ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FITCHBURG, MA · JUNE 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/june-2022-report
Monthly Traffic Safety Analysis
81 CRASHES IN
FITCHBURG, MA
JUNE 2022
In June 2022, Fitchburg experienced 81 crashes, marking a 24.3% decrease compared to the 107 crashes recorded in June 2021. This notable year-over-year shift indicates a significant reduction in overall crash incidents.
81
▼ -24.3%was 107
Total Crash Events
0
Persons Killed
18
▼ -5.3%was 19
Persons Injured
0
▼ -100.0%was 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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Fitchburg showed a declining trend year-over-year, decreasing from 107 crashes in June 2021 to 81 crashes in June 2022, representing a 24.3% reduction. Total injuries also saw a slight decrease, from 19 in June 2021 to 18 in June 2022, a 5.3% reduction.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
17
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Wednesday in June 2021, with 25 incidents, to Thursday in June 2022, with 17 incidents. While the peak hour remained 4 p.m. in both periods, the number of crashes at this hour decreased from 12 in June 2021 to 10 in June 2022. Crashes on Sundays decreased by 50%, from 16 in June 2021 to 8 in June 2022, and Wednesday crashes decreased by 52%, from 25 to 12.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities in either period. Serious injuries (Severity A) increased by 100%, from 1 in June 2021 to 2 in June 2022, and accounted for a larger share of crashes (2.5%) compared to 0.9% previously. Minor injuries (Severity B) increased from 7 to 8, while possible injuries (Severity C) decreased by 50%, from 6 to 3.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Followed too closely,' decreased in count by 7 crashes, from 16 in June 2021 to 9 in June 2022, and its share of crashes decreased from 15% to 11.1%. 'Inattention' increased by 1 crash, from 14 to 15, and its share rose from 13.1% to 18.5%. 'Disregarded traffic signs, signals, road markings' saw a 150% increase in count, from 2 crashes in June 2021 to 5 crashes in June 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 95 in June 2021 to 72 in June 2022. Similarly, crashes during 'Daylight' decreased from 87 to 72, and those on 'Dry' road surfaces decreased from 102 to 77. The proportion of crashes occurring under these generally favorable conditions remained dominant in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The age distribution of persons involved in crashes showed notable shifts, with persons aged 21-25 decreasing by 41.4% (from 29 to 17) and those aged 45-54 decreasing by 54.1% (from 37 to 17). Conversely, persons aged 65+ increased by 15.4%, from 13 to 15. Among vehicle makes, Ford saw a decrease of 13 vehicles involved (from 25 to 12), while Honda increased by 5 vehicles (from 18 to 23).
Top Vehicle Makes (139 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (146 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed limit zone decreased by 11 incidents, from 46 in June 2021 to 35 in June 2022. The 30 mph zone also saw a reduction of 6 crashes, from 27 to 21. Conversely, crashes in the 55 mph zone increased by 3 incidents, from 2 to 5, representing a 150% increase. There were no fatal crashes reported in any speed limit zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: FITCHBURG, MA
- Total crash records analyzed: 81
- Total persons involved: 159
- Total vehicles involved: 139
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: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/june-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: 2022-06-01 – 2022-06-30
Generated: June 21, 2026 · All rights reserved