ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · APRIL 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/april-2024-report
Monthly Traffic Safety Analysis
35 CRASHES IN
GARDNER, MA
APRIL 2024
Total crashes in Gardner increased by 66.67% from 21 in April 2023 to 35 in April 2024. This notable rise in overall crash incidents occurred alongside a 60% decrease in total injuries, falling from 10 to 4. Despite the increase in crashes, there were no fatalities reported in either period.
35
▲ 66.7%was 21
Total Crash Events
0
Persons Killed
4
▼ -60.0%was 10
Persons Injured
3
▲ 200.0%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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a significant increase in crash incidents year-over-year, with total crashes rising from 21 in April 2023 to 35 in April 2024. This represents a 66.67% increase in crash volume. Conversely, total injuries decreased by 60% during the same period, from 10 to 4.
3
Hit-and-Run Crashes — April 2024
▲ 200.0% vs prior (1)
Hit-and-run crashes increased from 1 in April 2023 to 3 in April 2024, representing a 200% increase in count. The hit-and-run crash rate also rose from 4.8% of total crashes in April 2023 to 8.6% in April 2024. This indicates an upward trend in both the number and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
2
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak day moving from Saturday in April 2023 (7 crashes) to Thursday in April 2024 (10 crashes). The peak hour for crashes also changed, from 1 PM (3 crashes) in the prior period to 4 PM (5 crashes) in the current period. Crashes on Mondays, Tuesdays, and Thursdays saw notable increases in count, while Saturday crashes decreased from 7 to 2.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either April 2023 or April 2024. The number of crashes resulting in injuries decreased from 6 in April 2023 to 4 in April 2024. Consequently, the total number of injured persons also decreased, from 10 in April 2023 to 4 in April 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
Inattention remained a leading contributing factor, increasing from 6 crashes in April 2023 to 8 crashes in April 2024, a 33.3% increase in count. 'No improper driving' saw a significant increase, rising from 2 crashes to 7 crashes, a 250% increase in count, and its rank changed from fourth to second. Conversely, 'Failure to keep in proper lane or running off road' decreased from 4 crashes to 1 crash, a 75% decrease in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 15 to 17, though their share of total crashes decreased from 71.4% to 48.6%. Crashes during adverse weather conditions, including snow, sleet, and rain, increased from 2 in the prior period to 7 in the current period. Similarly, crashes on adverse road surfaces (wet, snow, ice) increased from 4 to 11, indicating a higher proportion of crashes occurring under these conditions in April 2024.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (63 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (72 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 20 mph zones saw a substantial increase, rising from 2 in April 2023 to 11 in April 2024. Crashes in 30 mph zones also increased from 12 to 14 year-over-year. The current period's data included crashes in 5 mph, 15 mph, 25 mph, 40 mph, and 50 mph zones, which were not present in the prior period's data, suggesting a broader distribution of crashes across various speed limits. No fatalities were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 35
- Total persons involved: 86
- Total vehicles involved: 63
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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/april-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: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved