Monthly Traffic Safety Analysis

54 CRASHES IN
CHARLTON, MA
FEBRUARY 2022

All metrics benchmarked againstFebruary 2021

Total crashes in Charlton increased significantly from 19 in February 2021 to 54 in February 2022, marking a 184.21% rise. This period also saw one fatal crash and one fatality, whereas no fatalities were recorded in the prior year. The substantial increase in overall crash volume and the occurrence of a fatality are the most notable year-over-year shifts.

54

184.2%was 19

Total Crash Events

1

Persons Killed

20

566.7%was 3

Persons Injured

0

-100.0%was 1

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash incidents in Charlton showed a substantial upward trend year-over-year, increasing from 19 crashes in February 2021 to 54 crashes in February 2022. This represents an increase of 35 crashes, or 184.21%.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

20

Motorists Injured

Prior: 3566.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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 moving from Tuesday in February 2021 (7 crashes) to Saturday in February 2022 (17 crashes). The peak crash hour also changed from 4 AM with 3 crashes in the prior period to 7 PM with 6 crashes in the current period. This indicates a shift towards higher crash volumes during weekend and evening hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in February 2022 compared to the prior year, with one fatal crash and one fatality recorded, up from zero in February 2021. Total injuries rose from 3 to 20 year-over-year. Minor injury crashes increased from 3 (15.8% share of crashes) to 9 (16.7% share of crashes), and possible injury crashes, not present in the prior period, accounted for 4 crashes (7.4% share of crashes) in the current period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.9%
Minor Injury9minor injury crashes16.7%
200.0%prior 3
Possible Injury4possible injury crashes7.4%
No Injury40no injury crashes74.1%
150.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to "No improper driving" rose from 5 in February 2021 to 23 in February 2022, representing a 360% increase in count. Crashes where "Driving too fast for conditions" was a factor doubled from 4 to 8, a 100% increase in count. "Failed to yield right of way" crashes increased from 1 to 5, a 400% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving23 (42.6%)360.0%prior 5
Driving too fast for conditions8 (14.8%)
Failed to yield right of way5 (9.3%)
Followed too closely4 (7.4%)
Operating defective equipment2 (3.7%)
Physical impairment2 (3.7%)
Glare1 (1.9%)
Failure to keep in proper lane or running off road1 (1.9%)
Fatigued/asleep1 (1.9%)
Distracted1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes under "Clear" weather conditions increased substantially from 3 in February 2021 to 27 in February 2022, while crashes in "Snow" conditions also rose from 5 to 11. Under lighting conditions, crashes during "Daylight" increased from 9 to 23, and crashes in "Dark - lighted roadway" increased from 3 to 15. For road surface conditions, "Dry" surface crashes increased from 5 to 18, and "Ice" surface crashes rose from 1 to 13 in the current period.

Weather

Clear27 (50.0%)
Snow11 (20.4%)
120.0%prior 5
Cloudy6 (11.1%)
Sleet, hail (freezing rain or drizzle)3 (5.6%)
Rain2 (3.7%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (1.9%)
Sleet, hail (freezing rain or drizzle)/Rain1 (1.9%)
Sleet, hail (freezing rain or drizzle)/Snow1 (1.9%)
Clear/Unknown1 (1.9%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash

Lighting

Daylight23 (42.6%)
155.6%prior 9
Dark - lighted roadway15 (27.8%)
Dark - roadway not lighted14 (25.9%)
133.3%prior 6
Dusk2 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field

Road Surface

Dry18 (33.3%)
260.0%prior 5
Ice13 (24.1%)
Snow13 (24.1%)
62.5%prior 8
Wet5 (9.3%)
Slush4 (7.4%)
Water (standing, moving)1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (79 vehicles)

1
TOYOTA13 (16.5%)
2
HONDA10 (12.7%)
3
CHEVROLET7 (8.9%)
4
SUBARU6 (7.6%)
5
FORD6 (7.6%)
6
NISSAN5 (6.3%)
7
JEEP3 (3.8%)
8
GMC3 (3.8%)
9
MITS3 (3.8%)
10
KIA2 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records

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

Sex Distribution (107 persons with recorded sex)

Male57 (53.3%)
200.0%prior 19
Female50 (46.7%)
455.6%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased from 9 in February 2021 to 14 in February 2022, and this zone recorded the only fatal crash in the current period. Crashes in 30 mph zones also saw a significant increase from 1 to 12 year-over-year. Additionally, 50 mph zones accounted for 9 crashes in the current period, a category not as prominent in the prior period's top crash zones.

Fatal crashes by zone: 65 mph: 1 of 14 (7.143%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-02-01 through 2022-02-28 (28 days)
  • Geographic scope: CHARLTON, MA
  • Total crash records analyzed: 54
  • Total persons involved: 110
  • Total vehicles involved: 79

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). "CHARLTON, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/charlton/february-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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Charlton, MA Crash Report — February 2022 | ThatCarHitMe.com