Monthly Traffic Safety Analysis

16 CRASHES IN
MARION, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

In January 2022, MARION experienced 16 total crashes, a substantial increase of 166.67% compared to the 6 crashes recorded in January 2021. The most notable shift was the absence of fatalities in January 2022, down from 1 fatality in January 2021.

16

166.7%was 6

Total Crash Events

0

-100.0%was 1

Persons Killed

4

300.0%was 1

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

Trend Summary

The overall trend indicates a significant increase in crashes year-over-year, with total crashes rising from 6 in January 2021 to 16 in January 2022, representing a 166.67% increase.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

4

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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 Saturday with 2 crashes in January 2021 to Sunday with 5 crashes in January 2022. The peak hour also shifted from 1p with 2 crashes in January 2021 to 11p with 2 crashes in January 2022, indicating a change in the timing of crash occurrences.

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

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

Crash Severity Breakdown

The fatal crash rate decreased from 16.67% in January 2021 to 0% in January 2022, as there was 1 fatal crash in the prior period and 0 in the current. While the prior period had 0 non-fatal injury crashes, the current period saw 4 injury crashes, comprising 1 serious injury crash, 2 minor injury crashes, and 1 possible injury crash, representing 25% of total crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.3%
Minor Injury2minor injury crashes12.5%
Possible Injury1possible injury crashes6.3%
No Injury11no injury crashes68.8%
120.0%prior 5

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The top contributing factor, "No improper driving," increased from 2 crashes in January 2021 to 8 crashes in January 2022. Factors like "Exceeded authorized speed limit" and "Failed to yield right of way" maintained a count of 1 crash each across both periods. Several new contributing factors, such as "Fatigued/asleep" and "Inattention," appeared with 1 crash each in January 2022, which were not present in January 2021.

Officer-Reported Primary Contributing Cause

No improper driving8 (50%)
Exceeded authorized speed limit1 (6.3%)
Failed to yield right of way1 (6.3%)
Fatigued/asleep1 (6.3%)
Followed too closely1 (6.3%)
Glare1 (6.3%)
Inattention1 (6.3%)
Driving too fast for conditions1 (6.3%)
Physical impairment1 (6.3%)

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

Road & Environmental Conditions

Crashes under clear weather conditions increased from 5 in January 2021 to 9 in January 2022, and daylight crashes increased from 2 to 8. Crashes on dry road surfaces also increased from 5 to 9, while crashes on snow-covered roads increased from 1 to 2. Additionally, conditions like rain, wet road surfaces, and ice appeared as factors in January 2022, not being present in the prior period.

Weather

Clear9 (64.3%)
80.0%prior 5
Cloudy2 (14.3%)
Rain1 (7.1%)
Severe crosswinds/Cloudy1 (7.1%)
Sleet, hail (freezing rain or drizzle)1 (7.1%)

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

Lighting

Daylight8 (50.0%)
Dark - roadway not lighted6 (37.5%)
Dark - lighted roadway2 (12.5%)

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

Road Surface

Dry9 (56.3%)
80.0%prior 5
Wet3 (18.8%)
Snow2 (12.5%)
Ice1 (6.3%)
Other1 (6.3%)

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

Vehicles & Demographics

Top Vehicle Makes (22 vehicles)

1
HONDA4 (18.2%)
2
FORD4 (18.2%)
3
GMC3 (13.6%)
4
SUBARU2 (9.1%)
5
TOYOTA2 (9.1%)
6
NISSAN1 (4.5%)
7
BMW1 (4.5%)
8
VOLKSWAGEN1 (4.5%)
9
CHEVROLET1 (4.5%)
10
HYUNDAI1 (4.5%)

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

Sex Distribution (26 persons with recorded sex)

Female13 (50.0%)
333.3%prior 3
Male13 (50.0%)
160.0%prior 5

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

Speed Limit Zones

Crashes in the 40 mph speed zone increased from 1 in January 2021 to 2 in January 2022, and those in the 65 mph zone increased from 2 to 5. The 50 mph speed zone emerged with 6 crashes in January 2022, not appearing in the prior period's data. The single fatal crash in the 25 mph zone in January 2021 was not present in any speed zone in January 2022.

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

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: MARION, MA
  • Total crash records analyzed: 16
  • Total persons involved: 27
  • Total vehicles involved: 22

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). "MARION, MA Crash Intelligence Report: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marion/january-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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Marion, MA Crash Report — January 2022 | ThatCarHitMe.com