Monthly Traffic Safety Analysis

116 CRASHES IN
FRAMINGHAM, MA
MAY 2024

All metrics benchmarked againstMay 2023

Total crashes in Framingham decreased from 141 in May 2023 to 116 in May 2024, representing a 17.73% reduction. The most notable shift was the increase in the hit-and-run crash rate, which rose from 14.2% to 24.1% of all crashes.

116

-17.7%was 141

Total Crash Events

0

Persons Killed

40

-4.8%was 42

Persons Injured

28

40.0%was 20

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. 7 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Framingham decreased year-over-year, with a 17.73% reduction from 141 crashes in May 2023 to 116 crashes in May 2024. This indicates a falling trend in total crashes for the reported month.

28

Hit-and-Run Crashes — May 2024

40.0% vs prior (20)

Hit-and-run crashes increased from 20 in May 2023 to 28 in May 2024. This resulted in a notable increase in the hit-and-run rate, rising from 14.2% of all crashes in May 2023 to 24.1% in May 2024.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

4

Cyclists Injured

Prior: 1300.0%

35

Motorists Injured

Prior: 40-12.5%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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 24 crashes in May 2023 to Thursday with 21 crashes in May 2024. The peak hour for crashes also shifted from 5 PM with 12 crashes in May 2023 to 7 PM with 11 crashes in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both periods reported zero fatal crashes and zero fatalities. While total injuries decreased slightly from 42 in May 2023 to 40 in May 2024, serious injuries increased from 0 to 3. The proportion of crashes resulting in minor injury increased from 9.9% to 15.5%, and possible injury decreased from 14.2% to 9.5%.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes2.6%
Minor Injury18minor injury crashes15.5%
28.6%prior 14
Possible Injury11possible injury crashes9.5%
-45.0%prior 20
No Injury77no injury crashes66.4%
-23.8%prior 101

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Failed to yield right of way' decreased from 22 to 10, and 'Disregarded traffic signs, signals, road markings' decreased from 10 to 2. Conversely, crashes due to 'Driving too fast for conditions' increased from 2 to 5, and 'Inattention' crashes rose from 5 to 7.

Officer-Reported Primary Contributing Cause

No improper driving38 (32.8%)-2.6%prior 39
Followed too closely17 (14.7%)-22.7%prior 22
Failed to yield right of way10 (8.6%)-54.5%prior 22
Inattention7 (6%)40.0%prior 5
Failure to keep in proper lane or running off road5 (4.3%)-54.5%prior 11
Driving too fast for conditions5 (4.3%)
Other improper action4 (3.4%)
Made an improper turn3 (2.6%)
Disregarded traffic signs, signals, road markings2 (1.7%)-80.0%prior 10
Distracted2 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions (Clear/Clear, Clear, Clear/Cloudy, Cloudy/Clear) decreased from 113 in May 2023 to 94 in May 2024. Similarly, crashes on dry road surfaces decreased from 115 to 99, and crashes during daylight hours decreased from 99 to 85.

Weather

Clear/Clear60 (52.2%)
-16.7%prior 72
Clear29 (25.2%)
-23.7%prior 38
Rain7 (6.1%)
40.0%prior 5
Rain/Rain5 (4.3%)
-28.6%prior 7
Clear/Cloudy5 (4.3%)
Cloudy5 (4.3%)
0.0%prior 5
Cloudy/Cloudy2 (1.7%)
Cloudy/Rain2 (1.7%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight85 (73.3%)
-14.1%prior 99
Dark - lighted roadway19 (16.4%)
-36.7%prior 30
Dark - roadway not lighted4 (3.4%)
Dusk4 (3.4%)
Dawn3 (2.6%)
Dark - unknown roadway lighting1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry99 (85.3%)
-13.9%prior 115
Wet16 (13.8%)
-27.3%prior 22
Reported but invalid1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 321 to 257 year-over-year. The 26-34 age group saw a decrease from 62 to 42 persons, and the 21-25 age group decreased from 48 to 23 persons. Toyota remained the most frequently involved vehicle make, though its count decreased from 51 to 37.

Top Vehicle Makes (216 vehicles)

1
TOYOTA37 (17.1%)
-27.5%prior 51
2
HONDA30 (13.9%)
11.1%prior 27
3
FORD25 (11.6%)
-10.7%prior 28
4
CHEVROLET14 (6.5%)
-6.7%prior 15
5
NISSAN14 (6.5%)
-12.5%prior 16
6
HYUNDAI10 (4.6%)
0.0%prior 10
7
SUBARU7 (3.2%)
-41.7%prior 12
8
MAZDA6 (2.8%)
9
LEXUS6 (2.8%)
10
JEEP5 (2.3%)
-50.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

50 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (201 persons with recorded sex)

Male113 (56.2%)
-27.6%prior 156
Female88 (43.8%)
-29.6%prior 125

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes on roads with a 65 MPH speed limit increased from 15 in May 2023 to 18 in May 2024. Crashes at 25 MPH increased from 1 to 4, while crashes at 30 MPH decreased from 4 to 3. There were no fatal crashes reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: FRAMINGHAM, MA
  • Total crash records analyzed: 116
  • Total persons involved: 257
  • Total vehicles involved: 216

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: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/may-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

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Framingham, MA Crash Report — May 2024 | ThatCarHitMe.com