ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · 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/2022-annual-report
Yearly Traffic Safety Analysis
1,535 CRASHES IN
FRAMINGHAM, MA
2022
In 2022, Framingham recorded 1,535 total traffic crashes, a 6.3% increase from the 1,444 crashes documented in 2021. While overall crash volume saw a modest rise, the most significant year-over-year change was a dramatic increase in the number of people injured, which rose from 56 in 2021 to 446 in 2022. Concurrently, the number of fatalities resulting from these crashes doubled from three to six.
1,535
▲ 6.3%was 1,444
Total Crash Events
6
▲ 100.0%was 3
Persons Killed
446
▲ 696.4%was 56
Persons Injured
203
▼ -15.4%was 240
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 237 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Framingham indicates a rising trend in both the frequency and severity of incidents year-over-year. Total crashes increased by 6.3% from 1,444 in 2021 to 1,535 in 2022. This was accompanied by a doubling of fatalities from 3 to 6 and a nearly seven-fold increase in total injuries from 56 to 446.
203
Hit-and-Run Crashes — 2022
▼ -15.4% vs prior (240)
The frequency of hit-and-run incidents decreased from 2021 to 2022. The total count of hit-and-run crashes fell by 15.4%, from 240 in 2021 to 203 in 2022. Correspondingly, the hit-and-run rate, as a percentage of all crashes, trended downward from 16.6% to 13.2%.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
17
Pedestrians Injured
9
Cyclists Injured
416
Motorists Injured
4
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. While the peak hour for collisions remained the 5 p.m. hour in both 2021 (108 crashes) and 2022 (127 crashes), the peak day for incidents changed. In 2021, Monday was the most common day for crashes with 221 incidents, whereas in 2022, Friday became the peak day with 265 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes escalated significantly from 2021 to 2022. The number of fatal crashes doubled from 3 to 6, and the fatal crash rate increased from 0.21% to 0.39% of all collisions. The proportion of crashes resulting in any level of injury (serious, minor, or possible) saw a substantial rise, increasing from just 2.8% of all crashes in 2021 (40 incidents) to 22.0% in 2022 (337 incidents).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors to crashes remained consistent between 2021 and 2022, with 'No improper driving,' 'Followed too closely,' and 'Failed to yield right of way' as the top three in both years. However, the count for several factors shifted, with incidents attributed to 'Followed too closely' increasing by 12.5% from 176 to 198. Crashes involving 'Disregarded traffic signs, signals, road markings' saw a notable 46.6% increase in count, from 73 incidents in 2021 to 107 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Comparing conditions, a larger number of crashes occurred on dry roads and in clear weather in 2022 than in the prior year. Collisions on dry surfaces increased by 9.3% from 1,118 to 1,222, while crashes on wet roads decreased by 12% from 250 to 220. Similarly, crashes during daylight hours rose from 949 to 1,011, while incidents on dark, lighted roadways were unchanged at 346 for both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—were the same in both 2021 and 2022. The number of Toyotas in collisions increased from 420 to 518. In terms of persons involved, the 26-34 age group remained the largest demographic in both years (655 in 2021 and 666 in 2022). Notably, the number of persons in the 16-20 age group involved in crashes grew by 24.2%, from 285 to 354.
Top Vehicle Makes (2,898 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
334 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,274 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a noticeable shift in the distribution of crashes across different speed zones. Crashes in 30 mph zones decreased by 35.8% from 148 in 2021 to 95 in 2022. Conversely, collisions in 65 mph zones remained stable, with 153 incidents in 2022 compared to 148 in 2021. The number of fatal crashes occurring in 65 mph zones doubled from one to two year-over-year.
Fatal crashes by zone: 25 mph: 1 of 71 (1.408%) · 30 mph: 1 of 95 (1.053%) · 65 mph: 2 of 153 (1.307%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 1,535
- Total persons involved: 3,633
- Total vehicles involved: 2,898
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved