ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CANTON, MA · APRIL 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/canton/april-2023-report
Monthly Traffic Safety Analysis
34 CRASHES IN
CANTON, MA
APRIL 2023
In April 2023, Canton experienced 34 total crashes, an increase of 13.33% compared to the 30 crashes recorded in April 2022. The most significant year-over-year shift was the increase in total fatalities, rising from 0 in April 2022 to 1 in April 2023.
34
▲ 13.3%was 30
Total Crash Events
1
Persons Killed
6
▼ -50.0%was 12
Persons Injured
2
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Canton increased year-over-year, with total crashes rising from 30 to 34, representing a 13.33% increase. Fatalities saw a concerning increase from 0 to 1, while total injuries decreased by 50%, from 12 in April 2022 to 6 in April 2023.
2
Hit-and-Run Crashes — April 2023
5.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
1
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday (7 crashes) in April 2022 to Friday (8 crashes) in April 2023. The peak hour for crashes also shifted from 5 PM (4 crashes) in April 2022 to 4 PM (6 crashes) in April 2023. Crashes occurring on Tuesdays significantly increased from 2 in the prior period to 7 in the current period.
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)
Crash Severity Breakdown
The fatal crash rate increased from 0% in April 2022 to 2.9% in April 2023, corresponding to an increase from 0 to 1 fatal crash. Injury crashes collectively decreased, with minor injuries falling from 4 to 2 crashes and possible injuries decreasing from 4 to 1 crash. Conversely, crashes with no injuries rose from 21 (70% share) to 29 (85.3% share) of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record
Top Contributing Factors
Among common contributing factors, 'No improper driving' increased by 4 crashes, from 7 to 11, marking a 57.14% increase in count. 'Followed too closely' rose by 2 crashes, from 4 to 6, a 50% increase in count. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 2 crashes, from 3 to 1, representing a 66.67% decrease in count. 'Inattention' appeared as a factor in 3 crashes in April 2023, while it was not among the top factors in April 2022.
Officer-Reported Primary Contributing Cause
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
Crashes occurring in 'Clear' weather conditions slightly decreased from 20 to 19, while those in 'Cloudy' conditions increased from 3 to 7. Crashes on 'Wet' road surfaces saw a substantial increase from 4 in April 2022 to 10 in April 2023. The number of crashes occurring in 'Dark - lighted roadway' conditions doubled from 3 to 6 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 69 to 77 year-over-year. The 35-44 age group saw the largest increase, rising from 9 to 15 persons, while the 65+ age group experienced a decrease from 9 to 4 persons. The representation of male persons increased from 35 to 49, while female persons decreased from 30 to 24.
Top Vehicle Makes (62 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (73 persons with recorded sex)
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
Crashes in 55 mph speed zones saw a significant increase, rising from 4 in April 2022 to 10 in April 2023. While 65 mph zones had 7 crashes in both periods, a fatal crash occurred in a 65 mph zone in April 2023, whereas no fatal crashes were recorded in any speed zone in April 2022. Crashes in 30 mph zones decreased from 3 to 1, and in 35 mph zones from 4 to 2.
Fatal crashes by zone: 65 mph: 1 of 7 (14.286%)
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: CANTON, MA
- Total crash records analyzed: 34
- Total persons involved: 77
- Total vehicles involved: 62
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: 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/canton/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-04-01 – 2023-04-30
Generated: June 21, 2026 · All rights reserved