Monthly Traffic Safety Analysis

9 CRASHES IN
AYER, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

November 2022 saw 9 total crashes in AYER, MA, marking a 28.6% increase from the 7 crashes reported in November 2021. The most notable shift was the emergence of DUI-related crashes, which increased from 0 in the prior period to 2 in the current period. Despite the increase in total crashes, fatalities remained at 0 in both periods.

9

28.6%was 7

Total Crash Events

0

Persons Killed

1

-66.7%was 3

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 · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in AYER, MA showed an upward trend year-over-year, increasing by 28.6% from 7 crashes in November 2021 to 9 crashes in November 2022. While fatalities remained at 0 in both periods, total injuries decreased by 66.7%, from 3 in November 2021 to 1 in November 2022. This indicates a rise in crash frequency but a decrease in injury severity.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

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 distribution of crashes shifted significantly year-over-year. In November 2021, the peak day for crashes was Saturday with 3 incidents, and the peak hour was 11p with 1 incident. In contrast, November 2022 saw Tuesday as the peak day with 4 crashes, and 7a as the peak hour with 2 crashes, indicating a shift in crash timing from weekends/late nights to weekdays/mornings.

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

Crash severity patterns changed between the two periods, though no fatalities occurred in either November 2021 or November 2022. Minor injury crashes decreased from 3 incidents (42.9% of crashes) in November 2021 to 1 incident (11.1% of crashes) in November 2022. Concurrently, crashes resulting in no injuries increased from 4 incidents (57.1% of crashes) to 8 incidents (88.9% of crashes) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes11.1%
-66.7%prior 3
No Injury8no injury crashes88.9%
100.0%prior 4

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 contributing factors to crashes showed shifts year-over-year. "No improper driving" remained consistent with 2 crashes in both periods. "Inattention" crashes increased from 1 in November 2021 to 2 in November 2022, while "Disregarded traffic signs, signals, road markings" was present with 1 crash in November 2021 but absent in November 2022. Additionally, factors like "Failed to yield right of way" and "Followed too closely" emerged in November 2022, each contributing to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving2 (22.2%)
Inattention2 (22.2%)
Failed to yield right of way1 (11.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (11.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (11.1%)
Followed too closely1 (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

Crash conditions saw changes primarily in weather and lighting, as road surface data was unavailable for November 2022. Crashes occurring in clear weather increased from 4 in November 2021 to 8 in November 2022, while crashes in rainy conditions (Rain, Rain/Sleet) decreased from 3 to 0. Daylight crashes increased from 3 to 5, and dawn crashes increased from 0 to 2 year-over-year, suggesting a shift towards crashes in clear, daylight/dawn conditions.

Weather

Clear8 (88.9%)
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

Daylight5 (55.6%)
Dark - roadway not lighted2 (22.2%)
Dawn2 (22.2%)

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 (17 vehicles)

1
FORD5 (29.4%)
2
SUBARU4 (23.5%)
3
TOYOTA2 (11.8%)
4
CHEVROLET1 (5.9%)
5
MACK1 (5.9%)
6
MAZDA1 (5.9%)
7
JEEP1 (5.9%)
8
HD1 (5.9%)
9
HYUNDAI1 (5.9%)

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

Sex Distribution (18 persons with recorded sex)

Male13 (72.2%)
225.0%prior 4
Female5 (27.8%)
-54.5%prior 11

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

Crashes across different speed zones showed varied changes. Crashes at 25 mph decreased from 2 in November 2021 to 1 in November 2022, while those at 30 mph increased from 2 to 3, and 35 mph crashes increased from 1 to 3. Notably, 2 crashes occurred in 40 mph zones in November 2022, a category not present in November 2021, and crashes in 5 mph and 45 mph zones observed in November 2021 were absent in November 2022. Fatal crashes remained at 0 in all speed zones for both periods.

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: AYER, MA
  • Total crash records analyzed: 9
  • Total persons involved: 18
  • Total vehicles involved: 17

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). "AYER, 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/ayer/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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Ayer, MA Crash Report — November 2022 | ThatCarHitMe.com