Yearly Traffic Safety Analysis

1,740 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In Wayne County, total traffic crashes decreased by 8.6% from 1,904 in 2022 to 1,740 in 2023. Despite the overall reduction in collisions, the number of fatalities resulting from these incidents rose from 17 to 23 year-over-year. This increase in fatalities occurred alongside a 4.1% decrease in total injuries.

1,740

▼ -8.6%was 1,904

Total Crash Events

23

▲ 35.3%was 17

Persons Killed

710

▼ -4.1%was 740

Persons Injured

151

▼ -16.1%was 180

Hit-and-Run Crashes

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Wayne County shows a decrease in the total volume of crashes, which fell from 1,904 in 2022 to 1,740 in 2023. However, the severity of crashes worsened, as total fatalities increased by 35.3% from 17 to 23. The number of people injured saw a modest decline of 4.1%, from 740 to 710.

151

Hit-and-Run Crashes — 2023

▼ -16.1% vs prior (180)

Hit-and-run incidents saw a decrease in both volume and rate compared to the previous year. The total number of hit-and-run crashes fell from 180 in 2022 to 151 in 2023. Correspondingly, the hit-and-run rate, which measures the percentage of all crashes that were hit-and-runs, declined from 9.5% to 8.7%.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 3↓-33.3%

21

Motorists Killed

Prior: 14↑50.0%

4

Pedestrians Injured

Prior: 7↓-42.9%

706

Motorists Injured

Prior: 733↓-3.7%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. In 2023, the peak day for crashes was Wednesday with 286 incidents, a change from 2022 when Friday was the peak day with 338 crashes. The peak hour for collisions remained consistent, with the 3 PM hour recording the highest number of incidents in both years (166 in 2023 and 163 in 2022).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes declined, the severity of crashes increased from 2022 to 2023. The fatal crash rate rose from 0.84% to 1.26% of all crashes, with the number of fatal incidents increasing from 16 to 22. The proportion of crashes resulting in any form of injury (serious, minor, or possible) grew from 26.2% in 2022 to 28.1% in 2023, driven by increases in minor and possible injury crashes.

Severity is per crash event (most severe injury). 22 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal22fatal crashes1.3%
↑37.5%prior 16
Serious Injury45serious injury crashes2.6%
↓-15.1%prior 53
Minor Injury316minor injury crashes18.2%
↓-4.0%prior 329
Possible Injury127possible injury crashes7.3%
↑8.5%prior 117
No Injury1,230no injury crashes70.7%
↓-11.4%prior 1,389

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with a majority of incidents in both periods occurring in daylight (67.4% in 2023 vs. 66.2% in 2022) and on dry roads (76.7% vs. 73.5%). There was a minor proportional increase in crashes occurring during rain, which accounted for 10.1% of incidents in 2023 compared to 8.4% in 2022. Crashes on snowy or icy roads decreased from 9.8% of the total in 2022 to 6.6% in 2023.

Weather

Clear980 (56.3%)
↓-9.7%prior 1,085
Cloudy458 (26.3%)
↓-6.7%prior 491
Rain175 (10.1%)
↑9.4%prior 160
Snow94 (5.4%)
↓-19.7%prior 117
Fog; Smog; Smoke21 (1.2%)
↑31.3%prior 16
Other/Unknown6 (0.3%)
→0.0%prior 6
Sleet; Hail4 (0.2%)
Severe Crosswinds1 (0.1%)
Blowing Sand; Soil; Dirt; Snow1 (0.1%)
↓-95.5%prior 22

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight1,173 (67.4%)
↓-7.0%prior 1,261
Dark - Roadway Not Lighted350 (20.1%)
↓-15.3%prior 413
Dark - Lighted Roadway109 (6.3%)
→0.0%prior 109
Dawn/Dusk101 (5.8%)
↓-11.4%prior 114
Other/Unknown5 (0.3%)
→0.0%prior 5
Dark - Unknown Roadway Lighting2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry1,334 (76.7%)
↓-4.7%prior 1,400
Wet316 (18.2%)
↓-2.2%prior 323
Snow63 (3.6%)
↓-50.0%prior 126
Ice22 (1.3%)
↓-53.2%prior 47
Slush3 (0.2%)
Water (Standing; Moving)1 (0.1%)
Other/Unknown1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The distribution of vehicle types and makes involved in crashes was largely stable between 2022 and 2023. Passenger cars, Sport Utility Vehicles, and Pickups were the three most common vehicle types in both years, and the top three makes remained Ford, Chevrolet, and Honda. An analysis of persons involved shows a proportional increase in the 65+ age group, which represented 14.4% of all persons in 2023, up from 12.9% in 2022.

Top Vehicle Makes (2,901 vehicles)

1
FORD513 (17.7%)
↓-4.6%prior 538
2
CHEVROLET424 (14.6%)
↓-13.1%prior 488
3
HONDA280 (9.7%)
↓-6.0%prior 298
4
TOYOTA217 (7.5%)
↓-3.1%prior 224
5
DODGE181 (6.2%)
↓-19.2%prior 224
6
JEEP134 (4.6%)
↓-11.3%prior 151
7
KIA96 (3.3%)
↑6.7%prior 90
8
NISSAN92 (3.2%)
↓-5.2%prior 97
9
GMC88 (3%)
↓-5.4%prior 93
10
HYUNDAI72 (2.5%)
↓-11.1%prior 81

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (3,820 persons with recorded sex)

Male2,117 (55.4%)
↓-9.7%prior 2,344
Female1,703 (44.6%)
↓-4.6%prior 1,786

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,740
  • Total persons involved: 3,906
  • Total vehicles involved: 2,901

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: 2023." Published July 5, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2023-annual-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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Wayne County, OH Crash Report — 2023 | ThatCarHitMe.com