Monthly Traffic Safety Analysis

4 CRASHES IN
ASHFIELD, MA
AUGUST 2024

During August 2024, ASHFIELD, MA recorded a total of 4 crashes, resulting in 0 fatalities and 1 injury. The most notable finding is that 75% of crashes resulted in no injuries, with the remaining 25% involving minor injuries. There were no fatal crashes reported during this period.

4

Total Crash Events

0

Persons Killed

1

Persons Injured

0

Fatal Crash Events

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 · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

During August 2024, there were no pedestrians or cyclists killed or injured in crashes. One motorist sustained injuries, while no motorists were killed. Overall, 1 motorist was injured, making them the highest-impact group in terms of injuries.

0

Motorists Killed

1

Motorists Injured

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash data for August 2024 indicates that crashes most frequently occurred on Wednesday, with 2 incidents. The peak hour for crashes was 11p, accounting for 1 incident, though other hours also recorded single incidents. Crashes were equally split between daylight (2 incidents) and non-daylight conditions (1 dark, 1 dusk).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Analysis of crash severity reveals that 75% of incidents (3 out of 4) resulted in no injuries. The remaining 25% (1 crash) involved minor injuries. There were no fatal crashes, and consequently, 0 fatalities were reported during this period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes25%
No Injury3no injury crashes75%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record

Top Contributing Factors

The most common contributing factor identified in crashes was 'No improper driving,' accounting for 50% of incidents (2 crashes). 'Driving too fast for conditions' and 'Inattention' each contributed to 25% of crashes (1 incident each). This indicates that half of the crashes did not involve reported improper driving.

Officer-Reported Primary Contributing Cause

No improper driving2 (50%)
Driving too fast for conditions1 (25%)
Inattention1 (25%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Regarding environmental conditions, 75% of crashes (3 out of 4) occurred in clear weather and on dry road surfaces. Daylight conditions were present in 50% of crashes (2 incidents), while 25% occurred in dark conditions and 25% at dusk. One crash occurred in cloudy/rainy weather and on a wet road surface.

Weather

Clear3 (75.0%)
Cloudy/Rain1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash

Lighting

Daylight2 (50.0%)
Dark - roadway not lighted1 (25.0%)
Dusk1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field

Road Surface

Dry3 (75.0%)
Wet1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (4 vehicles)

1
TOYOTA2 (50%)
2
MIFU1 (25%)
3
SUBARU1 (25%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records

Sex Distribution (8 persons with recorded sex)

Female4 (50.0%)
Male4 (50.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes were equally distributed between 35 mph and 45 mph speed limit zones, with 2 crashes occurring in each zone. This means 50% of crashes occurred in the 35 mph zone and 50% in the 45 mph zone. No fatal crashes were reported in either speed zone during this period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-08-01 through 2024-08-31 (31 days)
  • Geographic scope: ASHFIELD, MA
  • Total crash records analyzed: 4
  • Total persons involved: 8
  • 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). "ASHFIELD, MA Crash Intelligence Report: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ashfield/august-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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Ashfield, MA Crash Report — August 2024 | ThatCarHitMe.com