ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CANTON, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
491 CRASHES IN
CANTON, MA
2023
In 2023, Canton experienced 491 total traffic crashes, a 12.1% increase from the 438 crashes recorded in 2022. During this period, total injuries rose from 134 to 154, and one fatal crash occurred, compared to zero in the prior year. The most significant shift in contributing factors was a 94% increase in the count of crashes attributed to 'Followed too closely,' which rose from 51 incidents in 2022 to 99 in 2023.
491
▲ 12.1%was 438
Total Crash Events
1
Persons Killed
154
▲ 14.9%was 134
Persons Injured
29
▲ 38.1%was 21
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. 10 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Canton are rising year-over-year. Total crashes increased by 12.1%, from 438 in 2022 to 491 in 2023. This increase was accompanied by a 14.9% rise in total injuries (from 134 to 154) and an increase in fatalities from zero to one.
29
Hit-and-Run Crashes — 2023
▲ 38.1% vs prior (21)
Hit-and-run incidents increased in both count and as a proportion of total crashes. The number of hit-and-run crashes rose from 21 in 2022 to 29 in 2023, a 38.1% increase in count. The hit-and-run rate also trended upward, accounting for 5.9% of all crashes in 2023, compared to 4.8% in the prior year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
2
Pedestrians Injured
3
Cyclists Injured
148
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Monday (79 incidents) in 2022 to Thursday (89 incidents) in 2023. However, the peak hour for collisions remained consistent at the 8 a.m. hour in both years, with 44 crashes in 2022 and 43 in 2023. The afternoon commute hours from 2 p.m. to 5 p.m. also remained a period of high crash frequency in both years.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased in 2023 compared to the prior year. The city recorded one fatal crash in 2023, up from zero in 2022, raising the fatal crash rate from 0% to 0.2%. The count of serious injury crashes also grew from 5 to 9, increasing their share of total crashes from 1.1% to 1.8%. While the count of minor injury crashes slightly decreased from 60 to 57, possible injury crashes rose from 30 to 39.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors shifted between 2022 and 2023. The count of crashes attributed to 'Followed too closely' increased by 94%, rising from 51 incidents in 2022 to 99 in 2023; its share of total crashes grew from 11.6% to 20.2%. Similarly, the count for 'Driving too fast for conditions' more than doubled, increasing from 14 to 34 incidents. While 'No improper driving' was the most common finding in both years, its count decreased slightly from 175 to 169, and its overall share of crashes dropped from 40% to 34.4%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both 2022 and 2023 occurred in daylight on dry roads under clear skies. However, there was an increase in crashes under adverse conditions in 2023. The count of crashes on wet roads rose from 67 to 102, and collisions during rain increased from 34 to 43. While daylight crashes remained the most frequent, their proportion of the total slightly decreased from 69.6% in 2022 to 68.2% in 2023 as the total number of crashes grew.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford being the three most frequent in both 2022 and 2023. While Toyota and Honda held the top two spots, the number of Hondas involved increased from 112 to 122, while Toyotas decreased from 161 to 151. An analysis of persons involved in crashes shows notable increases in the 21-25 age group (from 103 to 140 persons) and the 35-44 age group (from 142 to 201 persons).
Top Vehicle Makes (935 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
48 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,027 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes appeared to shift towards higher speed zones in 2023. The number of collisions in 65 mph zones increased from 88 to 113, and this zone accounted for the year's only fatal crash. Similarly, crashes in 55 mph zones rose from 77 to 107. Conversely, crashes in the 45 mph zone decreased from 81 to 72. There were no fatal crashes recorded in any speed zone in 2022.
Fatal crashes by zone: 65 mph: 1 of 113 (0.885%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: CANTON, MA
- Total crash records analyzed: 491
- Total persons involved: 1,124
- Total vehicles involved: 935
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/canton/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved