Monthly Traffic Safety Analysis

18 CRASHES IN
GREAT BARRINGTON, MA
JUNE 2024

All metrics benchmarked againstJune 2023

GREAT BARRINGTON experienced a slight increase in total crashes, rising from 17 in June 2023 to 18 in June 2024, representing a 5.9% increase. A notable shift was observed in crashes occurring within 25 mph speed zones, which more than doubled from 2 to 7 crashes year-over-year.

18

5.9%was 17

Total Crash Events

0

Persons Killed

3

-25.0%was 4

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 · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in GREAT BARRINGTON showed a rising trend year-over-year, increasing by 1 crash from 17 in June 2023 to 18 in June 2024. This represents a 5.9% increase in total crash incidents for the month.

1

Hit-and-Run Crashes — June 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both June 2023 and June 2024. Consequently, the hit-and-run rate saw a slight decrease from 5.9% in the prior period to 5.6% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 4-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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 3 crashes in June 2023, to Monday, with 6 crashes in June 2024. The peak hour also changed, moving from 3 PM with 3 crashes in the prior period to 8 AM with 4 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities recorded in either June 2023 or June 2024. Total injuries decreased from 4 in June 2023 to 3 in June 2024. Minor injury crashes, as a proportion of total crashes, increased from 5.9% (1 crash) in the prior period to 11.1% (2 crashes) in the current period.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes11.1%
100.0%prior 1
No Injury15no injury crashes83.3%
15.4%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving', increased from 6 crashes in June 2023 to 7 crashes in June 2024. 'Inattention' decreased significantly from 4 crashes to 1 crash, while 'Followed too closely' increased from 1 crash to 2 crashes. New factors observed in June 2024 include 'Failure to keep in proper lane or running off road' (2 crashes) and 'Disregarded traffic signs, signals, road markings' (1 crash).

Officer-Reported Primary Contributing Cause

No improper driving7 (38.9%)16.7%prior 6
Failure to keep in proper lane or running off road2 (11.1%)
Followed too closely2 (11.1%)
Disregarded traffic signs, signals, road markings1 (5.6%)
Inattention1 (5.6%)
Distracted1 (5.6%)
Failed to yield right of way1 (5.6%)
Other improper action1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 14 to 16 year-over-year, while cloudy conditions remained stable at 2 crashes. Wet road crashes decreased from 3 in June 2023 to 1 in June 2024, with dry road crashes increasing from 14 to 17. Crashes during daylight conditions increased from 14 to 15, and 'Dark - lighted roadway' (2 crashes) was observed in the current period, replacing 'Dark - roadway not lighted' (2 crashes) from the prior period.

Weather

Clear16 (88.9%)
14.3%prior 14
Cloudy2 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight15 (83.3%)
7.1%prior 14
Dark - lighted roadway2 (11.1%)
Dusk1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry17 (94.4%)
21.4%prior 14
Wet1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
SUBARU8 (25%)
2
TOYOTA4 (12.5%)
-50.0%prior 8
3
HYUNDAI3 (9.4%)
4
HONDA3 (9.4%)
5
FORD2 (6.3%)
6
KIA2 (6.3%)
7
UT2 (6.3%)
8
JEEP1 (3.1%)
9
BMW1 (3.1%)
10
CHEVROLET1 (3.1%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

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

Sex Distribution (29 persons with recorded sex)

Male17 (58.6%)
6.3%prior 16
Female12 (41.4%)
-25.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone saw a notable increase from 2 in June 2023 to 7 in June 2024. Conversely, crashes in the 35 mph zone decreased from 6 to 4. New crashes were reported in the 55 mph zone (2 crashes) in June 2024, a zone not present in the prior period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: GREAT BARRINGTON, MA
  • Total crash records analyzed: 18
  • Total persons involved: 32
  • Total vehicles involved: 32

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). "GREAT BARRINGTON, MA Crash Intelligence Report: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/great-barrington/june-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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Great Barrington, MA Crash Report — June 2024 | ThatCarHitMe.com