Monthly Traffic Safety Analysis

5 CRASHES IN
CHESHIRE, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, Cheshire experienced 5 total crashes, which is consistent with the 5 crashes recorded in April 2022, representing no change year-over-year. A notable shift is the 100% decrease in total injuries, falling from 2 in the prior period to 0 in the current period.

5

Total Crash Events

0

Persons Killed

0

-100.0%was 2

Persons Injured

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The total number of crashes remained stable year-over-year, with 5 crashes reported in both April 2023 and April 2022. While overall crash volume was unchanged, total injuries saw a significant decrease of 100%, dropping from 2 in April 2022 to 0 in April 2023.

1

Hit-and-Run Crashes — April 2023

0.0% vs prior (1)

The number of hit-and-run crashes remained stable, with 1 incident reported in both April 2023 and April 2022. Consequently, the hit-and-run rate also held steady at 20% for both periods.

When Crashes Happen

Temporal crash patterns shifted considerably between the two periods. In April 2022, the peak day for crashes was Monday with 4 incidents, whereas in April 2023, crashes were highest on Wednesday and Thursday, each with 2 incidents. The peak crash hour also changed from 10 PM with 1 incident in April 2022 to 12 PM with 2 incidents in April 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Top Contributing Factors

The contributing factors for crashes showed significant changes year-over-year. Factors such as 'Exceeded authorized speed limit,' 'Failed to yield right of way,' and 'Other improper action' each decreased from 1 crash in April 2022 to 0 in April 2023. Conversely, 'Followed too closely,' 'Over-correcting/over-steering,' 'Physical impairment,' and 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' each increased from 0 crashes in April 2022 to 1 crash in April 2023.

Officer-Reported Primary Contributing Cause

Followed too closely1 (20%)
No improper driving1 (20%)
Over-correcting/over-steering1 (20%)
Physical impairment1 (20%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (20%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Regarding lighting conditions, both periods recorded 4 crashes occurring in Daylight. However, crashes in 'Dark - lighted roadway' increased from 0 in April 2022 to 1 in April 2023, while crashes in 'Dark - roadway not lighted' decreased from 1 in April 2022 to 0 in April 2023. Weather and road surface condition data for the prior period are not available for comparison.

Weather

Clear3 (60.0%)
Cloudy2 (40.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight4 (80.0%)
Dark - lighted roadway1 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (9 vehicles)

1
FORD3 (33.3%)
2
TOYOTA2 (22.2%)
3
CHEVROLET1 (11.1%)
4
HONDA1 (11.1%)
5
SUBARU1 (11.1%)
6
VOLKSWAGEN1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

Sex Distribution (10 persons with recorded sex)

Male6 (60.0%)
100.0%prior 3
Female4 (40.0%)
33.3%prior 3

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crash distribution across speed zones shifted year-over-year, with crashes moving from higher to lower speed limits. In April 2023, crashes were recorded at 15 mph (1 crash) and 30 mph (1 crash), which were not present in April 2022. Conversely, crashes at 25 mph (1 crash) and 50 mph (2 crashes) in April 2022 were absent in April 2023, indicating a shift away from these higher speed zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: CHESHIRE, MA
  • Total crash records analyzed: 5
  • Total persons involved: 10
  • 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). "CHESHIRE, MA Crash Intelligence Report: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/cheshire/april-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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Cheshire, MA Crash Report — April 2023 | ThatCarHitMe.com