ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · MARCH 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/gardner/march-2022-report
Monthly Traffic Safety Analysis
36 CRASHES IN
GARDNER, MA
MARCH 2022
In March 2022, Gardner experienced 36 crashes, a slight decrease of 2.7% compared to the 37 crashes recorded in March 2021. A notable shift is the increase in fatalities, with 1 fatality in March 2022 compared to 0 in the prior year. Total injuries decreased by 50%, from 8 in March 2021 to 4 in March 2022.
36
▼ -2.7%was 37
Total Crash Events
1
Persons Killed
4
▼ -50.0%was 8
Persons Injured
3
▲ 200.0%was 1
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Gardner remained relatively stable, with a minor decrease of 2.7% from 37 crashes in March 2021 to 36 crashes in March 2022. However, the period saw a significant increase in crash severity, with total fatalities rising from 0 to 1, while total injuries decreased by 50% from 8 to 4.
3
Hit-and-Run Crashes — March 2022
▲ 200.0% vs prior (1)
Hit-and-run crashes increased significantly, from 1 crash in March 2021 to 3 crashes in March 2022, representing a 200% rise. Consequently, the hit-and-run crash rate also increased from 2.7% to 8.3% year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Pedestrians Injured
4
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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 Tuesday in March 2021 (8 crashes) to Monday in March 2022 (8 crashes). The peak hour also changed, moving from 3 PM with 7 crashes in March 2021 to 2 PM with 5 crashes in March 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased from 0% in March 2021 to 2.78% in March 2022, with 1 fatal crash recorded in the current period. Crashes resulting in minor injuries decreased by 60%, from 5 in March 2021 to 2 in March 2022, and possible injuries decreased by 66.7%, from 3 to 1. Conversely, crashes with no injuries increased by 8%, from 25 to 27.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' remained constant at 9 crashes in both periods. 'Inattention' crashes decreased from 7 in March 2021 to 5 in March 2022, a 28.6% reduction in count. Notably, 'Driving too fast for conditions' appeared as a contributing factor in 5 crashes in March 2022, compared to its absence in the top factors for March 2021.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a notable shift in weather conditions, with crashes in clear weather decreasing by 37.1% from 35 in March 2021 to 22 in March 2022. Conversely, crashes occurring in snowy conditions increased significantly, with 7 crashes reported in snow and 3 in snow/blowing snow in March 2022, compared to none in March 2021. This corresponds to a 41.7% decrease in crashes on dry road surfaces (from 36 to 21) and an increase in crashes on snow (from 0 to 10) and ice (from 0 to 3) surfaces.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field
Vehicles & Demographics
Toyota became the most frequently involved vehicle make in March 2022 with 14 vehicles, a 133.3% increase from 6 in March 2021, while Chevrolet involvement decreased by 60% from 10 to 4. Regarding person demographics, the 0-15 age group saw a 133.3% increase in involvement, from 3 to 7, and the 65+ age group experienced a 50% decrease, from 10 to 5.
Top Vehicle Makes (60 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (58 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed limit zone remained constant at 16 crashes in both March 2021 and March 2022, but this zone saw a fatal crash in March 2022 (6.25% fatal rate) compared to none in March 2021. Crashes in the 20 mph zone increased by 133.3%, from 3 in March 2021 to 7 in March 2022, while crashes in the 5 mph zone decreased from 3 to 0.
Fatal crashes by zone: 30 mph: 1 of 16 (6.25%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-03-01 through 2022-03-31 (31 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 36
- Total persons involved: 72
- Total vehicles involved: 60
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). "GARDNER, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/march-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: 2022-03-01 – 2022-03-31
Generated: June 21, 2026 · All rights reserved