Monthly Traffic Safety Analysis

24 CRASHES IN
FRANKLIN, MA
MAY 2023

All metrics benchmarked againstMay 2022

Total crashes in FRANKLIN, MA increased by 41.2% year-over-year, rising from 17 crashes in May 2022 to 24 crashes in May 2023. This period saw a substantial increase in total injuries, which grew by 300% from 4 to 16. There were no fatalities reported in either period.

24

41.2%was 17

Total Crash Events

0

Persons Killed

16

300.0%was 4

Persons Injured

0

-100.0%was 1

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. 1 crash with unreported severity is 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 crash activity in FRANKLIN, MA showed an upward trend, with total crashes increasing by 41.2% from 17 in May 2022 to 24 in May 2023. Concurrently, the number of total injuries rose significantly by 300%, from 4 to 16. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

15

Motorists Injured

Prior: 4275.0%

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 Monday in May 2022 (5 crashes) to Friday in May 2023 (5 crashes), while Monday crashes remained stable. The peak crash hour also shifted, with 4 PM becoming the peak in May 2023 with 5 crashes, up from 2 crashes at 4 PM in May 2022. Crashes on Sunday decreased from 3 to 1, while Saturday crashes increased from 1 to 3.

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

The severity distribution of crashes shifted year-over-year, with serious injury crashes increasing from 0 in May 2022 to 2 in May 2023. Minor injury crashes also increased, rising from 2 to 5. The proportion of no-injury crashes decreased from 76.5% of total crashes in May 2022 to 58.3% in May 2023.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes8.3%
Minor Injury5minor injury crashes20.8%
150.0%prior 2
Possible Injury2possible injury crashes8.3%
0.0%prior 2
No Injury14no injury crashes58.3%
7.7%prior 13

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 most frequent contributing factor in May 2023 was "No improper driving," increasing by 6 crashes from 4 to 10, and its share rose from 23.5% to 41.7%. Conversely, "Failed to yield right of way" crashes decreased by 2, from 6 to 4, and its share dropped from 35.3% to 16.7%. "Inattention" crashes doubled from 1 to 2, while "Failure to keep in proper lane or running off road" decreased from 2 to 1.

Officer-Reported Primary Contributing Cause

No improper driving10 (41.7%)
Failed to yield right of way4 (16.7%)-33.3%prior 6
Inattention2 (8.3%)
Failure to keep in proper lane or running off road1 (4.2%)
Made an improper turn1 (4.2%)
Followed too closely1 (4.2%)
Operating defective equipment1 (4.2%)
Over-correcting/over-steering1 (4.2%)
Glare1 (4.2%)

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 daylight conditions increased from 14 to 19 year-over-year. The number of crashes on wet road surfaces increased from 1 in May 2022 to 5 in May 2023. Additionally, crashes occurring in 'Dark - lighted roadway' conditions increased from 0 to 3, and new categories like 'Rain/Cloudy', 'Rain/Rain', and 'Rain' appeared, accounting for 5 crashes in May 2023.

Weather

Clear/Clear10 (43.5%)
11.1%prior 9
Clear8 (34.8%)
14.3%prior 7
Rain/Cloudy2 (8.7%)
Rain/Rain2 (8.7%)
Rain1 (4.3%)

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

Lighting

Daylight19 (79.2%)
35.7%prior 14
Dark - lighted roadway3 (12.5%)
Dark - roadway not lighted1 (4.2%)
Dawn1 (4.2%)

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

Road Surface

Dry18 (78.3%)
12.5%prior 16
Wet5 (21.7%)

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

Vehicles & Demographics

Top Vehicle Makes (43 vehicles)

1
HONDA7 (16.3%)
2
TOYOTA7 (16.3%)
0.0%prior 7
3
FORD5 (11.6%)
4
JEEP4 (9.3%)
5
NISSAN3 (7%)
6
KIA3 (7%)
7
GMC2 (4.7%)
8
CHEVROLET2 (4.7%)
9
TT1 (2.3%)
10
AUDI1 (2.3%)

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

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

Sex Distribution (53 persons with recorded sex)

Male29 (54.7%)
31.8%prior 22
Female24 (45.3%)
50.0%prior 16

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 at 30 mph increased by 2, from 4 in May 2022 to 6 in May 2023. Crashes at 40 mph also saw an increase of 4, rising from 2 to 6. Conversely, crashes at 35 mph decreased by 1, from 4 to 3, and a new crash was recorded at 45 mph in May 2023 where none were present in the prior period. No fatalities were reported in any speed zone for either period.

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: FRANKLIN, MA
  • Total crash records analyzed: 24
  • Total persons involved: 55
  • Total vehicles involved: 43

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). "FRANKLIN, 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/franklin/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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Franklin, MA Crash Report — May 2023 | ThatCarHitMe.com