Monthly Traffic Safety Analysis

17 CRASHES IN
FRANKLIN, MA
MAY 2022

All metrics benchmarked againstMay 2021

In May 2022, FRANKLIN experienced 17 total crashes, a decrease from 19 crashes reported in May 2021, representing a 10.5% reduction. This period also saw a notable decrease in total injuries, falling from 6 in May 2021 to 4 in May 2022, including the elimination of serious injuries. The number of DUI and speeding-related crashes also dropped to zero in May 2022.

17

-10.5%was 19

Total Crash Events

0

Persons Killed

4

-33.3%was 6

Persons Injured

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for FRANKLIN in May 2022 indicates a decrease in crash activity compared to May 2021. Total crashes declined by 10.5%, from 19 to 17, and total injuries decreased by 33.3%, from 6 to 4, suggesting an improvement in road safety for the month.

1

Hit-and-Run Crashes — May 2022

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both May 2021 and May 2022. Despite the overall decrease in total crashes, the hit-and-run rate slightly increased from 5.3% in May 2021 to 5.9% in May 2022.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 6-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in FRANKLIN shifted year-over-year. The peak day for crashes moved from Saturday in May 2021 (4 crashes) to Monday in May 2022 (5 crashes). Similarly, the peak hour for crashes changed from 9 AM in May 2021 (3 crashes) to 12 PM in May 2022 (3 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities and fatal crashes remained at zero in both May 2021 and May 2022. The most significant change in crash severity was the absence of serious injuries (Severity A) in May 2022, which had accounted for 1 crash (5.3% of total crashes) in May 2021. The proportion of no-injury crashes increased from 68.4% in May 2021 to 76.5% in May 2022, while minor injuries decreased from 3 to 2.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes11.8%
-33.3%prior 3
Possible Injury2possible injury crashes11.8%
0.0%prior 2
No Injury13no injury crashes76.5%
0.0%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Failed to yield right of way' saw a 200% increase in count, rising from 2 crashes in May 2021 to 6 crashes in May 2022, becoming the most frequent factor. 'No improper driving' also increased from 2 crashes to 4 crashes, a 100% rise in count. Conversely, factors like 'Distracted' and 'Disregarded traffic signs, signals, road markings,' which each contributed to 2 crashes in the prior period, were not reported in the current period's top factors.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (35.3%)
No improper driving4 (23.5%)
Failure to keep in proper lane or running off road2 (11.8%)
Inattention1 (5.9%)
Other improper action1 (5.9%)
Reported but invalid1 (5.9%)
Fatigued/asleep1 (5.9%)
Glare1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year, with the majority of incidents occurring in clear weather, daylight, and on dry road surfaces. Crashes occurring in 'Dark - roadway not lighted' conditions decreased from 3 in May 2021 to 1 in May 2022. The number of crashes on wet road surfaces remained constant at 1 in both periods.

Weather

Clear/Clear9 (52.9%)
28.6%prior 7
Clear7 (41.2%)
-36.4%prior 11
Cloudy1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Lighting

Daylight14 (82.4%)
0.0%prior 14
Dark - roadway not lighted1 (5.9%)
Dark - unknown roadway lighting1 (5.9%)
Dusk1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry16 (94.1%)
-11.1%prior 18
Wet1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (31 vehicles)

1
TOYOTA7 (22.6%)
16.7%prior 6
2
CHEVROLET3 (9.7%)
3
FORD2 (6.5%)
-66.7%prior 6
4
JEEP2 (6.5%)
5
NISSAN2 (6.5%)
6
HONDA2 (6.5%)
7
HYUNDAI2 (6.5%)
8
OLDSMOBILE1 (3.2%)
9
SUBARU1 (3.2%)
10
VOLKSWAGEN1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records

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

Sex Distribution (38 persons with recorded sex)

Male22 (57.9%)
15.8%prior 19
Female16 (42.1%)
-5.9%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events

Speed Limit Zones

There were shifts in crash distribution across speed zones; crashes in 30 mph zones decreased from 6 to 4, and 65 mph zones saw a reduction from 5 to 3 crashes. Conversely, crashes in 35 mph zones doubled from 2 in May 2021 to 4 in May 2022. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: FRANKLIN, MA
  • Total crash records analyzed: 17
  • Total persons involved: 39
  • Total vehicles involved: 31

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 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/franklin/may-2022-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 2022 | ThatCarHitMe.com