Monthly Traffic Safety Analysis

30 CRASHES IN
FRANKLIN, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In March 2022, FRANKLIN experienced 30 total crashes, a substantial increase of 114.29% compared to the 14 crashes recorded in March 2021. The number of total injuries also rose significantly, from 2 in the prior period to 8 in the current period. This represents a notable escalation in crash activity year-over-year.

30

114.3%was 14

Total Crash Events

0

Persons Killed

8

300.0%was 2

Persons Injured

0

Fatal Crash Events

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 · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for March in FRANKLIN shows a rising trend year-over-year, with total crashes increasing from 14 in 2021 to 30 in 2022. Total injuries also increased from 2 to 8 during this period, indicating a more severe outcome for those involved in crashes. Fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 2300.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day changing from Monday with 5 crashes in March 2021 to both Wednesday and Thursday, each with 10 crashes, in March 2022. The peak hour also shifted from 5 PM with 3 crashes in March 2021 to 2 PM and 3 PM, each with 6 crashes, in March 2022. This indicates a broader distribution of peak crash times across weekdays and earlier in the afternoon.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While there were no fatal crashes in either period, total injuries increased from 2 in March 2021 to 8 in March 2022. Minor injury crashes increased from 1 (7.1% of total) to 3 (10% of total), and possible injury crashes also increased from 1 (7.1% of total) to 3 (10% of total). The proportion of no-injury crashes decreased from 85.7% to 80% of total crashes.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes10%
200.0%prior 1
Possible Injury3possible injury crashes10%
200.0%prior 1
No Injury24no injury crashes80%
100.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw increased counts year-over-year; 'No improper driving' increased from 3 crashes to 5, 'Inattention' from 3 to 4, and 'Failed to yield right of way' from 2 to 4. 'Disregarded traffic signs, signals, road markings' also increased from 1 crash to 3 crashes. The factor 'Distracted' remained constant at 2 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving5 (16.7%)
Inattention4 (13.3%)
Failed to yield right of way4 (13.3%)
Disregarded traffic signs, signals, road markings3 (10%)
Other improper action2 (6.7%)
Distracted2 (6.7%)
Failure to keep in proper lane or running off road1 (3.3%)
Over-correcting/over-steering1 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Fatigued/asleep1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions increased from 7 in March 2021 to 15 in March 2022, while 'Clear' conditions increased from 5 to 7. Crashes during 'Rain' (including 'Rain/Cloudy' and 'Cloudy/Rain') conditions appeared in March 2022 with 4 occurrences, compared to none in March 2021. For lighting, crashes in 'Daylight' increased from 12 to 25, and crashes in 'Dark - roadway not lighted' increased from 1 to 2. No comparison can be made for road surface conditions as data was not available for the prior period.

Weather

Clear/Clear15 (50.0%)
114.3%prior 7
Clear7 (23.3%)
40.0%prior 5
Cloudy2 (6.7%)
Rain2 (6.7%)
Rain/Cloudy1 (3.3%)
Clear/Cloudy1 (3.3%)
Cloudy/Cloudy1 (3.3%)
Cloudy/Rain1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight25 (83.3%)
108.3%prior 12
Dark - roadway not lighted2 (6.7%)
Dark - lighted roadway1 (3.3%)
Dawn1 (3.3%)
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry23 (76.7%)
Wet6 (20.0%)
Ice1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (53 vehicles)

1
TOYOTA11 (20.8%)
2
FORD6 (11.3%)
20.0%prior 5
3
JEEP5 (9.4%)
4
CHEVROLET5 (9.4%)
5
HONDA3 (5.7%)
6
SUBARU3 (5.7%)
7
VOLKSWAGEN3 (5.7%)
8
NISSAN2 (3.8%)
9
GMC2 (3.8%)
10
KIA2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (56 persons with recorded sex)

Male31 (55.4%)
63.2%prior 19
Female25 (44.6%)
66.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 3 in March 2021 to 7 in March 2022, and those in 35 mph zones increased from 2 to 6. Crashes in 40 mph zones increased from 1 to 3, and 65 mph zones increased from 2 to 3. Conversely, crashes in 25 mph zones decreased from 2 to 1. Fatal rates remained at 0 across all speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: FRANKLIN, MA
  • Total crash records analyzed: 30
  • Total persons involved: 58
  • Total vehicles involved: 53

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: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/franklin/march-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 — March 2022 | ThatCarHitMe.com