Monthly Traffic Safety Analysis

222 CRASHES IN
OHIO, OH
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, Allen County recorded 222 total crashes, a decrease from 249 crashes in September 2022, representing a 10.8% year-over-year decline. The most significant change was the number of fatalities, which dropped from four in the prior period to zero in the current period. Overall injuries also decreased from 102 to 80.

222

-10.8%was 249

Total Crash Events

0

-100.0%was 4

Persons Killed

80

-21.6%was 102

Persons Injured

44

-4.3%was 46

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: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Allen County improved year-over-year. Total crashes fell by 10.8% from 249 to 222, and total injuries decreased by 21.6% from 102 to 80. Notably, there were no fatalities in September 2023, compared to four in September 2022.

44

Hit-and-Run Crashes — September 2023

-4.3% vs prior (46)

The total number of hit-and-run crashes saw a slight decrease from 46 in September 2022 to 44 in September 2023. However, because the total number of crashes fell by a larger margin, the hit-and-run rate—the proportion of all crashes that were hit-and-runs—increased from 18.5% to 19.8% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 4-100.0%

1

Pedestrians Injured

Prior: 10.0%

79

Motorists Injured

Prior: 101-21.8%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted between the two periods. In September 2022, the peak day for crashes was Sunday with 44 incidents, but in September 2023, the peak shifted to Friday with 41 incidents. The peak hour for crashes remained the 3 PM hour in both periods, although the volume in that hour decreased from 32 to 26 crashes.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a notable improvement year-over-year. Fatal crashes were eliminated, dropping from 4 incidents (1.6% of total) in September 2022 to zero in September 2023. The proportion of crashes involving serious injury remained stable at 2.7% (6 crashes) compared to 2.4% (6 crashes) in the prior year. The share of no-injury crashes increased from 72.7% to 74.8% of all incidents.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes2.7%
0.0%prior 6
Minor Injury30minor injury crashes13.5%
-14.3%prior 35
Possible Injury20possible injury crashes9%
-13.0%prior 23
No Injury166no injury crashes74.8%
-8.3%prior 181

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of environmental conditions during crashes remained largely consistent year-over-year. In both September 2023 and September 2022, crashes predominantly occurred in clear weather (71.2% and 68.7% respectively) and on dry roads (89.2% and 85.9% respectively). The proportion of crashes occurring during daylight hours decreased from 74.3% in the prior year to 68.5% in the current period.

Weather

Clear158 (71.2%)
-7.6%prior 171
Cloudy41 (18.5%)
-24.1%prior 54
Rain16 (7.2%)
-20.0%prior 20
Other/Unknown4 (1.8%)
Fog; Smog; Smoke3 (1.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight152 (68.5%)
-17.8%prior 185
Dark - Roadway Not Lighted26 (11.7%)
0.0%prior 26
Dark - Lighted Roadway24 (10.8%)
4.3%prior 23
Dawn/Dusk14 (6.3%)
27.3%prior 11
Other/Unknown6 (2.7%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry198 (89.2%)
-7.5%prior 214
Wet21 (9.5%)
-36.4%prior 33
Other/Unknown2 (0.9%)
Sand; Mud; Dirt; Oil; Gravel1 (0.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes remained consistent, with Passenger Cars, Sport Utility Vehicles, and Pick-ups being the most common in both periods. The top vehicle makes, led by Ford and Chevrolet, also saw no significant change in ranking, though the counts for each decreased in line with the overall reduction in crashes. Among persons involved, the proportion of those aged 65 and older decreased from 13.7% of the total in the prior year to 11.9% in the current year.

Top Vehicle Makes (390 vehicles)

1
FORD77 (19.7%)
-11.5%prior 87
2
CHEVROLET55 (14.1%)
-27.6%prior 76
3
HONDA26 (6.7%)
-35.0%prior 40
4
DODGE26 (6.7%)
-16.1%prior 31
5
CHRYSLER19 (4.9%)
18.8%prior 16
6
NISSAN18 (4.6%)
28.6%prior 14
7
BUICK18 (4.6%)
157.1%prior 7
8
HYUNDAI17 (4.4%)
54.5%prior 11
9
JEEP16 (4.1%)
0.0%prior 16
10
TOYOTA15 (3.8%)
-34.8%prior 23

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (454 persons with recorded sex)

Male248 (54.6%)
-21.8%prior 317
Female206 (45.4%)
-29.0%prior 290

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv 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: Csv 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: 2023-09-01 through 2023-09-30
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 222
  • Total persons involved: 486
  • Total vehicles involved: 390

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). "ohio, OH Crash Intelligence Report: September 2023." Published July 6, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/september-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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Allen County, OH Crash Report — September 2023 | ThatCarHitMe.com