Monthly Traffic Safety Analysis

80 CRASHES IN
AUBURN, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

In December 2025, Auburn experienced 80 crashes, an increase of 9.59% compared to the 73 crashes recorded in December 2024. A notable shift is the presence of 1 fatal crash in the current period, whereas no fatal crashes occurred in the prior period.

80

9.6%was 73

Total Crash Events

1

Persons Killed

26

85.7%was 14

Persons Injured

8

100.0%was 4

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Auburn show an increase year-over-year, with total crashes rising by 9.59% from 73 to 80. This period also saw a significant increase in total injuries, from 14 to 26, and the occurrence of 1 fatality compared to none in the prior year.

8

Hit-and-Run Crashes — December 2025

100.0% vs prior (4)

Hit-and-run crashes increased significantly, from 4 in December 2024 to 8 in December 2025. Consequently, the hit-and-run rate rose from 5.5% to 10% year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 00.0%

0

Pedestrians Injured

Prior: 00.0%

26

Motorists Injured

Prior: 1485.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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 Monday with 14 crashes in December 2024 to Tuesday with 27 crashes in December 2025. The peak hour also shifted slightly, with 10 crashes occurring at 1p in the current period, compared to 9 crashes at 12p in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate increased from 0% in December 2024 to 1.25% in December 2025, with 1 fatal crash occurring in the current period. Crashes resulting in minor injuries increased from 8 to 12, and possible injury crashes rose from 3 to 5.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.3%
Minor Injury12minor injury crashes15%
50.0%prior 8
Possible Injury5possible injury crashes6.3%
66.7%prior 3
No Injury61no injury crashes76.3%
0.0%prior 61

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' crashes increased by 6, from 14 to 20, and 'Inattention' crashes increased by 3, from 11 to 14. Conversely, crashes attributed to 'Followed too closely' decreased by 3, from 14 to 11. Notably, crashes involving 'Driving too fast for conditions' saw a substantial increase, rising from 3 to 8.

Officer-Reported Primary Contributing Cause

No improper driving20 (25%)42.9%prior 14
Inattention14 (17.5%)27.3%prior 11
Followed too closely11 (13.8%)-21.4%prior 14
Failed to yield right of way9 (11.3%)0.0%prior 9
Driving too fast for conditions8 (10%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway4 (5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.8%)
Failure to keep in proper lane or running off road2 (2.5%)
Other improper action2 (2.5%)
Glare1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 30 to 36, while those in 'Snow' conditions decreased from 7 to 3. For lighting, 'Daylight' crashes rose from 49 to 54. Regarding road surface, crashes on 'Dry' roads increased from 47 to 48, and those on 'Wet' roads increased from 13 to 15, while 'Snow' road surface crashes decreased from 11 to 5.

Weather

Clear36 (45.0%)
20.0%prior 30
Clear/Clear11 (13.8%)
0.0%prior 11
Clear/Unknown4 (5.0%)
Snow/Cloudy4 (5.0%)
Cloudy3 (3.8%)
-40.0%prior 5
Snow3 (3.8%)
-57.1%prior 7
Cloudy/Rain3 (3.8%)
Rain3 (3.8%)
Snow/Sleet, hail (freezing rain or drizzle)2 (2.5%)
Sleet, hail (freezing rain or drizzle)2 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight54 (67.5%)
10.2%prior 49
Dark - lighted roadway14 (17.5%)
-6.7%prior 15
Dark - roadway not lighted8 (10.0%)
0.0%prior 8
Dusk3 (3.8%)
Dawn1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry48 (60.0%)
2.1%prior 47
Wet15 (18.8%)
15.4%prior 13
Slush8 (10.0%)
Snow5 (6.3%)
-54.5%prior 11
Ice4 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Honda vehicles involved in crashes increased from 15 to 26, making it the top make in the current period. Toyota vehicles involved decreased from 30 to 21. Chevrolet also saw an increase in involvement, from 8 to 13, while Ford's involvement decreased from 15 to 9.

Top Vehicle Makes (162 vehicles)

1
HONDA26 (16%)
73.3%prior 15
2
TOYOTA21 (13%)
-30.0%prior 30
3
CHEVROLET13 (8%)
62.5%prior 8
4
SUBARU10 (6.2%)
-9.1%prior 11
5
LEXUS9 (5.6%)
6
NISSAN9 (5.6%)
-10.0%prior 10
7
FORD9 (5.6%)
-40.0%prior 15
8
HYUNDAI6 (3.7%)
0.0%prior 6
9
GMC5 (3.1%)
10
KIA5 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (165 persons with recorded sex)

Male93 (56.4%)
14.8%prior 81
Female72 (43.6%)
-8.9%prior 79

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

A fatal crash occurred in a 45 mph speed zone in December 2025, where none occurred in the prior period. Crashes in 30 mph zones decreased from 17 to 15, while crashes in 40 mph zones increased from 16 to 18. The number of crashes in 65 mph zones remained stable at 19 for both periods.

Fatal crashes by zone: 45 mph: 1 of 4 (25%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: AUBURN, MA
  • Total crash records analyzed: 80
  • Total persons involved: 182
  • Total vehicles involved: 162

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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/december-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 — December 2025 | ThatCarHitMe.com