ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · MARCH 2024
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-2024-report
Monthly Traffic Safety Analysis
49 CRASHES IN
GARDNER, MA
MARCH 2024
Total crashes in Gardner decreased slightly from 51 in March 2023 to 49 in March 2024, representing a 3.9% reduction year-over-year. Despite the overall decrease, crashes occurring in 20 mph speed zones saw a notable increase from 7 crashes in the prior period to 12 crashes in the current period, marking a 71.4% rise. Fatalities remained at zero in both periods, while total injuries held steady at 9.
49
▼ -3.9%was 51
Total Crash Events
0
Persons Killed
9
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in Gardner shows a slight decrease in total crashes, falling from 51 in March 2023 to 49 in March 2024, a reduction of 3.9%. Both total fatalities and total injuries remained stable year-over-year, with zero fatalities and 9 injuries recorded in both March 2023 and March 2024.
2
Hit-and-Run Crashes — March 2024
▼ 0.0% vs prior (2)
The number of hit-and-run crashes remained stable at 2 incidents in both March 2023 and March 2024. However, the hit-and-run rate slightly increased from 3.9% of total crashes in the prior period to 4.1% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
9
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 Wednesday with 10 crashes in March 2023 to Saturday with 12 crashes in March 2024. The peak crash hour also changed, moving from 2 PM with 8 crashes in the prior period to 1 PM with 7 crashes in the current period. This indicates a shift in the timing of peak crash activity.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity showed some shifts year-over-year, though total injuries remained at 9 in both periods. Serious injuries (code A) increased from 0 in March 2023 to 1 in March 2024, while minor injuries (code B) decreased from 4 to 2. Possible injuries (code C) increased from 2 to 4 between the two periods.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Inattention' decreased from 19 crashes in March 2023 to 16 crashes in March 2024, a reduction of 3 crashes. 'No improper driving' saw a larger decrease, falling from 13 crashes to 8 crashes, a decrease of 5 crashes. Conversely, 'Failed to yield right of way' increased from 3 crashes to 5 crashes, an increase of 2 crashes, and 'Driving too fast for conditions' remained stable at 4 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather decreased from 31 in March 2023 to 22 in March 2024, while crashes in 'Rain' conditions increased from 2 to 6. Regarding lighting, crashes during 'Daylight' decreased from 42 to 37, but crashes in 'Dark - roadway not lighted' conditions increased from 2 to 6. On road surfaces, crashes on 'Snow' decreased significantly from 11 to 3, while 'Ice' conditions accounted for 4 crashes in March 2024, having not been present in March 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased slightly from 89 in March 2023 to 86 in March 2024. Toyota became the most frequently involved make, increasing from 11 vehicles in March 2023 to 14 in March 2024, while Ford and Chevrolet counts decreased from 14 each to 11 and 8 respectively. Subaru also saw an increase, moving from 3 vehicles to 8, entering the top five makes.
Top Vehicle Makes (86 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (86 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones decreased from 19 in March 2023 to 15 in March 2024. Conversely, crashes in 20 mph speed zones increased from 7 to 12 over the same period. There were no fatal crashes reported in any speed zone in either March 2023 or March 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-03-01 through 2024-03-31 (31 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 49
- Total persons involved: 97
- Total vehicles involved: 86
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 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/march-2024-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: 2024-03-01 – 2024-03-31
Generated: June 21, 2026 · All rights reserved