Monthly Traffic Safety Analysis

9 CRASHES IN
ACUSHNET, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, ACUSHNET experienced 9 crashes, a significant decrease from the 15 crashes recorded in November 2021, representing a 40% reduction. Total injuries remained stable at 1 for both periods, with no fatalities reported in either year. The most notable shift is the substantial decline in overall crash incidents.

9

-40.0%was 15

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in ACUSHNET shows a significant decrease year-over-year, with total crashes falling by 40% from 15 in November 2021 to 9 in November 2022. This indicates a positive downward trend in crash incidents for the period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 10.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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 notably year-over-year. In November 2021, the peak day for crashes was Thursday with 3 incidents, while in November 2022, both Sunday and Monday saw the highest number of crashes, each with 2 incidents. The peak crash hour also changed from 3 PM with 3 crashes in the prior period to 10 PM with 2 crashes in the current period, indicating a shift towards later evening incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either November 2021 or November 2022. The total number of injuries remained constant at 1 in both periods. However, the proportion of crashes resulting in injury increased from 6.7% (1 injury crash out of 15 total crashes) in November 2021 to 11.1% (1 injury crash out of 9 total crashes) in November 2022, despite the overall reduction in crash count.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes11.1%
No Injury7no injury crashes77.8%
-41.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

The most prevalent contributing factor in November 2022 was 'No improper driving,' accounting for 8 crashes, an increase from 6 crashes in November 2021. Factors such as 'Inattention' and 'Followed too closely,' which each contributed to 2 crashes in the prior period, were not reported in the current period. The factor 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' remained constant, contributing to 1 crash in both periods.

Officer-Reported Primary Contributing Cause

No improper driving8 (88.9%)33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather remained the dominant condition for crashes in both periods, with 7 crashes in November 2022 compared to 12 in November 2021. There was a notable shift in lighting conditions, as crashes occurring in 'Dark - lighted roadway' increased from 4 in November 2021 to 6 in November 2022. Conversely, crashes during 'Daylight' decreased significantly from 10 in the prior period to 1 in the current period. Road surface conditions are not available for comparison in the current period.

Weather

Clear7 (77.8%)
-41.7%prior 12
Clear/Unknown1 (11.1%)
Cloudy1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway6 (66.7%)
Dark - roadway not lighted1 (11.1%)
Daylight1 (11.1%)
-90.0%prior 10
Dusk1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (9 vehicles)

1
FORD2 (22.2%)
2
DODGE1 (11.1%)
3
GMC1 (11.1%)
4
JEEP1 (11.1%)
5
KIA1 (11.1%)
6
NISSAN1 (11.1%)
7
CHEVROLET1 (11.1%)
8
SUBARU1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

Sex Distribution (9 persons with recorded sex)

Male5 (55.6%)
-66.7%prior 15
Female4 (44.4%)
-66.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted year-over-year. Crashes in the 25 mph zone, which accounted for 3 incidents in November 2021, were not reported in November 2022. The 30 mph zone saw a decrease from 4 crashes in the prior period to 1 crash in the current period, and the 35 mph zone decreased from 4 crashes to 3 crashes. Conversely, crashes in the 40 mph zone increased from 4 incidents in November 2021 to 5 incidents in November 2022. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: ACUSHNET, MA
  • Total crash records analyzed: 9
  • Total persons involved: 9
  • Total vehicles involved: 9

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). "ACUSHNET, MA Crash Intelligence Report: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/acushnet/november-2022-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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Acushnet, MA Crash Report — November 2022 | ThatCarHitMe.com