Monthly Traffic Safety Analysis

59 CRASHES IN
AUBURN, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

Total crashes in Auburn decreased by 9.23%, from 65 in September 2023 to 59 in September 2024. The most notable shift was the absence of fatalities in September 2024, compared to one fatality in the prior year.

59

-9.2%was 65

Total Crash Events

0

-100.0%was 1

Persons Killed

15

-31.8%was 22

Persons Injured

5

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Auburn decreased year-over-year, with total incidents falling by 9.23% from 65 to 59. Fatalities were eliminated in September 2024, and total injuries also saw a significant reduction of 31.82%, decreasing from 22 to 15.

5

Hit-and-Run Crashes — September 2024

0.0% vs prior (5)

The number of hit-and-run crashes remained consistent at 5 incidents in both September 2023 and September 2024. However, the hit-and-run rate increased from 7.7% in the prior period to 8.5% in the current period, relative to the overall decrease in total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

14

Motorists Injured

Prior: 22-36.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 Saturday, with 12 incidents in September 2023, to Tuesday, also with 12 incidents, in September 2024. The peak crash hour moved from 4 PM with 7 crashes in the prior period to 2 PM with 8 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in September 2023 to 0 in September 2024. Total injuries also saw a reduction, dropping from 22 to 15 year-over-year. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) was 20.3% in September 2024, a slight decrease from 21.5% in September 2023.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.7%
Minor Injury7minor injury crashes11.9%
-22.2%prior 9
Possible Injury4possible injury crashes6.8%
-20.0%prior 5
No Injury46no injury crashes78%
-8.0%prior 50

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' decreased from 19 crashes to 14 crashes, a 26.3% reduction. 'Followed too closely' also decreased from 12 crashes to 10 crashes, a 16.7% reduction. Conversely, 'Inattention' increased by 50%, rising from 6 crashes to 9 crashes, and 'Over-correcting/over-steering' increased from 1 crash to 4 crashes, a 300% change in count.

Officer-Reported Primary Contributing Cause

No improper driving14 (23.7%)-26.3%prior 19
Followed too closely10 (16.9%)-16.7%prior 12
Inattention9 (15.3%)50.0%prior 6
Failed to yield right of way7 (11.9%)16.7%prior 6
Over-correcting/over-steering4 (6.8%)
Failure to keep in proper lane or running off road4 (6.8%)-33.3%prior 6
Exceeded authorized speed limit2 (3.4%)
Fatigued/asleep2 (3.4%)
Visibility obstructed2 (3.4%)
Made an improper turn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 34 incidents in September 2023 to 40 in September 2024. Crashes on 'Wet' road surfaces decreased significantly by 45%, from 20 incidents to 11 incidents. Daylight crashes decreased from 50 to 45, while crashes in 'Dark - lighted roadway' conditions increased from 7 to 8.

Weather

Clear40 (69.0%)
17.6%prior 34
Rain4 (6.9%)
-33.3%prior 6
Clear/Cloudy4 (6.9%)
Cloudy3 (5.2%)
-70.0%prior 10
Cloudy/Rain2 (3.4%)
-77.8%prior 9
Clear/Unknown2 (3.4%)
Rain/Cloudy1 (1.7%)
Clear/Clear1 (1.7%)
Cloudy/Other1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight45 (76.3%)
-10.0%prior 50
Dark - lighted roadway8 (13.6%)
14.3%prior 7
Dark - roadway not lighted3 (5.1%)
Dusk2 (3.4%)
Dawn1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry48 (81.4%)
6.7%prior 45
Wet11 (18.6%)
-45.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

Toyota remained the top vehicle make involved in crashes, with its count decreasing slightly from 22 to 21. Ford increased its involvement from 10 to 14, moving up in ranking, while Nissan saw a substantial increase from 5 to 12. In age distribution, persons aged 45-54 involved in crashes increased from 13 to 25, a 92.3% rise, while those aged 65+ decreased by 50%, from 24 to 12.

Top Vehicle Makes (117 vehicles)

1
TOYOTA21 (17.9%)
-4.5%prior 22
2
FORD14 (12%)
40.0%prior 10
3
NISSAN12 (10.3%)
140.0%prior 5
4
CHEVROLET9 (7.7%)
-25.0%prior 12
5
JEEP6 (5.1%)
20.0%prior 5
6
HYUNDAI6 (5.1%)
-33.3%prior 9
7
VOLVO5 (4.3%)
8
HONDA5 (4.3%)
-28.6%prior 7
9
SUBARU5 (4.3%)
-16.7%prior 6
10
LEXUS3 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (122 persons with recorded sex)

Male68 (55.7%)
-12.8%prior 78
Female54 (44.3%)
-12.9%prior 62

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in the 65 mph speed zone decreased from 30 incidents in September 2023 to 20 incidents in September 2024, with this zone recording 0 fatal crashes in the current period compared to 1 in the prior period. Crashes in the 40 mph speed zone increased from 10 to 16 incidents. Additionally, crashes in the 25 mph zone increased from 1 to 3 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: AUBURN, MA
  • Total crash records analyzed: 59
  • Total persons involved: 133
  • Total vehicles involved: 117

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/september-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

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Auburn, MA Crash Report — September 2024 | ThatCarHitMe.com