ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, 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/fitchburg/april-2022-report
Monthly Traffic Safety Analysis
93 CRASHES IN
FITCHBURG, MA
APRIL 2022
In April 2022, Fitchburg experienced 93 crashes, an increase from 86 crashes in April 2021. This represents an 8.1% rise in overall crash incidents year-over-year. A notable shift includes a significant increase in crashes attributed to "Inattention," rising from 7 to 19 incidents.
93
▲ 8.1%was 86
Total Crash Events
0
Persons Killed
24
▲ 14.3%was 21
Persons Injured
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. 6 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 Fitchburg increased year-over-year, with 93 crashes reported in April 2022 compared to 86 in April 2021. This marks an 8.1% rise in total crashes. The data indicates a slight upward trend in crash frequency for this period.
2
Hit-and-Run Crashes — April 2022
2.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
22
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 remained Friday in both April 2022 (25 crashes) and April 2021 (21 crashes), and the peak hour was consistently 4 PM with 10 crashes in both periods. However, crashes occurring at 8 PM saw a significant increase from 0 in April 2021 to 9 in April 2022, indicating a shift in evening crash patterns. Thursday crashes decreased from 14 to 7, while Sunday crashes increased from 3 to 6.
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
Total injuries increased from 21 in April 2021 to 24 in April 2022, a 14.3% rise. While serious injuries (code A) decreased from 3 to 1, minor injuries (code B) significantly increased from 7 to 16 incidents. There were no reported fatalities in either April 2021 or April 2022.
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
Crashes attributed to "Inattention" saw a substantial increase, rising from 7 in April 2021 to 19 in April 2022, a 171.4% increase in count. Conversely, "Other improper action" decreased from 12 crashes to 8, and "Visibility obstructed" decreased from 3 to 1 crash. "No improper driving" remained stable with 20 crashes in both periods.
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 in "Clear" weather conditions increased from 54 to 70 incidents year-over-year, while crashes during "Cloudy" conditions decreased from 10 to 3. Crashes in "Daylight" conditions decreased from 77 to 71, whereas crashes in "Dark - lighted roadway" conditions more than doubled, rising from 5 to 14. "Dry" road surface conditions saw an increase from 71 to 77 crashes.
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 increased from 155 in April 2021 to 160 in April 2022. TOYOTA remained the top make involved, increasing from 23 to 29 vehicles, while HONDA decreased from 21 to 16 vehicles. Regarding persons involved, the 0-15 age group saw a substantial increase from 7 to 17 individuals, and the 45-54 age group also rose significantly from 15 to 27 individuals.
Top Vehicle Makes (160 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (186 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
The 25 mph speed limit zone remained the most frequent location for crashes, with 42 incidents in both April 2021 and April 2022. Crashes in the 30 mph zone saw a notable decrease from 25 to 15, while those in the 20 mph zone increased from 3 to 10. There were no reported fatalities in any speed limit zone during either period.
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: FITCHBURG, MA
- Total crash records analyzed: 93
- Total persons involved: 200
- Total vehicles involved: 160
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). "FITCHBURG, 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/fitchburg/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