Yearly Traffic Safety Analysis

36 CRASHES IN
BARRE, MA
2024

All metrics benchmarked against2023

In 2024, Barre recorded 36 total crashes, a 63.6% increase from the 22 crashes reported in 2023. The total number of injuries also rose from 4 to 8. Most notably, the city experienced one fatal crash resulting in one death in 2024, whereas no fatalities were recorded in the prior year.

36

63.6%was 22

Total Crash Events

1

Persons Killed

8

100.0%was 4

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Barre show a significant year-over-year increase. Total crashes rose by 63.6%, from 22 in 2023 to 36 in 2024. This upward trend is also reflected in crash outcomes, with total injuries doubling from 4 to 8 and one fatality occurring in 2024 compared to zero in the previous year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

8

Motorists Injured

Prior: 4100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Thursday with 12 incidents, a change from Friday, which was the peak day in 2023 with 10 incidents. The peak hour also moved from the evening to the morning, shifting from 6 p.m. (3 crashes) in 2023 to 10 a.m. (5 crashes) in 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a notable shift with the emergence of a fatal crash in 2024, which accounted for 2.8% of all incidents, compared to zero fatal crashes in 2023. The proportion of crashes resulting in any injury remained relatively stable, moving from 18.2% (4 out of 22 crashes) in 2023 to 19.4% (7 out of 36 crashes) in 2024. The share of non-injury crashes was nearly identical in both years, at 77.3% in 2023 and 77.8% in 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.8%
Minor Injury6minor injury crashes16.7%
200.0%prior 2
Possible Injury1possible injury crashes2.8%
0.0%prior 1
No Injury28no injury crashes77.8%
64.7%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

While "No improper driving" was the most common primary factor in both years, the specific driver-related factors changed. The count of crashes attributed to "Inattention" increased significantly from 1 in 2023 to 7 in 2024. "History heart/epilepsy/fainting" was cited in 2 crashes in 2024 but only 1 in the prior year. Conversely, factors like "Failure to keep in proper lane or running off road" decreased from 2 crashes in 2023 to 1 in 2024, and "Exceeded authorized speed limit," cited in 1 crash in 2023, was not a primary factor in 2024.

Officer-Reported Primary Contributing Cause

No improper driving20 (55.6%)66.7%prior 12
Inattention7 (19.4%)
History heart/epilepsy/fainting2 (5.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.8%)
Over-correcting/over-steering1 (2.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.8%)
Distracted1 (2.8%)
Failed to yield right of way1 (2.8%)
Failure to keep in proper lane or running off road1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The conditions under which crashes occurred shifted towards clearer weather and better visibility year-over-year. In 2024, 77.8% of crashes happened in clear weather, a substantial increase from 50% in 2023. Similarly, crashes in daylight conditions rose from 50% of the total in 2023 to 69.4% in 2024. The proportion of crashes on non-dry road surfaces (wet, ice, or snow) saw a slight decrease, accounting for 36.1% of crashes in 2024 compared to 40.9% in the prior year.

Weather

Clear28 (77.8%)
154.5%prior 11
Snow2 (5.6%)
Cloudy1 (2.8%)
Rain1 (2.8%)
Rain/Cloudy1 (2.8%)
Snow/Blowing sand, snow1 (2.8%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.8%)
Clear/Other1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight25 (69.4%)
127.3%prior 11
Dark - lighted roadway3 (8.3%)
Dark - roadway not lighted3 (8.3%)
-40.0%prior 5
Dawn3 (8.3%)
Dusk2 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry23 (63.9%)
76.9%prior 13
Wet6 (16.7%)
Ice4 (11.1%)
Snow3 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (49 vehicles)

1
TOYOTA9 (18.4%)
50.0%prior 6
2
CHEVROLET6 (12.2%)
3
HONDA6 (12.2%)
4
GMC5 (10.2%)
5
JEEP3 (6.1%)
6
FORD3 (6.1%)
7
HYUNDAI2 (4.1%)
8
MACK2 (4.1%)
9
NISSAN2 (4.1%)
10
SUBARU2 (4.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

Sex Distribution (54 persons with recorded sex)

Male32 (59.3%)
100.0%prior 16
Female22 (40.7%)
46.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones changed between periods. In 2024, the 30 mph zone saw the highest number of crashes (12), double the 6 crashes recorded in that zone in 2023. Conversely, crashes in 40 mph zones decreased from 8 in 2023 to 6 in 2024. The single fatal crash in 2024 occurred in a 30 mph zone, where no fatalities were recorded in the previous year.

Fatal crashes by zone: 30 mph: 1 of 12 (8.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: BARRE, MA
  • Total crash records analyzed: 36
  • Total persons involved: 55
  • Total vehicles involved: 49

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). "BARRE, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barre/2024-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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Barre, MA Crash Report — 2024 | ThatCarHitMe.com