ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AUBURN, 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/auburn/april-2024-report
Monthly Traffic Safety Analysis
71 CRASHES IN
AUBURN, MA
APRIL 2024
In April 2024, AUBURN experienced 71 total crashes, a 65.1% increase compared to the 43 crashes recorded in April 2023. Total injuries also rose from 14 to 25, marking a 78.6% increase year-over-year. A notable shift was observed in speeding-related crashes, which increased from 0 in April 2023 to 11 in April 2024.
71
▲ 65.1%was 43
Total Crash Events
0
Persons Killed
25
▲ 78.6%was 14
Persons Injured
3
▲ 50.0%was 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.
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
Overall crash activity in AUBURN showed a significant upward trend year-over-year. Total crashes increased by 65.1%, rising from 43 in April 2023 to 71 in April 2024. Concurrently, the number of injured persons increased by 78.6%, from 14 to 25, while fatalities remained at zero in both periods.
3
Hit-and-Run Crashes — April 2024
▲ 50.0% vs prior (2)
The number of hit-and-run crashes increased from 2 in April 2023 to 3 in April 2024. However, the hit-and-run crash rate slightly decreased from 4.7% of total crashes in April 2023 to 4.2% in April 2024.
Vulnerable Road User Casualties
0
Motorists Killed
25
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. In April 2023, the peak day for crashes was Friday with 9 incidents, whereas in April 2024, Thursday became the peak day with 24 crashes. The peak hour also shifted from 2p with 6 crashes in April 2023 to 3p with 8 crashes in April 2024.
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
Fatal crashes remained at zero in both April 2023 and April 2024. The proportion of crashes resulting in any injury (serious, minor, or possible) decreased from 25.6% of total crashes in April 2023 to 19.7% in April 2024. However, the number of serious injury crashes increased from 0 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
Several contributing factors saw notable year-over-year changes in crash counts. Crashes attributed to 'Followed too closely' increased by 100%, from 9 incidents in April 2023 to 18 in April 2024, and its share of total crashes rose from 20.9% to 25.4%. 'Driving too fast for conditions' incidents increased significantly from 0 to 8 crashes. Conversely, crashes due to 'Failed to yield right of way' decreased by 44.4%, from 9 incidents to 5.
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
The distribution of crash conditions shifted significantly year-over-year, indicating a broader range of adverse conditions in April 2024. While 'Clear' weather crashes remained at 34, their proportion of total crashes decreased from 79.1% to 47.9%. Road surface conditions saw a substantial increase in 'Wet' crashes, rising by 175% from 4 to 11, and new categories like 'Ice,' 'Snow,' and 'Slush' appeared with 5, 5, and 4 crashes respectively in April 2024. Crashes occurring in 'Dark - lighted roadway' and 'Dark - roadway not lighted' conditions also increased by 125% and 166.7% respectively.
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
The vehicle makes involved in crashes saw a shift in prevalence, with TOYOTA and FORD showing significant increases in counts. TOYOTA-involved crashes rose from 6 to 25, and FORD-involved crashes increased from 7 to 20. HONDA-involved crashes slightly decreased from 12 to 10. Regarding persons involved, the 21-25 age group saw a substantial increase from 8 to 23 individuals, and the 26-34 age group increased from 11 to 28 individuals. Conversely, the 0-15 and 16-20 age groups saw decreases in persons involved.
Top Vehicle Makes (128 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (149 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 the 65 mph speed zone increased substantially from 8 incidents in April 2023 to 39 incidents in April 2024. Crashes in the 40 mph zone decreased from 14 to 12. There were no fatal crashes recorded in any speed zone during 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: AUBURN, MA
- Total crash records analyzed: 71
- Total persons involved: 154
- Total vehicles involved: 128
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). "AUBURN, 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/auburn/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