ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FRAMINGHAM, MA · MARCH 2024
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/march-2024-report
Monthly Traffic Safety Analysis
124 CRASHES IN
FRAMINGHAM, MA
MARCH 2024
FRAMINGHAM experienced a significant increase in crash activity in March 2024 compared to March 2023. Total crashes rose from 103 to 124, representing a 20.39% increase. Injuries also saw a substantial rise of 31.25%, from 32 to 42. The most notable year-over-year shift was in hit-and-run crashes, which increased by 41.67% from 12 to 17 incidents.
124
▲ 20.4%was 103
Total Crash Events
0
Persons Killed
42
▲ 31.3%was 32
Persons Injured
17
▲ 41.7%was 12
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 · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a rising number of crashes year-over-year. Total crashes increased by 20.39%, with a corresponding 31.25% rise in total injuries. This suggests an upward trend in crash incidents and their severity.
17
Hit-and-Run Crashes — March 2024
▲ 41.7% vs prior (12)
Hit-and-run crashes increased by 5 incidents, rising from 12 in March 2023 to 17 in March 2024. This represents a 41.67% increase in the count of hit-and-run crashes year-over-year. The hit-and-run rate also increased from 11.7% of total crashes in the prior period to 13.7% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
40
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 Friday with 19 incidents in March 2023 to Thursday with 23 incidents in March 2024. The peak hour for crashes remained consistent at 10 incidents, but shifted from 9 AM in the prior period to 1 PM in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either period. Total injuries increased from 32 to 42, a 31.25% rise year-over-year. Serious injuries (Severity A) increased from 1 to 2, while minor injuries (Severity B) rose from 13 to 18. Possible injuries (Severity C) decreased from 14 to 12.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Failed to yield right of way,' increased by 8 crashes (from 15 to 23), making it the leading factor in the current period. 'No improper driving' crashes decreased by 8 (from 30 to 22). 'Followed too closely' crashes increased by 5 (from 8 to 13), representing a 62.5% increase in count. 'Failure to keep in proper lane or running off road' remained stable with 13 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in wet road conditions significantly increased from 8 in the prior period to 27 in the current period. Clear weather conditions remained dominant, accounting for 78 clear-related crashes in both periods. There was a notable increase in crashes during dark-lighted conditions, rising from 22 to 34. Snow-related conditions were reported in 8 crashes in the prior period but none in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 189 to 232. Toyota remained the most common vehicle make involved, increasing from 40 to 47 vehicles. The age group 0-15 saw a significant increase in persons involved, rising from 4 to 26, while the 21-25 age group also increased from 16 to 26 persons involved.
Top Vehicle Makes (232 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (255 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes with reported speed limits increased from 27 in the prior period to 38 in the current period. Crashes in 25-35 mph zones increased from 14 to 23. Crashes in the 65 mph zone increased from 10 to 12, although the proportion of crashes in this zone slightly decreased from 37.0% to 31.6% of reported speed limit crashes. No fatal crashes were reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-03-01 through 2024-03-31 (31 days)
- Geographic scope: FRAMINGHAM, MA
- Total crash records analyzed: 124
- Total persons involved: 288
- Total vehicles involved: 232
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: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/march-2024-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: 2024-03-01 – 2024-03-31
Generated: June 21, 2026 · All rights reserved