Monthly Traffic Safety Analysis

3 CRASHES IN
CHARLEMONT, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

In March 2024, Charlemont experienced 3 crashes, an increase from the 2 crashes reported in March 2023, representing a 50% rise. Concurrently, total injuries decreased by 50%, from 2 in the prior period to 1 in the current period.

3

50.0%was 2

Total Crash Events

0

Persons Killed

1

-50.0%was 2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Total crashes in Charlemont increased from 2 in March 2023 to 3 in March 2024, marking a 50% rise year-over-year. Despite this increase in crash events, total injuries decreased by 50%, from 2 to 1 during the same period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 2-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 Wednesday in March 2023 to Saturday in March 2024, with 1 crash on each day. The peak hour also shifted significantly, from 4 PM with 1 crash in March 2023 to 8 PM with 2 crashes in March 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Crash Severity Breakdown

There were no fatalities in either March 2023 or March 2024. Total injuries decreased from 2 in March 2023 to 1 in March 2024. In March 2023, 1 crash resulted in minor injuries, while in March 2024, 1 crash also resulted in minor injuries.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes33.3%
0.0%prior 1
No Injury2no injury crashes66.7%
100.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Driving too fast for conditions' remained present in both periods, with 1 crash attributed to it each year. 'Wrong side or wrong way' was a factor in 1 crash in March 2023 but was not listed in March 2024. Conversely, 'No improper driving' and 'Physical impairment' each contributed to 1 crash in March 2024, neither of which were present in the prior period's top factors.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions1 (33.3%)
No improper driving1 (33.3%)
Physical impairment1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 1 in March 2023 to 2 in March 2024. Regarding road surface, 'Dry' conditions were present in 1 crash in both periods. In March 2023, 1 crash occurred on a 'Slush' road surface, while in March 2024, 1 crash occurred on a 'Snow' surface and 1 on a 'Wet' surface.

Weather

Clear2 (66.7%)
Snow/Sleet, hail (freezing rain or drizzle)1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Road Surface

Dry1 (33.3%)
Snow1 (33.3%)
Wet1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (4 vehicles)

1
CHEVROLET1 (25%)
2
HONDA1 (25%)
3
MACK1 (25%)
4
MAZDA1 (25%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

Sex Distribution (5 persons with recorded sex)

Male3 (60.0%)
50.0%prior 2
Female2 (40.0%)
-33.3%prior 3

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in a 30 mph speed limit zone remained stable at 1 crash in both March 2023 and March 2024. Similarly, 1 crash occurred in a 50 mph speed limit zone in both periods. A crash in a 45 mph speed limit zone was recorded in March 2024, a category not present in March 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: CHARLEMONT, MA
  • Total crash records analyzed: 3
  • Total persons involved: 5
  • Total vehicles involved: 4

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). "CHARLEMONT, MA Crash Intelligence Report: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/charlemont/march-2024-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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Charlemont, MA Crash Report — March 2024 | ThatCarHitMe.com