ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AUBURN, MA · AUGUST 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/auburn/august-2023-report
Monthly Traffic Safety Analysis
66 CRASHES IN
AUBURN, MA
AUGUST 2023
In August 2023, Auburn experienced 66 crashes, a slight decrease from 67 crashes in August 2022, representing a 1.5% reduction. A notable shift was observed in total injuries, which decreased by 37.5% from 24 in the prior period to 15 in the current period. Conversely, hit-and-run crashes increased significantly from 2 to 5 during the same timeframe.
66
▼ -1.5%was 67
Total Crash Events
0
Persons Killed
15
▼ -37.5%was 24
Persons Injured
5
▲ 150.0%was 2
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 · 2023-08-01 to 2023-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The total number of crashes remained relatively stable year-over-year, decreasing slightly from 67 in August 2022 to 66 in August 2023. However, there was a significant downward trend in total injuries, which fell from 24 to 15, marking a 37.5% reduction. Fatalities remained at zero in both periods.
5
Hit-and-Run Crashes — August 2023
▲ 150.0% vs prior (2)
Hit-and-run crashes increased significantly from 2 in August 2022 to 5 in August 2023, marking a 150% rise in count. The proportion of hit-and-run incidents relative to total crashes also increased, with the hit-and-run rate rising from 3% to 7.6%. This indicates an upward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · 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 Saturday (12 crashes) in August 2022 to Friday (16 crashes) in August 2023. The peak hour also changed, moving from 12p (10 crashes) in the prior period to 9a (8 crashes) in the current period. Crashes on Thursday saw an increase from 8 to 14, while Sunday crashes decreased from 9 to 5.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both August 2022 and August 2023, with no fatal crashes reported. Total injuries decreased by 37.5%, from 24 to 15, year-over-year. Minor injuries decreased from 14 (20.9% of crashes) to 8 (12.1% of crashes), while crashes with no injuries increased from 47 (70.1% of crashes) to 53 (80.3% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Most severe injury per crash record
Top Contributing Factors
The count of 'Followed too closely' crashes decreased from 17 to 13, a 23.5% reduction. 'No improper driving' crashes increased from 8 to 11, a 37.5% rise in count, moving from the fourth to the second most frequent factor. Crashes attributed to 'Driving too fast for conditions' increased from 1 to 3, representing a 200% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather decreased from 50 to 43 year-over-year. There was a notable increase in crashes during rainy conditions, rising from 2 to 8, and on wet road surfaces, which increased from 5 to 13. Crashes occurring in 'Dark - lighted roadway' conditions doubled from 3 in the prior period to 6 in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes decreased from 171 to 162 year-over-year. The 16-20 age group saw a decrease in involvement from 24 to 14 persons, and the 65+ age group also decreased from 26 to 17 persons. Toyota remained the most frequent vehicle make involved, increasing from 18 to 26 vehicles, while Nissan decreased from 13 to 10 and Chevrolet from 12 to 9.
Top Vehicle Makes (128 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (141 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 65 mph speed zone decreased from 24 to 21, and in the 40 mph speed zone, they decreased from 18 to 10. Conversely, crashes in the 30 mph speed zone increased from 13 to 15, and in the 25 mph speed zone, they increased from 3 to 6. No fatal crashes were reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-08-01 to 2023-08-31 · 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: 2023-08-01 through 2023-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-08-01 through 2023-08-31 (31 days)
- Geographic scope: AUBURN, MA
- Total crash records analyzed: 66
- Total persons involved: 162
- Total vehicles involved: 128
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: August 2023." Published June 21, 2026. Reporting period: 2023-08-01 to 2023-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/auburn/august-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-08-01 – 2023-08-31
Generated: June 21, 2026 · All rights reserved