Yearly Traffic Safety Analysis

28,431 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In Hamilton County, total traffic crashes increased by 3.5% from 27,477 in 2023 to 28,431 in 2024. Despite the rise in overall incidents, the most notable year-over-year shift was a significant improvement in crash outcomes. The number of fatalities decreased by 21.3%, falling from 80 in the prior year to 63 in the current period.

28,431

▲ 3.5%was 27,477

Total Crash Events

▼ -21.3%was 80

Persons Killed

8,593

▼ -2.3%was 8,796

Persons Injured

6,587

▲ 3.7%was 6,352

Hit-and-Run Crashes

Note: "Persons Killed" (63) counts individual fatalities across all crash events. "Fatal" in the severity table below (60) 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

Traffic safety trends in Hamilton County show a mixed picture year-over-year. The total volume of crashes rose by 3.5% from 27,477 to 28,431. However, the severity of these incidents lessened, as total injuries fell by 2.3% from 8,796 to 8,593, and fatalities dropped by 21.3% from 80 to 63.

6,587

Hit-and-Run Crashes — 2024

▲ 3.7% vs prior (6,352)

The total number of hit-and-run crashes increased from 6,352 in 2023 to 6,587 in 2024. However, this rise was proportional to the overall increase in total crashes. As a result, the hit-and-run rate remained effectively stable, moving from 23.1% of all crashes in the prior year to 23.2% in the current year.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 18↓-38.9%

Motorists Killed

Prior: 62↓-16.1%

421

Pedestrians Injured

Prior: 352↑19.6%

8,172

Motorists Injured

Prior: 8,444↓-3.2%

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 timing of crashes showed remarkable consistency between the two periods. Friday remained the day with the most crashes in both 2024 (4,787 incidents) and 2023 (4,616 incidents). A minor shift occurred in the peak hour, which moved from the 4 p.m. hour in 2023 (2,338 crashes) to the 5 p.m. hour in 2024 (2,408 crashes), both corresponding to the evening commute.

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

Crash severity outcomes improved from 2023 to 2024. Fatal crashes decreased from 72 to 60, and their share of all crashes fell from 0.3% to 0.2%. The proportion of serious injury crashes held steady at 1.4% in both years. Correspondingly, the percentage of crashes resulting in no injury increased from 77.0% in 2023 to 78.4% in 2024.

Severity is per crash event (most severe injury). 60 fatal crash events resulted in 63 persons killed.

Outcome by Severity (Crash Events)

Fatal60fatal crashes0.2%

↓-16.7%prior 72

Serious Injury394serious injury crashes1.4%

↑3.7%prior 380

Minor Injury3,055minor injury crashes10.7%

↓-2.1%prior 3,122

Possible Injury2,640possible injury crashes9.3%

↓-3.4%prior 2,733

No Injury22,282no injury crashes78.4%

↑5.3%prior 21,170

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 environmental conditions during which crashes occurred were largely stable year-over-year. The proportion of crashes happening in daylight was unchanged at 68.0% for both periods. Crashes on dry road surfaces were dominant in both years, though their share decreased slightly from 78.7% in 2023 to 77.9% in 2024. Incidents during rainy weather saw a marginal increase, accounting for 13.2% of crashes in 2024 compared to 12.2% in 2023.

Weather

Clear19,167 (67.4%)

↑4.9%prior 18,275

Cloudy4,700 (16.5%)

↓-9.4%prior 5,185

Rain3,759 (13.2%)

↑12.0%prior 3,356

Snow439 (1.5%)

↑33.0%prior 330

Other/Unknown275 (1.0%)

↑12.7%prior 244

Fog; Smog; Smoke58 (0.2%)

↑38.1%prior 42

Sleet; Hail11 (0.0%)

↓-54.2%prior 24

Freezing Rain or Freezing Drizzle10 (0.0%)

↑42.9%prior 7

Blowing Sand; Soil; Dirt; Snow6 (0.0%)

Severe Crosswinds6 (0.0%)

↓-50.0%prior 12

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

Lighting

Daylight19,323 (68.0%)

↑3.5%prior 18,672

Dark - Lighted Roadway6,013 (21.1%)

↑2.3%prior 5,876

Dawn/Dusk1,456 (5.1%)

↑8.5%prior 1,342

Dark - Roadway Not Lighted1,232 (4.3%)

↑5.7%prior 1,166

Other/Unknown252 (0.9%)

↑0.8%prior 250

Dark - Unknown Roadway Lighting155 (0.5%)

↓-9.4%prior 171

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

Road Surface

Dry22,157 (77.9%)

↑2.4%prior 21,633

Wet5,681 (20.0%)

↑5.7%prior 5,374

Snow294 (1.0%)

↑39.3%prior 211

Other/Unknown190 (0.7%)

↑9.2%prior 174

Ice90 (0.3%)

↑42.9%prior 63

Sand; Mud; Dirt; Oil; Gravel7 (0.0%)

↑40.0%prior 5

Slush6 (0.0%)

↓-14.3%prior 7

Water (Standing; Moving)6 (0.0%)

↓-40.0%prior 10

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

Vehicles & Demographics

The top three vehicle makes involved in crashes were Ford, Chevrolet, and Toyota in both 2023 and 2024, indicating stable vehicle demographics. While Ford and Chevrolet held the top two spots with similar numbers year-over-year, the involvement of Toyota vehicles increased from 5,857 to 6,297. Among persons involved in crashes, the 26-34 age group remained the largest demographic, growing from 10,239 individuals in 2023 to 10,764 in 2024.

Top Vehicle Makes (55,736 vehicles)

FORD6,671 (12%)

↓-1.7%prior 6,783

CHEVROLET6,663 (12%)

↑0.6%prior 6,624

TOYOTA6,297 (11.3%)

↑7.5%prior 5,857

HONDA6,081 (10.9%)

↑6.7%prior 5,698

NISSAN3,424 (6.1%)

↑5.1%prior 3,259

HYUNDAI2,437 (4.4%)

↑5.4%prior 2,312

KIA2,334 (4.2%)

↑5.1%prior 2,221

DODGE1,771 (3.2%)

↓-5.1%prior 1,867

JEEP1,716 (3.1%)

↑4.1%prior 1,648

MAZDA1,196 (2.1%)

↑12.1%prior 1,067

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

5,467 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (57,190 persons with recorded sex)

Male31,685 (55.4%)

↑4.7%prior 30,270

Female25,505 (44.6%)

↑1.6%prior 25,111

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 6, 2026

Data Coverage

Reporting period: 2024-01-01 through 2024-12-31 (366 days)
Geographic scope: ohio, OH
Total crash records analyzed: 28,431
Total persons involved: 61,879
Total vehicles involved: 55,736

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 6, 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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28,431 CRASHES INOHIO, OH2024