Monthly Traffic Safety Analysis

118 CRASHES IN
FRAMINGHAM, MA
DECEMBER 2023

All metrics benchmarked againstDecember 2022

Total crashes in FRAMINGHAM, MA decreased by 22.9% year-over-year, falling from 153 in December 2022 to 118 in December 2023. This significant reduction in overall crash incidents is the most notable shift between the two periods. Fatal crashes remained at zero for both months.

118

-22.9%was 153

Total Crash Events

0

Persons Killed

34

-39.3%was 56

Persons Injured

15

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in FRAMINGHAM, MA showed a notable downward trend from December 2022 to December 2023. The total number of crashes decreased by 22.9%, from 153 to 118. This indicates a significant reduction in traffic incidents for the specified month.

15

Hit-and-Run Crashes — December 2023

0.0% vs prior (15)

The number of hit-and-run crashes remained constant at 15 for both December 2022 and December 2023. However, due to a decrease in overall total crashes, the hit-and-run rate increased from 9.8% in the prior period to 12.7% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Cyclists Injured

Prior: 1100.0%

32

Motorists Injured

Prior: 51-37.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Both December 2022 and December 2023 identified Friday as the peak day for crashes, with counts of 35 and 25 respectively. The peak hour for crashes also remained consistent at 5 PM for both periods, recording 16 crashes in December 2022 and 15 in December 2023. While peak patterns held steady, the overall volume of crashes during these times decreased year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both December 2022 and December 2023. Total injuries decreased significantly from 56 in the prior period to 34 in the current period, representing a 39.3% reduction. The proportion of 'No Injury' crashes increased from 68.6% in December 2022 to 73.7% in December 2023, while 'Serious Injury' crashes (code A) were reported in the prior period (2 crashes, 1.3%) but not in the current period.

Outcome by Severity (Crash Events)

Minor Injury13minor injury crashes11%
-18.8%prior 16
Possible Injury16possible injury crashes13.6%
-33.3%prior 24
No Injury87no injury crashes73.7%
-17.1%prior 105

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Followed too closely' decreased from 23 in December 2022 to 15 in December 2023, a 34.8% reduction in count. Similarly, 'Failed to yield right of way' crashes decreased from 15 to 11, a 26.7% reduction. The count for 'No improper driving' remained stable at 39 crashes for both periods.

Officer-Reported Primary Contributing Cause

No improper driving39 (33.1%)0.0%prior 39
Followed too closely15 (12.7%)-34.8%prior 23
Failed to yield right of way11 (9.3%)-26.7%prior 15
Failure to keep in proper lane or running off road10 (8.5%)0.0%prior 10
Disregarded traffic signs, signals, road markings8 (6.8%)-11.1%prior 9
Inattention6 (5.1%)0.0%prior 6
Other improper action5 (4.2%)
Driving too fast for conditions3 (2.5%)-50.0%prior 6
Made an improper turn2 (1.7%)
Wrong side or wrong way2 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on 'Dry' road surfaces decreased from 104 in December 2022 to 79 in December 2023. Crashes in 'Daylight' conditions also saw a reduction from 78 to 61, and those in 'Dark - lighted roadway' decreased from 55 to 47. The share of crashes occurring in 'Clear/Clear' weather increased from 31.4% in the prior year to 47.5% in the current year, despite the overall decrease in total crashes.

Weather

Clear/Clear56 (47.5%)
16.7%prior 48
Clear23 (19.5%)
-42.5%prior 40
Rain/Rain13 (11.0%)
-7.1%prior 14
Rain8 (6.8%)
-42.9%prior 14
Cloudy/Cloudy6 (5.1%)
-50.0%prior 12
Cloudy3 (2.5%)
-62.5%prior 8
Cloudy/Rain2 (1.7%)
Rain/Cloudy2 (1.7%)
Cloudy/Clear2 (1.7%)
Rain/Sleet, hail (freezing rain or drizzle)1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight61 (51.7%)
-21.8%prior 78
Dark - lighted roadway47 (39.8%)
-14.5%prior 55
Dark - roadway not lighted3 (2.5%)
-66.7%prior 9
Dusk3 (2.5%)
Dark - unknown roadway lighting2 (1.7%)
Dawn2 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry79 (66.9%)
-24.0%prior 104
Wet35 (29.7%)
-5.4%prior 37
Ice2 (1.7%)
Other1 (0.8%)
Slush1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 298 in December 2022 to 216 in December 2023. Toyota remained the most frequent vehicle make involved in crashes, though its count decreased from 56 to 39 year-over-year. The 26-34 age group continued to represent the highest number of persons involved in crashes, with counts decreasing from 65 to 54.

Top Vehicle Makes (216 vehicles)

1
TOYOTA39 (18.1%)
-30.4%prior 56
2
FORD27 (12.5%)
-10.0%prior 30
3
HONDA23 (10.6%)
-48.9%prior 45
4
CHEVROLET17 (7.9%)
-15.0%prior 20
5
NISSAN10 (4.6%)
-47.4%prior 19
6
MERCEDES-BENZ9 (4.2%)
80.0%prior 5
7
SUBARU8 (3.7%)
14.3%prior 7
8
HYUNDAI8 (3.7%)
-11.1%prior 9
9
VOLKSWAGEN7 (3.2%)
40.0%prior 5
10
AUDI5 (2.3%)
0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (231 persons with recorded sex)

Male144 (62.3%)
-21.7%prior 184
Female87 (37.7%)
-48.5%prior 169

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes reported in 25 MPH speed zones decreased from 10 in December 2022 to 3 in December 2023, marking a 70% reduction. Crashes in 65 MPH zones also saw a decrease, falling from 15 to 8. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-12-01 through 2023-12-31 (31 days)
  • Geographic scope: FRAMINGHAM, MA
  • Total crash records analyzed: 118
  • Total persons involved: 260
  • 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: December 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/december-2023-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 — December 2023 | ThatCarHitMe.com