Monthly Traffic Safety Analysis

16 CRASHES IN
WESTMINSTER, MA
SEPTEMBER 2022

All metrics benchmarked againstSeptember 2021

Total crashes in WESTMINSTER increased from 14 in September 2021 to 16 in September 2022, representing a 14.3% increase year-over-year. Despite this rise in total incidents, the number of total injuries decreased by 33.3%, falling from 6 to 4. A notable shift was the increase in crashes attributed to 'Followed too closely,' which rose from 0 to 3 incidents.

16

14.3%was 14

Total Crash Events

0

Persons Killed

4

-33.3%was 6

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in WESTMINSTER increased by 14.3% from 14 in September 2021 to 16 in September 2022. During the same period, total injuries decreased by 33.3%, falling from 6 to 4, while total fatalities remained unchanged at 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 6-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Tuesday with 5 crashes in September 2021 to both Monday and Wednesday with 4 crashes each in September 2022. The peak crash hour also changed significantly, shifting from 2 PM with 5 crashes in the prior period to 7 AM with 3 crashes in the current period, indicating a shift towards earlier morning incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both September 2021 and September 2022. While total injuries decreased from 6 to 4 year-over-year, the current period saw the emergence of 1 serious injury crash, which was not present in the prior period. The proportion of crashes resulting in any injury increased slightly from 21.4% (3 of 14 crashes) in the prior period to 25.0% (4 of 16 crashes) in the current period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.3%
Minor Injury3minor injury crashes18.8%
0.0%prior 3
No Injury11no injury crashes68.8%
10.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Most severe injury per crash record

Top Contributing Factors

The most significant shift in contributing factors was the rise of 'Followed too closely' crashes, increasing from 0 in September 2021 to 3 in September 2022, making it the most cited factor in the current period. Conversely, 'Distracted' driving crashes, which accounted for 3 incidents in the prior period, were not reported in the current period's data. 'No improper driving' and 'Inattention' also decreased, from 3 to 2 crashes each.

Officer-Reported Primary Contributing Cause

Followed too closely3 (18.8%)
No improper driving2 (12.5%)
Inattention2 (12.5%)
Other improper action2 (12.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.3%)
Failed to yield right of way1 (6.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (6.3%)
Exceeded authorized speed limit1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions increased from 2 incidents (14.3% of total crashes) in September 2021 to 6 incidents (37.5% of total crashes) in September 2022. Similarly, crashes on wet road surfaces increased from 1 incident (7.1%) in the prior period to 5 incidents (31.3%) in the current period. The lighting conditions data for the prior period is unavailable for comparison.

Weather

Clear10 (62.5%)
-16.7%prior 12
Rain3 (18.8%)
Cloudy1 (6.3%)
Cloudy/Rain1 (6.3%)
Rain/Cloudy1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Weather condition at time of crash

Lighting

Daylight14 (87.5%)
Dark - roadway not lighted2 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Lighting condition field

Road Surface

Dry11 (68.8%)
-8.3%prior 12
Wet5 (31.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (31 vehicles)

1
HONDA5 (16.1%)
2
SUBARU3 (9.7%)
3
CHEVROLET3 (9.7%)
4
AUDI2 (6.5%)
5
DODGE2 (6.5%)
6
NISSAN2 (6.5%)
7
JEEP1 (3.2%)
8
MAZDA1 (3.2%)
9
MERCURY1 (3.2%)
10
TOYOTA1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Vehicle unit records

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

Sex Distribution (31 persons with recorded sex)

Male17 (54.8%)
-41.4%prior 29
Female14 (45.2%)
-50.0%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · Person-level records linked to crash events

Speed Limit Zones

There was a notable shift in crash distribution across speed zones year-over-year. Crashes in 30 mph zones decreased from 6 to 3, and in 40 mph zones from 3 to 1. Conversely, crashes in 55 mph zones increased significantly from 1 to 5, and 45 mph zones saw 2 crashes in the current period where none were recorded in the prior period, indicating a shift towards crashes occurring in higher speed limit areas.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-09-01 to 2022-09-30 · 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: 2022-09-01 through 2022-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-09-01 through 2022-09-30 (30 days)
  • Geographic scope: WESTMINSTER, MA
  • Total crash records analyzed: 16
  • Total persons involved: 37
  • Total vehicles involved: 31

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). "WESTMINSTER, MA Crash Intelligence Report: September 2022." Published June 21, 2026. Reporting period: 2022-09-01 to 2022-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westminster/september-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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Westminster, MA Crash Report — September 2022 | ThatCarHitMe.com