Yearly Traffic Safety Analysis

1,906 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In Wayne County, total crashes increased from 1,740 in 2023 to 1,906 in 2024, a rise of 9.5%. Despite the increase in total collisions, the number of fatalities saw a significant year-over-year decrease, falling from 23 to 10.

1,906

9.5%was 1,740

Total Crash Events

10

-56.5%was 23

Persons Killed

862

21.4%was 710

Persons Injured

149

-1.3%was 151

Hit-and-Run Crashes

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Wayne County show an increase in collision frequency and injuries year-over-year. Total crashes rose by 9.5% from 1,740 to 1,906, and the number of people injured increased by 21.4% from 710 to 862. In contrast, fatalities decreased substantially, dropping 56.5% from 23 in the prior period to 10 in the current period.

149

Hit-and-Run Crashes — 2024

-1.3% vs prior (151)

The number of hit-and-run crashes in Wayne County remained stable, with 149 incidents in 2024 compared to 151 in the prior year. However, due to the overall increase in total crashes, the hit-and-run rate saw a decrease. The rate fell from 8.7% of all crashes in 2023 to 7.8% in 2024, indicating a downward trend in the proportion of crashes involving a fleeing vehicle.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2-50.0%

9

Motorists Killed

Prior: 21-57.1%

18

Pedestrians Injured

Prior: 4350.0%

844

Motorists Injured

Prior: 70619.5%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Wayne County shifted between the two periods. The peak day for crashes moved from Wednesday (286 crashes) in 2023 to Friday (355 crashes) in 2024. The peak hour for collisions remained consistent, occurring in the 3 p.m. hour in both years with 166 and 167 crashes, respectively.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the severity profile of collisions changed year-over-year. The proportion of fatal crashes decreased from 1.3% of all crashes in 2023 to 0.5% in 2024. Conversely, the share of crashes resulting in any injury (serious, minor, or possible) increased from 28.1% to 31.0%, driven by a rise in the proportion of serious injury crashes from 2.6% to 3.7% of the total.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.5%
-54.5%prior 22
Serious Injury70serious injury crashes3.7%
55.6%prior 45
Minor Injury369minor injury crashes19.4%
16.8%prior 316
Possible Injury151possible injury crashes7.9%
18.9%prior 127
No Injury1,306no injury crashes68.5%
6.2%prior 1,230

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes across weather and road surface conditions remained largely consistent between 2023 and 2024, with clear weather and dry roads accounting for the majority of incidents in both periods. There was a notable increase in crashes occurring in dark, unlighted conditions, which grew from 350 incidents in 2023 to 427 in 2024. This represents a 22% increase in count and a shift in proportion from 20.1% to 22.4% of all crashes.

Weather

Clear1,068 (56.0%)
9.0%prior 980
Cloudy526 (27.6%)
14.8%prior 458
Rain189 (9.9%)
8.0%prior 175
Snow97 (5.1%)
3.2%prior 94
Fog; Smog; Smoke14 (0.7%)
-33.3%prior 21
Sleet; Hail6 (0.3%)
Other/Unknown5 (0.3%)
-16.7%prior 6
Freezing Rain or Freezing Drizzle1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight1,267 (66.5%)
8.0%prior 1,173
Dark - Roadway Not Lighted427 (22.4%)
22.0%prior 350
Dark - Lighted Roadway124 (6.5%)
13.8%prior 109
Dawn/Dusk82 (4.3%)
-18.8%prior 101
Dark - Unknown Roadway Lighting3 (0.2%)
Other/Unknown3 (0.2%)
-40.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,467 (77.0%)
10.0%prior 1,334
Wet342 (17.9%)
8.2%prior 316
Snow69 (3.6%)
9.5%prior 63
Ice17 (0.9%)
-22.7%prior 22
Slush9 (0.5%)
Water (Standing; Moving)1 (0.1%)
Other/Unknown1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The types and makes of vehicles involved in crashes saw little change, with Ford and Chevrolet remaining the top two makes in both years. An analysis of person demographics reveals a disproportionate increase in the involvement of certain age groups. The number of persons aged 16-20 involved in collisions grew by 15.4% from 553 to 638, a rate more than double the 7.2% overall increase in persons involved. Similarly, the 65+ age group saw an 11.9% increase in involvement from 562 to 629 persons.

Top Vehicle Makes (3,154 vehicles)

1
FORD527 (16.7%)
2.7%prior 513
2
CHEVROLET471 (14.9%)
11.1%prior 424
3
HONDA270 (8.6%)
-3.6%prior 280
4
TOYOTA252 (8%)
16.1%prior 217
5
DODGE195 (6.2%)
7.7%prior 181
6
JEEP151 (4.8%)
12.7%prior 134
7
KIA115 (3.6%)
19.8%prior 96
8
NISSAN107 (3.4%)
16.3%prior 92
9
HYUNDAI82 (2.6%)
13.9%prior 72
10
GMC79 (2.5%)
-10.2%prior 88

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (4,094 persons with recorded sex)

Male2,294 (56.0%)
8.4%prior 2,117
Female1,800 (44.0%)
5.7%prior 1,703

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,906
  • Total persons involved: 4,186
  • Total vehicles involved: 3,154

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: 2024." Published July 5, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2024-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 — 2024 | ThatCarHitMe.com