Monthly Traffic Safety Analysis

41 CRASHES IN
CANTON, MA
FEBRUARY 2023

All metrics benchmarked againstFebruary 2022

In February 2023, Canton experienced 41 total crashes, a 46.4% increase compared to 28 crashes in February 2022. The most notable shift was in crashes attributed to 'Failed to yield right of way,' which saw a 300% increase in count, rising from 2 to 8 crashes year-over-year.

41

46.4%was 28

Total Crash Events

0

Persons Killed

13

62.5%was 8

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Canton in February 2023 shows an upward trend compared to the same month in the prior year. Total crashes increased by 46.4%, from 28 to 41, while total injuries rose by 62.5%, from 8 to 13.

1

Hit-and-Run Crashes — February 2023

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 in both February 2023 and February 2022. However, the hit-and-run rate decreased from 3.6% in the prior period to 2.4% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 862.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with 10 crashes in February 2023 and 9 crashes in February 2022. The peak crash hour shifted from 7a in February 2022 to 6a in February 2023, with both hours recording 5 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either February 2023 or February 2022. The number of crashes resulting in serious injuries increased from 0 to 1, while minor injury crashes decreased from 7 to 2. Crashes with possible injuries saw a notable increase from 1 to 6.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.4%
Minor Injury2minor injury crashes4.9%
-71.4%prior 7
Possible Injury6possible injury crashes14.6%
500.0%prior 1
No Injury31no injury crashes75.6%
55.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Failed to yield right of way' increased significantly from 2 to 8, marking a 300% rise in count and an increase in share from 7.1% to 19.5%. Conversely, crashes due to 'Followed too closely' decreased by 3 in count, from 6 to 3, and its share fell from 21.4% to 7.3%. Crashes where 'No improper driving' was cited increased by 1 in count, from 11 to 12, but its share of total crashes decreased from 39.3% to 29.3%.

Officer-Reported Primary Contributing Cause

No improper driving12 (29.3%)9.1%prior 11
Failed to yield right of way8 (19.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (7.3%)
Driving too fast for conditions3 (7.3%)
Followed too closely3 (7.3%)-50.0%prior 6
Inattention3 (7.3%)
Over-correcting/over-steering1 (2.4%)
Made an improper turn1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 18 to 22, while those on dry road surfaces rose from 17 to 29. A notable shift was observed in lighting conditions, with crashes occurring in 'Dark - roadway not lighted' increasing from 1 to 6 year-over-year.

Weather

Clear22 (55.0%)
22.2%prior 18
Cloudy7 (17.5%)
Snow/Rain2 (5.0%)
Rain2 (5.0%)
Sleet, hail (freezing rain or drizzle)2 (5.0%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (2.5%)
Snow1 (2.5%)
Clear/Snow1 (2.5%)
Cloudy/Clear1 (2.5%)
Cloudy/Rain1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash

Lighting

Daylight24 (58.5%)
14.3%prior 21
Dark - lighted roadway7 (17.1%)
Dark - roadway not lighted6 (14.6%)
Dawn2 (4.9%)
Dusk2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field

Road Surface

Dry29 (70.7%)
70.6%prior 17
Wet6 (14.6%)
-14.3%prior 7
Ice4 (9.8%)
Snow2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 54 in February 2022 to 81 in February 2023. Toyota vehicles involved in crashes increased from 6 to 15, and Chevrolet vehicles saw a significant rise from 1 to 11. Honda, however, saw a decrease in involvement, from 14 vehicles to 9.

Top Vehicle Makes (81 vehicles)

1
TOYOTA15 (18.5%)
150.0%prior 6
2
CHEVROLET11 (13.6%)
3
HYUNDAI9 (11.1%)
80.0%prior 5
4
HONDA9 (11.1%)
-35.7%prior 14
5
FORD8 (9.9%)
6
GMC3 (3.7%)
7
SUBARU3 (3.7%)
8
NISSAN3 (3.7%)
9
MERCEDES-BENZ3 (3.7%)
10
VOLVO2 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records

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

Sex Distribution (91 persons with recorded sex)

Male60 (65.9%)
100.0%prior 30
Female31 (34.1%)
34.8%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 20 mph zones increased from 1 to 4, and those in 25 mph zones rose from 2 to 6. Similarly, crashes in 30 mph zones also increased from 2 to 6. Crashes in 35 mph zones decreased slightly from 3 to 2, while crashes in 65 mph zones remained stable at 8.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-02-01 through 2023-02-28 (28 days)
  • Geographic scope: CANTON, MA
  • Total crash records analyzed: 41
  • Total persons involved: 94
  • Total vehicles involved: 81

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). "CANTON, MA Crash Intelligence Report: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/canton/february-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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Canton, MA Crash Report — February 2023 | ThatCarHitMe.com