Monthly Traffic Safety Analysis

35 CRASHES IN
PALMER, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

In January 2022, PALMER experienced 35 total crashes, an increase of 20.7% compared to the 29 crashes reported in January 2021. Despite the rise in total crashes, total injuries decreased by 50%, from 10 injuries in January 2021 to 5 injuries in January 2022. Fatalities remained at zero in both periods.

35

20.7%was 29

Total Crash Events

0

Persons Killed

5

-50.0%was 10

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. 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 rise in total crashes, increasing by 20.7% from 29 crashes in January 2021 to 35 crashes in January 2022. Conversely, total injuries saw a significant decrease of 50%, falling from 10 to 5 over the same period. Fatalities remained stable at zero for both months.

1

Hit-and-Run Crashes — January 2022

2.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 10-50.0%

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 remained Monday in both periods, with 7 crashes in January 2021 increasing to 10 crashes in January 2022. The peak crash hour shifted from 5 p.m. with 4 crashes in January 2021 to 8 a.m. with 6 crashes in January 2022. This suggests a change in the busiest crash times, moving from evening to morning commute hours.

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

Fatalities remained at 0 in both January 2021 and January 2022. Total injuries decreased by 50%, from 10 in January 2021 to 5 in January 2022. The proportion of crashes resulting in no injury increased from 72.4% (21 crashes) in January 2021 to 82.9% (29 crashes) in January 2022, while serious injuries (code A) were reported in 1 crash in January 2021 but not in January 2022.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes5.7%
-50.0%prior 4
Possible Injury3possible injury crashes8.6%
0.0%prior 3
No Injury29no injury crashes82.9%
38.1%prior 21

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

"No improper driving" remained the most frequent contributing factor, increasing from 8 crashes in January 2021 to 9 crashes in January 2022. "Failure to keep in proper lane or running off road" decreased from 4 crashes in January 2021 to 2 crashes in January 2022. "Visibility obstructed" was a factor in 3 crashes in January 2022, but was not among the top contributing factors in January 2021.

Officer-Reported Primary Contributing Cause

No improper driving9 (25.7%)12.5%prior 8
Other improper action3 (8.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (8.6%)
Inattention3 (8.6%)
Visibility obstructed3 (8.6%)
Driving too fast for conditions2 (5.7%)
Exceeded authorized speed limit2 (5.7%)
Failure to keep in proper lane or running off road2 (5.7%)
Operating defective equipment1 (2.9%)
Followed too closely1 (2.9%)

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 occurring in "Clear" weather conditions increased from 11 in January 2021 to 16 in January 2022. Conversely, crashes in "Snow" conditions decreased from 7 in January 2021 to 6 in January 2022. The number of crashes occurring in "Daylight" increased from 12 in January 2021 to 21 in January 2022, while crashes on "Ice" road surfaces rose from 2 to 5 between the two periods.

Weather

Clear16 (45.7%)
45.5%prior 11
Snow6 (17.1%)
-14.3%prior 7
Cloudy6 (17.1%)
-14.3%prior 7
Clear/Cloudy3 (8.6%)
Sleet, hail (freezing rain or drizzle)2 (5.7%)
Rain/Cloudy1 (2.9%)
Snow/Blowing sand, snow1 (2.9%)

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

Lighting

Daylight21 (60.0%)
75.0%prior 12
Dark - lighted roadway7 (20.0%)
40.0%prior 5
Dark - roadway not lighted6 (17.1%)
-40.0%prior 10
Dawn1 (2.9%)

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

Road Surface

Dry17 (48.6%)
0.0%prior 17
Snow8 (22.9%)
-11.1%prior 9
Ice5 (14.3%)
Wet4 (11.4%)
Slush1 (2.9%)

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 (53 vehicles)

1
CHEVROLET11 (20.8%)
120.0%prior 5
2
FORD7 (13.2%)
16.7%prior 6
3
HYUNDAI6 (11.3%)
4
JEEP4 (7.5%)
5
DODGE4 (7.5%)
6
VOLVO3 (5.7%)
7
TOYOTA3 (5.7%)
-57.1%prior 7
8
BUIC2 (3.8%)
9
HONDA2 (3.8%)
10
GMC1 (1.9%)

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

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

Sex Distribution (63 persons with recorded sex)

Male42 (66.7%)
13.5%prior 37
Female21 (33.3%)
23.5%prior 17

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

The most common speed limit for crashes shifted from 40 mph (7 crashes) in January 2021 to 30 mph (16 crashes) in January 2022. Crashes in 30 mph zones increased significantly from 6 in January 2021 to 16 in January 2022. Conversely, crashes in 40 mph zones decreased from 7 in January 2021 to 2 in January 2022, and no fatal crashes were recorded in any speed zone during either period.

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: PALMER, MA
  • Total crash records analyzed: 35
  • Total persons involved: 65
  • 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). "PALMER, 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/palmer/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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Palmer, MA Crash Report — January 2022 | ThatCarHitMe.com