Monthly Traffic Safety Analysis

83 CRASHES IN
AUBURN, MA
JUNE 2023

All metrics benchmarked againstJune 2022

Total crashes in Auburn for June 2023 were 83, an increase from 59 crashes in June 2022. This represents a 40.7% rise in total crashes year-over-year. The most significant shift was in contributing factors, with crashes due to "Followed too closely" increasing by 154.5%, from 11 in June 2022 to 28 in June 2023.

83

40.7%was 59

Total Crash Events

0

Persons Killed

25

56.3%was 16

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Auburn for June 2023 showed an upward trend compared to June 2022, with total crashes increasing by 40.7%, from 59 to 83. This indicates a notable rise in crash incidents year-over-year.

5

Hit-and-Run Crashes — June 2023

0.0% vs prior (5)

The number of hit-and-run crashes remained constant at 5 in both June 2022 and June 2023. However, the hit-and-run rate decreased from 8.5% of total crashes in June 2022 to 6% in June 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

25

Motorists Injured

Prior: 1566.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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 Friday in June 2022, with 16 crashes, to Saturday in June 2023, with 22 crashes. The peak hour for crashes also shifted, from 3 p.m. in June 2022, with 8 crashes, to 5 p.m. in June 2023, with 10 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries increased from 16 in June 2022 to 25 in June 2023. While no fatalities were recorded in either period, there was a shift in injury severity: June 2022 reported 3 serious injuries, whereas June 2023 reported none, with minor injuries increasing from 9 to 10 and possible injuries increasing from 2 to 6.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes12%
11.1%prior 9
Possible Injury6possible injury crashes7.2%
200.0%prior 2
No Injury64no injury crashes77.1%
42.2%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor "Followed too closely" saw a significant increase of 154.5% in count, rising from 11 crashes in June 2022 to 28 in June 2023, making it the top factor. "Failed to yield right of way" crashes doubled from 7 to 14, a 100% increase in count, while "No improper driving" decreased by 43.8% in count, from 16 to 9.

Officer-Reported Primary Contributing Cause

Followed too closely28 (33.7%)154.5%prior 11
Failed to yield right of way14 (16.9%)100.0%prior 7
No improper driving9 (10.8%)-43.8%prior 16
Inattention9 (10.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (4.8%)
Failure to keep in proper lane or running off road3 (3.6%)
Distracted3 (3.6%)
Other improper action3 (3.6%)
Visibility obstructed3 (3.6%)
Exceeded authorized speed limit2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 52 in June 2022 to 46 in June 2023, while crashes in cloudy conditions increased substantially from 3 to 20. Crashes on dry road surfaces increased from 56 to 70, and crashes on wet road surfaces increased from 3 to 13 year-over-year.

Weather

Clear46 (57.5%)
-11.5%prior 52
Cloudy20 (25.0%)
Rain5 (6.3%)
Cloudy/Rain4 (5.0%)
Clear/Unknown2 (2.5%)
Rain/Cloudy2 (2.5%)
Clear/Other1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight71 (85.5%)
39.2%prior 51
Dark - lighted roadway5 (6.0%)
Dawn3 (3.6%)
Dusk2 (2.4%)
Dark - roadway not lighted1 (1.2%)
Dark - unknown roadway lighting1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry70 (84.3%)
25.0%prior 56
Wet13 (15.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 48.2%, from 110 in June 2022 to 163 in June 2023. Toyota remained the top make, with involved vehicles increasing from 16 to 26, while Ford saw a notable increase from 7 to 16 involved vehicles. The age groups 26-34 and 35-44 experienced significant increases in person involvement, rising from 25 to 48 and 14 to 33 respectively.

Top Vehicle Makes (163 vehicles)

1
TOYOTA26 (16%)
62.5%prior 16
2
FORD16 (9.8%)
128.6%prior 7
3
CHEVROLET12 (7.4%)
33.3%prior 9
4
HONDA12 (7.4%)
71.4%prior 7
5
JEEP10 (6.1%)
66.7%prior 6
6
SUBARU9 (5.5%)
80.0%prior 5
7
VOLKSWAGEN9 (5.5%)
8
LEXUS7 (4.3%)
9
HYUNDAI7 (4.3%)
10
NISSAN6 (3.7%)
-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

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

Sex Distribution (182 persons with recorded sex)

Male110 (60.4%)
74.6%prior 63
Female72 (39.6%)
24.1%prior 58

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 65 mph speed zones increased from 20 in June 2022 to 37 in June 2023, an 85% increase in count. Crashes in 40 mph zones also increased from 10 to 15, a 50% increase, while crashes in 30 mph zones decreased from 10 to 8. No fatalities were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: AUBURN, MA
  • Total crash records analyzed: 83
  • Total persons involved: 197
  • Total vehicles involved: 163

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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/june-2023-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 — June 2023 | ThatCarHitMe.com