ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RANDOLPH, MA · APRIL 2022
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/randolph/april-2022-report
Monthly Traffic Safety Analysis
63 CRASHES IN
RANDOLPH, MA
APRIL 2022
In April 2022, RANDOLPH experienced 63 total crashes, a decrease of 4.5% compared to 66 crashes in April 2021. Total injuries also decreased from 13 to 11, representing a 15.4% reduction. A notable shift was the 300% increase in DUI-related crashes, rising from 1 in April 2021 to 4 in April 2022.
63
▼ -4.5%was 66
Total Crash Events
0
Persons Killed
11
▼ -15.4%was 13
Persons Injured
1
▼ -50.0%was 2
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. 36 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in RANDOLPH saw a slight decline year-over-year, with total crashes decreasing by 4.5% from 66 in April 2021 to 63 in April 2022. Similarly, total injuries decreased by 15.4%, from 13 to 11. Fatalities remained at zero in both periods.
1
Hit-and-Run Crashes — April 2022
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased from 2 incidents in April 2021 to 1 incident in April 2022. This represents a reduction in the hit-and-run rate from 3% to 1.6% of all crashes, indicating a downward trend year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Friday in April 2021, with 18 crashes, to Saturday in April 2022, with 16 crashes. The peak hour also changed, moving from 4 PM with 8 crashes in April 2021 to 6 PM with 6 crashes in April 2022. This indicates a shift in the most frequent crash times from late afternoon on weekdays to evening on weekends.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both April 2021 and April 2022. Total injuries decreased from 13 in the prior period to 11 in the current period, a 15.4% reduction. Notably, serious injuries, which accounted for 3 incidents in April 2021, were not reported in April 2022, while possible injuries increased from 2 to 4.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record
Top Contributing Factors
The most frequent contributing factor, 'Failed to yield right of way,' increased from 12 crashes in April 2021 to 14 crashes in April 2022, a 16.7% rise. 'Followed too closely' remained constant at 12 crashes in both periods. 'No improper driving' decreased by 28.6%, from 14 crashes to 10, while 'Inattention' crashes saw a substantial increase from 2 to 7, a 250% rise. Additionally, crashes attributed to 'Exceeded authorized speed limit' increased from 1 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions increased from 39 in April 2021 to 50 in April 2022, while crashes in rainy conditions decreased from 9 to 5. There was a notable shift in lighting conditions, with crashes occurring in 'Dark - lighted roadway' increasing from 3 to 15, and those in 'Dark - roadway not lighted' decreasing from 11 to 2. Crashes on dry road surfaces increased from 49 to 55, while those on wet surfaces decreased from 16 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 149 in April 2021 to 131 in April 2022. While Toyota remained a top make with 21 vehicles in both periods, Honda-involved crashes increased from 18 to 21, and Chevrolet-involved crashes increased from 9 to 14. Ford-involved crashes decreased significantly from 16 to 8. Regarding person demographics, there was a notable increase in persons aged 0-15 involved in crashes, rising from 1 to 9, while involvement in the 26-34, 35-44, 55-64, and 65+ age groups decreased.
Top Vehicle Makes (131 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (148 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones saw a significant increase, rising from 7 in April 2021 to 17 in April 2022. Similarly, crashes in 30 mph zones increased from 9 to 13. Conversely, crashes in 65 mph zones experienced a substantial decrease, falling from 19 to 7, indicating a shift of crashes from higher to lower speed limit areas. Fatalities remained at zero across all speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-04-01 through 2022-04-30 (30 days)
- Geographic scope: RANDOLPH, MA
- Total crash records analyzed: 63
- Total persons involved: 164
- Total vehicles involved: 131
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). "RANDOLPH, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/april-2022-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: 2022-04-01 – 2022-04-30
Generated: June 21, 2026 · All rights reserved