Monthly Traffic Safety Analysis

37 CRASHES IN
AUBURN, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, Auburn experienced 37 crashes, a decrease of 30.2% compared to the 53 crashes reported in April 2021. The most notable shift was a 200% increase in DUI-related crashes, rising from 1 in April 2021 to 3 in April 2022.

37

-30.2%was 53

Total Crash Events

0

Persons Killed

16

-11.1%was 18

Persons Injured

0

-100.0%was 1

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 · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Auburn showed a significant downward trend year-over-year, decreasing from 53 crashes in April 2021 to 37 crashes in April 2022. This represents a reduction of 16 crashes, or approximately 30.2%.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 18-11.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year. In April 2021, the peak day for crashes was Friday with 10 incidents, while in April 2022, Monday became the peak day with 11 crashes. Similarly, the peak crash hour moved from 8 PM with 7 crashes in April 2021 to 3 PM with 4 crashes in April 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both April 2021 and April 2022 reported no traffic fatalities. The total number of injured persons decreased from 18 in April 2021 to 16 in April 2022, an 11.1% reduction. While April 2021 reported no serious injuries, April 2022 saw 1 serious injury crash, representing 2.7% of all crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.7%
Minor Injury8minor injury crashes21.6%
-11.1%prior 9
Possible Injury4possible injury crashes10.8%
-20.0%prior 5
No Injury24no injury crashes64.9%
-38.5%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Comparing contributing factors, 'Inattention' remained the leading factor but decreased from 14 crashes in April 2021 to 10 crashes in April 2022, a 28.6% reduction in count. Conversely, 'Followed too closely' incidents surged by 166.7%, rising from 3 crashes in April 2021 to 8 crashes in April 2022, moving it up in rank. 'Failed to yield right of way' also saw an increase, from 4 crashes to 5 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Inattention10 (27%)-28.6%prior 14
Followed too closely8 (21.6%)
Failed to yield right of way5 (13.5%)
No improper driving3 (8.1%)-70.0%prior 10
Failure to keep in proper lane or running off road2 (5.4%)
Over-correcting/over-steering2 (5.4%)
Driving too fast for conditions1 (2.7%)
Visibility obstructed1 (2.7%)
History heart/epilepsy/fainting1 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 33 in April 2021 to 27 in April 2022, while crashes on dry road surfaces decreased from 41 to 31. Crashes occurring in daylight conditions increased proportionally, from 62.3% of total crashes in April 2021 to 73.0% in April 2022. The number of crashes on wet road surfaces decreased from 10 to 6, and crashes in dark-roadway-not-lighted conditions decreased from 5 to 1.

Weather

Clear27 (75.0%)
-18.2%prior 33
Rain4 (11.1%)
-20.0%prior 5
Clear/Cloudy2 (5.6%)
Cloudy2 (5.6%)
-66.7%prior 6
Rain/Cloudy1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight27 (73.0%)
-18.2%prior 33
Dark - lighted roadway8 (21.6%)
-38.5%prior 13
Dark - roadway not lighted1 (2.7%)
-80.0%prior 5
Dusk1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry31 (83.8%)
-24.4%prior 41
Wet6 (16.2%)
-40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 90 in April 2021 to 74 in April 2022, a 17.8% reduction. Toyota vehicles saw a 100% increase in involvement, rising from 6 to 12, and became the top make involved. Regarding persons involved, the 65+ age group saw a 75% increase in representation, from 8 to 14, while the 16-20 age group decreased by 52.9%, from 17 to 8.

Top Vehicle Makes (74 vehicles)

1
TOYOTA12 (16.2%)
100.0%prior 6
2
FORD11 (14.9%)
37.5%prior 8
3
HYUNDAI7 (9.5%)
16.7%prior 6
4
VOLKSWAGEN5 (6.8%)
5
CHEVROLET5 (6.8%)
-50.0%prior 10
6
JEEP4 (5.4%)
-20.0%prior 5
7
DODGE4 (5.4%)
8
HONDA4 (5.4%)
-50.0%prior 8
9
MAZDA3 (4.1%)
10
NISSAN3 (4.1%)
-57.1%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (92 persons with recorded sex)

Male57 (62.0%)
-10.9%prior 64
Female35 (38.0%)
-20.5%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Fatalities remained at zero across all speed zones in both periods. There was a notable decrease in crash counts within higher speed zones, with 65 mph zones experiencing a 47.1% reduction from 17 crashes to 9, and 40 mph zones decreasing by 35.7% from 14 crashes to 9. Crashes in 30 mph zones also saw an 18.2% decrease, from 11 to 9.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: AUBURN, MA
  • Total crash records analyzed: 37
  • Total persons involved: 95
  • Total vehicles involved: 74

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: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/april-2022-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 — April 2022 | ThatCarHitMe.com