Monthly Traffic Safety Analysis

60 CRASHES IN
AUBURN, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, AUBURN experienced 60 crashes, a 25% increase compared to the 48 crashes recorded in February 2024. Despite the rise in total crashes, the number of injuries significantly decreased by 50%, falling from 14 to 7 year-over-year. Fatalities remained at zero in both periods.

60

25.0%was 48

Total Crash Events

0

Persons Killed

7

-50.0%was 14

Persons Injured

4

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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in AUBURN increased by 25% year-over-year, rising from 48 crashes in February 2024 to 60 crashes in February 2025. Conversely, total injuries saw a substantial decrease of 50%, falling from 14 to 7. Fatalities remained stable at zero for both periods.

4

Hit-and-Run Crashes — February 2025

0.0% vs prior (4)

The number of hit-and-run crashes remained stable at 4 incidents in both February 2024 and February 2025. However, the hit-and-run rate decreased from 8.3% in the prior period to 6.7% in the current period, reflecting the overall increase in total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 14-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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 Friday in February 2024, with 9 incidents, to Wednesday in February 2025, with 13 incidents. The peak hour also changed, moving from 9 PM with 4 crashes in the prior period to 11 AM with 8 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either period. The proportion of minor injury crashes decreased from 12.5% (6 crashes) in February 2024 to 5% (3 crashes) in February 2025. Possible injury crashes also saw a reduction from 12.5% (6 crashes) to 1.7% (1 crash), while crashes with no injury increased from 72.9% (35 crashes) to 91.7% (55 crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
0.0%prior 1
Minor Injury3minor injury crashes5%
-50.0%prior 6
Possible Injury1possible injury crashes1.7%
-83.3%prior 6
No Injury55no injury crashes91.7%
57.1%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

The number of crashes attributed to 'Inattention' increased by 1, from 5 in February 2024 to 6 in February 2025. 'Distracted' driving incidents saw a notable rise, increasing by 4 from 1 to 5 crashes. Crashes related to 'Driving too fast for conditions' also increased by 4, from 0 to 4 incidents, while 'Followed too closely' decreased by 2, from 5 to 3 crashes.

Officer-Reported Primary Contributing Cause

No improper driving13 (21.7%)0.0%prior 13
Failed to yield right of way8 (13.3%)0.0%prior 8
Inattention6 (10%)20.0%prior 5
Distracted5 (8.3%)
Driving too fast for conditions4 (6.7%)
Other improper action4 (6.7%)
Followed too closely3 (5%)-40.0%prior 5
Made an improper turn3 (5%)
Over-correcting/over-steering2 (3.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in 'Daylight' conditions increased from 31 in February 2024 to 46 in February 2025, while crashes in 'Dark - lighted roadway' decreased from 11 to 8. Crashes on 'Wet' road surfaces doubled from 5 to 10 year-over-year. Additionally, crashes on 'Ice' and 'Snow' road surfaces, which were not recorded in the prior period, accounted for 7 crashes each in February 2025.

Weather

Clear29 (48.3%)
-21.6%prior 37
Clear/Clear7 (11.7%)
Cloudy5 (8.3%)
-16.7%prior 6
Snow/Sleet, hail (freezing rain or drizzle)3 (5.0%)
Clear/Unknown3 (5.0%)
Snow3 (5.0%)
Cloudy/Rain1 (1.7%)
Cloudy/Severe crosswinds1 (1.7%)
Other1 (1.7%)
Rain1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight46 (76.7%)
48.4%prior 31
Dark - lighted roadway8 (13.3%)
-27.3%prior 11
Dark - roadway not lighted5 (8.3%)
-16.7%prior 6
Dark - unknown roadway lighting1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry35 (58.3%)
-16.7%prior 42
Wet10 (16.7%)
100.0%prior 5
Ice7 (11.7%)
Snow7 (11.7%)
Slush1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 18, from 93 in February 2024 to 111 in February 2025, representing a 19.4% rise. Toyota became the top vehicle make involved in crashes with 16 instances in February 2025, up from 8 in February 2024, while Honda remained stable with 10 instances in both periods. There was a notable increase in persons aged 21-25 involved in crashes, rising from 10 to 20, and those aged 55-64, increasing from 6 to 18.

Top Vehicle Makes (111 vehicles)

1
TOYOTA16 (14.4%)
100.0%prior 8
2
FORD13 (11.7%)
85.7%prior 7
3
HONDA10 (9%)
0.0%prior 10
4
CHEVROLET8 (7.2%)
60.0%prior 5
5
SUBARU7 (6.3%)
6
JEEP5 (4.5%)
-50.0%prior 10
7
KIA5 (4.5%)
0.0%prior 5
8
HYUNDAI5 (4.5%)
9
VOLKSWAGEN4 (3.6%)
10
BMW4 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

13 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (119 persons with recorded sex)

Male62 (52.1%)
12.7%prior 55
Female57 (47.9%)
16.3%prior 49

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 40 mph speed zones increased by 4, from 12 in February 2024 to 16 in February 2025. Incidents in 65 mph zones rose by 2, from 13 to 15 crashes year-over-year. Conversely, crashes in 35 mph speed zones decreased by 6, from 7 to 1 crash.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: AUBURN, MA
  • Total crash records analyzed: 60
  • Total persons involved: 133
  • Total vehicles involved: 111

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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/february-2025-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

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Auburn, MA Crash Report — February 2025 | ThatCarHitMe.com