Yearly Traffic Safety Analysis

1,392 CRASHES IN
FRAMINGHAM, MA
2024

All metrics benchmarked against2023

In 2024, Framingham recorded 1,392 total traffic crashes, a 2.5% decrease from the 1,427 crashes reported in 2023. While the overall crash volume declined slightly, the number of fatalities increased from zero in the prior period to three in the current period. This increase in fatal outcomes, along with a 55.6% rise in serious injury crashes, represents the most significant year-over-year shift in the data.

1,392

-2.5%was 1,427

Total Crash Events

3

Persons Killed

426

-0.7%was 429

Persons Injured

232

-1.3%was 235

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 65 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Framingham saw a slight year-over-year decrease of 2.5%, falling from 1,427 in 2023 to 1,392 in 2024. Despite this drop in total incidents, the number of people killed in crashes rose from zero to three. The total number of injuries remained relatively stable, decreasing by just 0.7% from 429 to 426.

232

Hit-and-Run Crashes — 2024

-1.3% vs prior (235)

The number of hit-and-run incidents remained stable, with 232 crashes reported in 2024 compared to 235 in 2023, a decrease of just three incidents. The hit-and-run rate, expressed as a percentage of total crashes, saw a slight increase from 16.5% to 16.7%. This indicates that while the absolute number of hit-and-runs slightly decreased, they constituted a slightly larger proportion of all crashes in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

18

Pedestrians Injured

Prior: 1520.0%

18

Cyclists Injured

Prior: 1612.5%

384

Motorists Injured

Prior: 394-2.5%

6

Other Injured

Prior: 450.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Friday with 213 incidents, a change from 2023 when Tuesday was the peak day with 243 incidents. The peak hour also moved later in the day, from 1 p.m. in the prior period (103 crashes) to the 5 p.m. evening commute hour in the current period (110 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened year-over-year, with the number of fatal crashes increasing from zero in 2023 to three in 2024. The count of crashes resulting in serious injuries also rose by 55.6%, from 18 to 28 incidents. Consequently, the proportion of crashes involving any injury (fatal, serious, minor, or possible) was nearly identical, comprising 28.3% of crashes in the current period versus 27.7% in the prior period.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.2%
Serious Injury28serious injury crashes2%
55.6%prior 18
Minor Injury176minor injury crashes12.6%
4.8%prior 168
Possible Injury122possible injury crashes8.8%
-15.9%prior 145
No Injury998no injury crashes71.7%
-3.3%prior 1,032

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

While 'Failed to yield right of way' and 'Followed too closely' remained the top two reported driver-related factors in both periods, their counts saw modest increases. Notably, the count of crashes attributed to 'Exceeded authorized speed limit' tripled, increasing by 200% from 8 incidents in 2023 to 24 in 2024. Crashes involving 'Driving too fast for conditions' also saw a significant 25% increase in count, from 44 to 55. Conversely, crashes related to 'Failure to keep in proper lane' decreased in count by 22.7%, from 110 to 85.

Officer-Reported Primary Contributing Cause

No improper driving370 (26.6%)-11.3%prior 417
Failed to yield right of way186 (13.4%)2.2%prior 182
Followed too closely182 (13.1%)5.8%prior 172
Failure to keep in proper lane or running off road85 (6.1%)-22.7%prior 110
Disregarded traffic signs, signals, road markings82 (5.9%)9.3%prior 75
Inattention62 (4.5%)8.8%prior 57
Driving too fast for conditions55 (4%)25.0%prior 44
Other improper action28 (2%)-46.2%prior 52
Made an improper turn27 (1.9%)-15.6%prior 32
Exceeded authorized speed limit24 (1.7%)200.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes by lighting conditions remained largely unchanged year-over-year, with about two-thirds of incidents occurring in daylight in both periods. However, there was a notable shift in road surface conditions. The number of crashes on wet roads decreased by 38.9%, from 293 in 2023 to 179 in 2024. Conversely, crashes on snow or ice increased by 37.8%, from 37 incidents in the prior year to 51 in the current year.

Weather

Clear/Clear684 (49.4%)
5.9%prior 646
Clear353 (25.5%)
-1.7%prior 359
Cloudy62 (4.5%)
-3.1%prior 64
Rain/Rain58 (4.2%)
-38.3%prior 94
Cloudy/Cloudy53 (3.8%)
39.5%prior 38
Rain44 (3.2%)
-33.3%prior 66
Clear/Cloudy23 (1.7%)
76.9%prior 13
Cloudy/Rain15 (1.1%)
-40.0%prior 25
Snow14 (1.0%)
75.0%prior 8
Snow/Snow13 (0.9%)
0.0%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight897 (65.3%)
-4.9%prior 943
Dark - lighted roadway354 (25.8%)
-2.2%prior 362
Dark - roadway not lighted49 (3.6%)
63.3%prior 30
Dusk43 (3.1%)
7.5%prior 40
Dawn24 (1.7%)
9.1%prior 22
Dark - unknown roadway lighting4 (0.3%)
-50.0%prior 8
Other3 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,140 (82.4%)
6.1%prior 1,074
Wet179 (12.9%)
-38.9%prior 293
Snow33 (2.4%)
17.9%prior 28
Ice18 (1.3%)
100.0%prior 9
Reported but invalid7 (0.5%)
-50.0%prior 14
Slush6 (0.4%)
Water (standing, moving)1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes remained consistent across both years: Toyota, Honda, Ford, Nissan, and Chevrolet, with only a minor change in ranking between Nissan and Chevrolet. The number of Toyotas involved in crashes increased from 484 to 518, while Fords decreased from 304 to 285. The age distribution of persons involved in crashes also showed stability, with the 26-34 age group being the largest in both periods, followed by the 35-44 age group.

Top Vehicle Makes (2,654 vehicles)

1
TOYOTA518 (19.5%)
7.0%prior 484
2
HONDA340 (12.8%)
3.0%prior 330
3
FORD285 (10.7%)
-6.3%prior 304
4
NISSAN151 (5.7%)
3.4%prior 146
5
CHEVROLET150 (5.7%)
-2.0%prior 153
6
HYUNDAI103 (3.9%)
8.4%prior 95
7
SUBARU101 (3.8%)
4.1%prior 97
8
JEEP94 (3.5%)
-11.3%prior 106
9
KIA58 (2.2%)
0.0%prior 58
10
MAZDA58 (2.2%)
7.4%prior 54

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (2,768 persons with recorded sex)

Male1,618 (58.5%)
-0.1%prior 1,619
Female1,149 (41.5%)
-3.7%prior 1,193
X / Unspecified1 (0.0%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Year-over-year, there was an increase in crashes occurring in 65 mph zones, rising from 141 to 160 incidents. Crashes in 25 mph zones also increased from 41 to 65. In contrast, crashes in 30 mph zones decreased from 66 to 56. While 2023 saw no fatalities in areas with a recorded speed limit, one of the three fatalities in 2024 occurred in a 35 mph zone.

Fatal crashes by zone: 35 mph: 1 of 24 (4.167%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: FRAMINGHAM, MA
  • Total crash records analyzed: 1,392
  • Total persons involved: 3,219
  • Total vehicles involved: 2,654

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/2024-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

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Framingham, MA Crash Report — 2024 | ThatCarHitMe.com