ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · APRIL 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/framingham/april-2022-report
Monthly Traffic Safety Analysis
113 CRASHES IN
FRAMINGHAM, MA
APRIL 2022
In April 2022, FRAMINGHAM experienced 113 crashes, a 28.4% increase from the 88 crashes recorded in April 2021. The most significant year-over-year shift was in total injuries, which surged from 2 in April 2021 to 29 in April 2022, representing a 1350% increase. Fatalities remained at 0 in both periods.
113
▲ 28.4%was 88
Total Crash Events
0
Persons Killed
29
▲ 1350.0%was 2
Persons Injured
20
▲ 81.8%was 11
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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in FRAMINGHAM trended upwards year-over-year, with total crashes increasing by 28.4% from 88 to 113. This rise was accompanied by a substantial 1350% increase in total injuries, from 2 to 29. Fatalities remained unchanged at zero for both periods.
20
Hit-and-Run Crashes — April 2022
▲ 81.8% vs prior (11)
Hit-and-run crashes increased by 9 incidents, rising from 11 in April 2021 to 20 in April 2022, an 81.8% increase. The hit-and-run rate also increased from 12.5% to 17.7% of all crashes, an increase of 5.2 percentage points.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
27
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Monday (16 crashes) in April 2021 to Friday (27 crashes) in April 2022. Similarly, the peak hour changed from 3 PM (10 crashes) in April 2021 to 5 PM (12 crashes) in April 2022. Crashes on Fridays more than doubled, increasing by 107.7% from 13 to 27.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at 0 in both April 2021 and April 2022. However, total injuries saw a significant increase of 1350%, rising from 2 to 29. Notably, serious injuries (Severity A) and possible injuries (Severity C) were reported in April 2022 with 2 and 16 incidents respectively, while none were recorded in April 2021.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record
Top Contributing Factors
Among common contributing factors, 'No improper driving' increased by 13 incidents (48.1%) from 27 to 40. 'Failure to keep in proper lane or running off road' saw a substantial increase of 6 incidents (600%), rising from 1 to 7. Conversely, 'Distracted' driving incidents decreased by 3 (75%) from 4 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under 'Dry' road surface conditions increased by 31 incidents, rising from 63 to 94. Conversely, crashes on 'Wet' road surfaces decreased by 7 incidents, from 22 to 15. The number of crashes in 'Daylight' conditions increased by 15, from 68 to 83.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 41 (24.1%), from 170 to 211. Toyota vehicles involved increased by 15 (51.7%) from 29 to 44, while Honda vehicles decreased by 6 (23.1%) from 26 to 20. The 26-34 age group saw an increase of 13 persons involved in crashes, from 33 to 46, while the 35-44 age group decreased by 15 persons, from 42 to 27.
Top Vehicle Makes (211 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records
39 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (241 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones increased by 6 incidents (75%), rising from 8 to 14. Conversely, crashes in 65 mph speed zones decreased by 4 incidents (44.4%), from 9 to 5. Crashes in 45 mph zones also decreased by 3 incidents (75%), from 4 to 1.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-04-01 through 2022-04-30 (30 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 113
- Total persons involved: 274
- Total vehicles involved: 211
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). "FRAMINGHAM, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/april-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: 2022-04-01 – 2022-04-30
Generated: June 21, 2026 · All rights reserved