Monthly Traffic Safety Analysis

141 CRASHES IN
FRAMINGHAM, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, FRAMINGHAM experienced 141 crashes, marking a 19.5% increase compared to the 118 crashes recorded in May 2022. A significant positive shift was observed in fatalities, which decreased from 1 in May 2022 to 0 in May 2023. Total injuries also saw an increase, rising from 37 to 42, representing a 13.5% increase year-over-year.

141

19.5%was 118

Total Crash Events

0

-100.0%was 1

Persons Killed

42

13.5%was 37

Persons Injured

20

33.3%was 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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in FRAMINGHAM showed an upward trend year-over-year, increasing from 118 crashes in May 2022 to 141 crashes in May 2023. This represents a 19.5% rise in total crash incidents for the month. Despite the increase in total crashes, there was a notable reduction in fatalities, decreasing from 1 in May 2022 to 0 in May 2023.

20

Hit-and-Run Crashes — May 2023

33.3% vs prior (15)

Hit-and-run crashes increased from 15 in May 2022 to 20 in May 2023, representing a 33.3% increase in count. The hit-and-run rate also trended upwards, rising from 12.7% of all crashes in May 2022 to 14.2% in May 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 2-50.0%

1

Cyclists Injured

Prior: 0%

40

Motorists Injured

Prior: 3514.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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 Tuesday in May 2022 (25 crashes) to Friday, Monday, and Wednesday in May 2023 (each with 24 crashes). The peak hour for crashes also changed, moving from 6 PM in May 2022 (10 crashes) to 5 PM in May 2023 (12 crashes). Crashes on Tuesdays saw a notable decrease from 25 to 10 year-over-year, while crashes on Fridays increased from 11 to 24.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities decreased significantly from 1 in May 2022 to 0 in May 2023, with no fatal crashes reported in the current period compared to 1 in the prior period. Total injuries increased by 5, from 37 to 42. The proportion of crashes resulting in minor injuries decreased from 16.1% (19 crashes) in May 2022 to 9.9% (14 crashes) in May 2023, while possible injuries increased from 7.6% (9 crashes) to 14.2% (20 crashes).

Outcome by Severity (Crash Events)

Minor Injury14minor injury crashes9.9%
-26.3%prior 19
Possible Injury20possible injury crashes14.2%
122.2%prior 9
No Injury101no injury crashes71.6%
31.2%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Followed too closely' saw a substantial increase in count, rising from 12 in May 2022 to 22 in May 2023, an 83.3% change. Similarly, 'Failed to yield right of way' also increased by 10 crashes, from 12 to 22, representing an 83.3% change. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 1 crash to 4 crashes, a 300% change in count, while 'Exceeded authorized speed limit' decreased from 3 crashes to 1 crash, a 66.7% change in count.

Officer-Reported Primary Contributing Cause

No improper driving39 (27.7%)8.3%prior 36
Followed too closely22 (15.6%)83.3%prior 12
Failed to yield right of way22 (15.6%)83.3%prior 12
Failure to keep in proper lane or running off road11 (7.8%)22.2%prior 9
Disregarded traffic signs, signals, road markings10 (7.1%)11.1%prior 9
Inattention5 (3.5%)-28.6%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.8%)
Driving too fast for conditions2 (1.4%)
Other improper action2 (1.4%)
Fatigued/asleep2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions increased from 53 in May 2022 to 72 in May 2023. Crashes in 'Dark - lighted roadway' conditions increased from 16 to 30 year-over-year. The number of crashes on 'Wet' road surfaces increased from 14 in May 2022 to 22 in May 2023, while crashes on 'Dry' road surfaces also increased from 103 to 115.

Weather

Clear/Clear72 (51.8%)
35.8%prior 53
Clear38 (27.3%)
-17.4%prior 46
Rain/Rain7 (5.0%)
Cloudy5 (3.6%)
Cloudy/Rain5 (3.6%)
Rain5 (3.6%)
Cloudy/Clear2 (1.4%)
Unknown/Unknown1 (0.7%)
Clear/Cloudy1 (0.7%)
Cloudy/Cloudy1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight99 (72.8%)
6.5%prior 93
Dark - lighted roadway30 (22.1%)
87.5%prior 16
Dawn2 (1.5%)
Dark - roadway not lighted2 (1.5%)
Dusk2 (1.5%)
Dark - unknown roadway lighting1 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry115 (82.1%)
11.7%prior 103
Wet22 (15.7%)
57.1%prior 14
Reported but invalid3 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 219 in May 2022 to 265 in May 2023, a 20.9% rise. The 21-25 age group saw a significant increase in persons involved in crashes, rising from 27 to 48. Conversely, the 65+ age group experienced a decrease from 33 to 24 persons involved. Toyota remained the top vehicle make involved, though its count slightly decreased from 52 to 51, while Ford increased from 21 to 28.

Top Vehicle Makes (265 vehicles)

1
TOYOTA51 (19.2%)
-1.9%prior 52
2
FORD28 (10.6%)
33.3%prior 21
3
HONDA27 (10.2%)
0.0%prior 27
4
NISSAN16 (6%)
45.5%prior 11
5
CHEVROLET15 (5.7%)
15.4%prior 13
6
SUBARU12 (4.5%)
20.0%prior 10
7
JEEP10 (3.8%)
11.1%prior 9
8
HYUNDAI10 (3.8%)
66.7%prior 6
9
GMC9 (3.4%)
80.0%prior 5
10
BMW8 (3%)
33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (281 persons with recorded sex)

Male156 (55.5%)
13.9%prior 137
Female125 (44.5%)
16.8%prior 107

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased from 12 in May 2022 to 15 in May 2023, with no fatalities reported in these zones in the current period compared to 1 fatality in the prior period. Crashes in 25 mph zones decreased from 8 to 1, and in 30 mph zones from 8 to 4. Overall, the distribution of crashes across various speed zones showed a shift, with fewer crashes in lower speed limit zones and a slight increase in the highest speed limit zone.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: FRAMINGHAM, MA
  • Total crash records analyzed: 141
  • Total persons involved: 321
  • Total vehicles involved: 265

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 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/framingham/may-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 — May 2023 | ThatCarHitMe.com