ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GARDNER, MA · 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/2024-annual-report
Yearly Traffic Safety Analysis
568 CRASHES IN
GARDNER, MA
2024
In 2024, Gardner recorded 568 total crashes, a 30.9% increase from the 434 crashes in 2023. Despite the rise in total collisions, the number of people killed decreased from four to two, and total injuries fell from 106 to 90. The most notable year-over-year shift was the substantial increase in non-injury crashes, which rose from 325 in the prior period to 462 in the current period.
568
▲ 30.9%was 434
Total Crash Events
2
▼ -50.0%was 4
Persons Killed
90
▼ -15.1%was 106
Persons Injured
32
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 29 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash incidents in Gardner showed a notable upward trend, increasing from 434 in 2023 to 568 in 2024, a rise of 30.9%. In contrast to the increase in total crashes, the number of resulting injuries decreased by 15.1% from 106 to 90. Similarly, traffic fatalities were halved, dropping from four in the prior year to two in the current year.
32
Hit-and-Run Crashes — 2024
▼ 0.0% vs prior (32)
The total number of hit-and-run crashes remained unchanged year-over-year, with 32 incidents recorded in both 2023 and 2024. However, due to the overall increase in total crashes in 2024, the hit-and-run rate decreased. The rate fell from 7.4% of all crashes in 2023 to 5.6% in 2024, indicating a downward trend in the proportion of crashes involving a driver leaving the scene.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
7
Pedestrians Injured
4
Cyclists Injured
79
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Friday (83 crashes) in 2023 to Thursday (98 crashes) in 2024. The peak hour for collisions remained the 3 p.m. hour in both years, but the volume of crashes during this time increased significantly from 39 to 65.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased in 2024 compared to the previous year. The number of fatal crashes fell from 3 to 2, and their share of total crashes dropped from 0.7% to 0.4%. The proportion of crashes resulting in minor injuries also declined from 12.4% to 9.3%. Conversely, the share of non-injury crashes grew from 74.9% of all incidents in 2023 to 81.3% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors cited in crashes remained consistent across both years, with 'Inattention' being the most common. The count of crashes attributed to inattention rose from 134 in 2023 to 164 in 2024, an increase of 22.4%. 'Failed to yield right of way' remained a leading cause, with the count of associated crashes increasing by 64.8% from 54 to 89. Crashes attributed to 'Failure to keep in proper lane or running off road' also saw a notable increase in count, rising from 15 to 25 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of environmental conditions during crashes remained largely stable year-over-year. In both 2023 and 2024, the vast majority of collisions occurred in 'Daylight' conditions, accounting for 72.6% and 74.3% of crashes, respectively. Crashes on 'Dry' road surfaces and during 'Clear' weather were also predominant in both periods, with no significant proportional shifts toward adverse conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes were consistent, with Toyota and Ford leading in both 2023 and 2024. In 2024, Toyota involvements increased from 115 to 156, and Ford from 87 to 127. Regarding the age of persons involved, the 65+ age group saw the most significant change, with involvement increasing from 99 individuals in 2023 to 189 in 2024, making it the most frequently involved age group in the current year.
Top Vehicle Makes (1,016 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
181 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,057 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased across most speed zones, with the largest absolute rise occurring in 30 mph zones, from 201 to 222 incidents. The most significant proportional growth was seen in 20 mph zones, where crashes increased from 71 to 118. Fatal crashes shifted to higher speed zones in 2024, with two fatalities occurring in zones of 40 mph and 50 mph, whereas 2023 saw one fatal crash in a 30 mph zone.
Fatal crashes by zone: 40 mph: 1 of 28 (3.571%) · 50 mph: 1 of 10 (10%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: GARDNER, MA
- Total crash records analyzed: 568
- Total persons involved: 1,245
- Total vehicles involved: 1,016
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gardner/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved