)
- Geographic scope: EASTON, MA
- Total crash records analyzed: 49
- Total persons involved: 100
- Total vehicles involved: 81
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). "EASTON, MA Crash Intelligence Report: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/easton/september-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: 2022-09-01 – 2022-09-30
Generated: June 21, 2026 · All rights reserved