Monthly Traffic Safety Analysis

31 CRASHES IN
PALMER, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, PALMER experienced a total of 31 crashes, marking a 22.5% decrease from the 40 crashes reported in May 2024. This notable reduction in total incidents is the most significant year-over-year shift, contributing to an overall safer period compared to the prior year.

31

-22.5%was 40

Total Crash Events

0

Persons Killed

10

-16.7%was 12

Persons Injured

0

-100.0%was 3

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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends for PALMER show a decrease year-over-year, with total crashes falling from 40 in May 2024 to 31 in May 2025, a reduction of 9 crashes or 22.5%. Total injuries also decreased by 2, from 12 to 10, representing a 16.7% decline. There were no fatalities reported in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 12-16.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 Friday in May 2024, which saw 12 incidents, to Thursday in May 2025 with 8 incidents. Similarly, the peak crash hour moved from 4 PM with 7 crashes in May 2024 to 5 PM with 5 crashes in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both May 2024 and May 2025 reported 0 fatalities, indicating no change in fatal crash outcomes. Total injuries decreased from 12 in the prior period to 10 in the current period. The number of serious injury crashes remained constant at 1 in both periods, while minor injury crashes decreased from 8 to 6.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.2%
0.0%prior 1
Minor Injury6minor injury crashes19.4%
-25.0%prior 8
Possible Injury1possible injury crashes3.2%
0.0%prior 1
No Injury22no injury crashes71%
-26.7%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Inattention' saw a significant decrease of 6 incidents, falling from 7 in May 2024 to 1 in May 2025. Factors such as 'No improper driving,' 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner,' and 'Followed too closely' each decreased by 2 crashes year-over-year. Conversely, 'Failed to yield right of way' crashes increased by 1, from 5 to 6 incidents.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (19.4%)20.0%prior 5
No improper driving4 (12.9%)-33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.5%)
Other improper action2 (6.5%)
Over-correcting/over-steering2 (6.5%)
Visibility obstructed2 (6.5%)
Followed too closely2 (6.5%)
Distracted2 (6.5%)
Fatigued/asleep2 (6.5%)
Emotional1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions decreased from 30 in May 2024 to 23 in May 2025. There was a notable shift in road surface conditions, with crashes on 'Dry' surfaces decreasing from 35 to 20, while those on 'Wet' surfaces increased from 5 to 8. Crashes during 'Clear' weather (including 'Clear/Clear') decreased from 33 to 14, whereas crashes during 'Rain' increased from 3 to 5.

Weather

Clear10 (33.3%)
-68.8%prior 32
Cloudy5 (16.7%)
Rain5 (16.7%)
Clear/Clear4 (13.3%)
Clear/Cloudy4 (13.3%)
Rain/Cloudy2 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight23 (76.7%)
-23.3%prior 30
Dark - roadway not lighted3 (10.0%)
Dark - lighted roadway2 (6.7%)
-60.0%prior 5
Dusk1 (3.3%)
Other1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry20 (66.7%)
-42.9%prior 35
Wet8 (26.7%)
60.0%prior 5
Water (standing, moving)2 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 77 in May 2024 to 54 in May 2025. Toyota's involvement in crashes decreased from 10 vehicles to 8, and Honda's decreased from 10 to 7. Conversely, Hyundai vehicles involved in crashes increased from 3 to 6 year-over-year.

Top Vehicle Makes (54 vehicles)

1
TOYOTA8 (14.8%)
-20.0%prior 10
2
CHEVROLET7 (13%)
0.0%prior 7
3
HONDA7 (13%)
-30.0%prior 10
4
HYUNDAI6 (11.1%)
5
FORD4 (7.4%)
-55.6%prior 9
6
NISSAN4 (7.4%)
7
VOLKSWAGEN2 (3.7%)
8
MERCEDES-BENZ2 (3.7%)
9
MACK1 (1.9%)
10
MAZDA1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Male39 (62.9%)
-23.5%prior 51
Female23 (37.1%)
-30.3%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed limit zone decreased by 4 incidents, from 14 in May 2024 to 10 in May 2025. Similarly, crashes in the 35 mph zone decreased from 4 to 1, and in the 40 mph zone from 4 to 1. No fatalities were reported in any speed limit zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: PALMER, MA
  • Total crash records analyzed: 31
  • Total persons involved: 66
  • Total vehicles involved: 54

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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/palmer/may-2025-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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