Yearly Traffic Safety Analysis

10 CRASHES IN
CUMMINGTON, MA
2022

All metrics benchmarked against2021

In 2022, Cummington recorded 10 total traffic crashes, an 11.1% increase from the 9 crashes recorded in 2021. While total crashes saw a slight rise, the number of reported injuries increased significantly from 2 in 2021 to 8 in 2022. This period also saw the emergence of a serious injury crash, which was not present in the prior year's data.

10

11.1%was 9

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Cummington trended upward year-over-year. Total collisions increased from 9 in 2021 to 10 in 2022. The most significant change was in the number of injuries, which quadrupled from 2 to 8 during the same period, while fatalities remained at zero in both years.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

7

Motorists Injured

Prior: 2250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted between the two years. The peak day for collisions moved from Thursday in 2021 (3 crashes) to Friday in 2022 (3 crashes). In 2022, crashes clustered in the 9 a.m., 12 p.m., and 5 p.m. hours with 2 incidents each, whereas in 2021, crashes were more evenly distributed throughout the day with no single hour having more than one incident.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased from 2021 to 2022, although no fatalities were recorded in either year. In 2022, 40% of crashes resulted in an injury, including one serious injury crash (10% of total) and three minor injury crashes (30%). This represents an increase from 2021, where 22.2% of crashes involved an injury and none were classified as serious.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes10%
Minor Injury3minor injury crashes30%
200.0%prior 1
No Injury6no injury crashes60%
-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

In both 2021 and 2022, "No improper driving" was the most frequently listed contributing factor, with its count increasing from 5 to 6 crashes. The number of crashes attributed to a fatigued or asleep driver remained stable at one incident in both years. Notably, 2022 saw single crashes attributed to "Distracted" and "Swerving or avoiding," factors that were not present in the 2021 data.

Officer-Reported Primary Contributing Cause

No improper driving6 (60%)20.0%prior 5
Distracted1 (10%)
Fatigued/asleep1 (10%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (10%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A direct comparison of all conditions is limited as weather and lighting data were not available for 2022. For road surface conditions, crashes on dry roads were predominant in both years, accounting for 8 of 10 crashes (80%) in 2022 and 6 of 9 crashes (67%) in 2021. Both years recorded one crash each on an icy surface.

Road Surface

Dry8 (80.0%)
33.3%prior 6
Ice1 (10.0%)
Sand, mud, dirt, oil, gravel1 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (12 vehicles)

1
HONDA4 (33.3%)
2
CHEVROLET2 (16.7%)
3
HYUNDAI1 (8.3%)
4
MITSUBISHI1 (8.3%)
5
NISSAN1 (8.3%)
6
SUBARU1 (8.3%)
7
VOLVO1 (8.3%)
8
FORD1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

Sex Distribution (20 persons with recorded sex)

Male12 (60.0%)
71.4%prior 7
Female8 (40.0%)
166.7%prior 3

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 2022 were more concentrated in higher speed zones compared to the previous year. In 2022, 50% of crashes with a recorded speed limit (5 out of 10) occurred in zones of 50 mph or higher, up from 33% (3 out of 9) in 2021. The highest number of crashes in 2022 occurred in the 55 mph zone with 3 incidents. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: CUMMINGTON, MA
  • Total crash records analyzed: 10
  • Total persons involved: 20
  • Total vehicles involved: 12

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). "CUMMINGTON, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/cummington/2022-annual-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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Cummington, MA Crash Report — 2022 | ThatCarHitMe.com