Monthly Traffic Safety Analysis

30 CRASHES IN
AVON, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, AVON experienced 30 total crashes, a 16.67% decrease from the 36 crashes recorded in October 2022. The most notable year-over-year shift was a 50% reduction in total injuries, decreasing from 12 in the prior period to 6 in the current period.

30

-16.7%was 36

Total Crash Events

0

Persons Killed

6

-50.0%was 12

Persons Injured

4

300.0%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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crashes in AVON decreased from 36 in October 2022 to 30 in October 2023, representing a 16.67% reduction. This indicates a declining trend in total crash incidents year-over-year for the month of October.

4

Hit-and-Run Crashes — October 2023

300.0% vs prior (1)

Hit-and-run crashes increased from 1 incident in October 2022 to 4 incidents in October 2023, marking a 300% increase in count. Consequently, the hit-and-run rate rose from 2.8% of total crashes in the prior period to 13.3% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 12-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

In October 2023, the peak day for crashes was Thursday with 7 incidents, shifting from Saturday with 10 incidents in October 2022. The peak hour also changed from 5 PM with 4 crashes in October 2022 to 7 AM with 4 crashes in October 2023, indicating a shift in the timing of peak crash activity.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries decreased by 50%, from 12 in October 2022 to 6 in October 2023. While both periods reported no fatalities, serious injuries (Severity A) were present in October 2022 with 2 incidents (5.6% share of crashes) but were absent in October 2023. Minor injuries (Severity B) decreased from 5 incidents (13.9% share) to 1 incident (3.3% share), and possible injuries (Severity C) increased from 2 incidents (5.6% share) to 4 incidents (13.3% share).

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes3.3%
-80.0%prior 5
Possible Injury4possible injury crashes13.3%
100.0%prior 2
No Injury25no injury crashes83.3%
-7.4%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor, "No improper driving," increased slightly from 11 incidents in October 2022 to 12 in October 2023. "Followed too closely" incidents decreased significantly by 80% in count, from 10 in the prior period to 2 in the current period. Conversely, "Inattention" incidents increased from 3 in October 2022 to 4 in October 2023.

Officer-Reported Primary Contributing Cause

No improper driving12 (40%)9.1%prior 11
Inattention4 (13.3%)
Failure to keep in proper lane or running off road3 (10%)
Failed to yield right of way3 (10%)
Followed too closely2 (6.7%)-80.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.3%)
Visibility obstructed1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 18 in October 2022 to 21 in October 2023, while crashes in rain decreased from 5 to 2. Crashes on wet road surfaces decreased from 7 to 2 year-over-year. Incidents occurring in daylight decreased from 23 to 17, while those in dark but lighted roadways decreased from 10 to 6.

Weather

Clear21 (70.0%)
16.7%prior 18
Clear/Other3 (10.0%)
Rain2 (6.7%)
-60.0%prior 5
Fog, smog, smoke1 (3.3%)
Clear/Unknown1 (3.3%)
-80.0%prior 5
Clear/Cloudy1 (3.3%)
Cloudy1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight17 (56.7%)
-26.1%prior 23
Dark - lighted roadway6 (20.0%)
-40.0%prior 10
Dark - roadway not lighted6 (20.0%)
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry28 (93.3%)
-3.4%prior 29
Wet2 (6.7%)
-71.4%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 71 in October 2022 to 60 in October 2023. Toyota, Honda, and Ford remained among the top vehicle makes involved in crashes across both periods. Toyota's involvement remained constant at 10 vehicles, while Honda's and Ford's decreased from 10 to 7 vehicles each.

Top Vehicle Makes (60 vehicles)

1
TOYOTA10 (16.7%)
0.0%prior 10
2
JEEP7 (11.7%)
40.0%prior 5
3
FORD7 (11.7%)
-30.0%prior 10
4
HONDA7 (11.7%)
-30.0%prior 10
5
NISSAN5 (8.3%)
6
CHEVROLET5 (8.3%)
-28.6%prior 7
7
KIA2 (3.3%)
8
VOLKSWAGEN2 (3.3%)
9
SUZI1 (1.7%)
10
ACURA1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (53 persons with recorded sex)

Male33 (62.3%)
-28.3%prior 46
Female20 (37.7%)
-37.5%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones decreased from 19 in October 2022 to 8 in October 2023, representing a 57.9% reduction. Crashes in 30 mph zones increased from 6 to 8, and in 40 mph zones from 6 to 7. No fatalities were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: AVON, MA
  • Total crash records analyzed: 30
  • Total persons involved: 64
  • Total vehicles involved: 60

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). "AVON, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/avon/october-2023-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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Avon, MA Crash Report — October 2023 | ThatCarHitMe.com