ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AUBURN, 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/auburn/2024-annual-report
Yearly Traffic Safety Analysis
819 CRASHES IN
AUBURN, MA
2024
In 2024, Auburn recorded 819 total crashes, an 11.3% increase from the 736 crashes documented in 2023. While total fatalities decreased from two to one year-over-year, the number of crashes resulting in serious injuries increased from 3 in 2023 to 13 in 2024.
819
▲ 11.3%was 736
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
237
▲ 13.9%was 208
Persons Injured
46
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. 8 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 and injury totals in Auburn trended upward year-over-year. Total crashes increased by 11.3%, rising from 736 in 2023 to 819 in 2024. Similarly, the number of people injured rose by 13.9% from 208 to 237, while the number of fatalities declined from two to one.
46
Hit-and-Run Crashes — 2024
▼ 0.0% vs prior (46)
The total number of hit-and-run crashes in Auburn remained unchanged, with 46 incidents recorded in both 2023 and 2024. Due to the overall increase in total crashes in the current period, the hit-and-run rate saw a slight decrease. The rate fell from 6.3% of all crashes in 2023 to 5.6% in 2024.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
233
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 in Auburn remained consistent year-over-year. Friday was the peak day for crashes in both 2024 (141 crashes) and 2023 (136 crashes). The 3 PM hour also remained the most frequent time for collisions in both periods, accounting for 82 crashes in 2024 and 74 in 2023.
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
The severity of crashes shifted year-over-year, with a notable increase in injury-related incidents. While fatal crashes decreased from 2 in 2023 to 1 in 2024, serious injury crashes rose from 3 to 13. The proportion of crashes resulting in minor injuries also grew, from a 12.9% share (95 crashes) in 2023 to a 14.3% share (117 crashes) in 2024. Consequently, the share of no-injury crashes saw a slight decline from 77.6% to 76.9% of all collisions.
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 leading contributing factors to crashes remained largely consistent between 2023 and 2024, with 'Followed too closely,' 'No improper driving,' and 'Inattention' being the top three factors in both years. The count of crashes involving 'Inattention' rose by 16.2%, from 99 incidents in 2023 to 115 in 2024. Crashes where 'Driving too fast for conditions' was a factor increased by 36.4% in count, from 22 to 30 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
Crashes in both periods predominantly occurred in clear conditions on dry roads during daylight hours. In 2024, 75.8% of crashes happened in daylight, a slight increase from a 73.6% share in 2023. The proportion of crashes on wet roads decreased from 18.9% in 2023 to 15.6% in 2024. However, crashes on snowy road surfaces doubled in count from 17 incidents in 2023 to 34 in 2024.
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 makes of vehicles involved in crashes showed a stable pattern, with Toyota, Ford, and Honda remaining the top three most frequent makes in both 2023 and 2024. Analysis of the age of persons involved in crashes reveals a shift in demographics. The proportion of individuals in the 45-54 age group increased from an 11.1% share of all persons involved in 2023 (190 individuals) to a 14.2% share in 2024 (265 individuals), while other age groups' representation remained relatively consistent.
Top Vehicle Makes (1,568 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
92 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,749 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 continue to be most frequent in 65 mph zones, with counts rising from 264 in 2023 to 278 in 2024; however, fatalities in this zone decreased from two to one. There was also an increase in crashes within lower speed zones, including a rise from 149 to 171 incidents in 40 mph zones and from 132 to 158 incidents in 30 mph zones. The single fatal crash in 2024 occurred in a 65 mph zone.
Fatal crashes by zone: 65 mph: 1 of 278 (0.36%)
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: AUBURN, MA
- Total crash records analyzed: 819
- Total persons involved: 1,866
- Total vehicles involved: 1,568
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: 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/auburn/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