Yearly Traffic Safety Analysis

14,180 CRASHES IN
CINCINNATI, OH
2024

All metrics benchmarked against2023

Total crashes increased by 3.77%, from 13,664 in the prior year to 14,180 in the current year. Despite this rise in overall crashes, total fatalities saw a significant decrease of 21.05%, dropping from 38 to 30. This indicates a notable shift towards less severe outcomes in crashes, even with an increase in crash frequency.

14,180

3.8%was 13,664

Total Crash Events

30

-21.1%was 38

Persons Killed

4,359

-4.0%was 4,542

Persons Injured

4,113

4.5%was 3,937

Hit-and-Run Crashes

Note: "Persons Killed" (30) counts individual fatalities across all crash events. "Fatal" in the severity table below (28) 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, crashes increased by 3.77% year-over-year, from 13,664 to 14,180. Conversely, total fatalities decreased by 21.05%, falling from 38 to 30. Total injuries also saw a decrease of 4.03%, from 4,542 to 4,359, indicating a general trend of fewer severe outcomes despite more crashes.

4,113

Hit-and-Run Crashes — 2024

4.5% vs prior (3,937)

Hit-and-run crashes increased by 4.47% year-over-year, from 3,937 to 4,113 incidents. The hit-and-run rate also saw a slight increase, rising from 28.8% in the prior year to 29% in the current year. This indicates a marginal upward trend in the proportion of crashes involving a hit-and-run.

Vulnerable Road User Casualties

6

Pedestrians Killed

Prior: 11-45.5%

24

Motorists Killed

Prior: 27-11.1%

295

Pedestrians Injured

Prior: 24520.4%

4,064

Motorists Injured

Prior: 4,297-5.4%

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 peak day for crashes remained Friday for both periods, with a 5.00% increase in crashes on Fridays in the current year. The peak hour shifted from 5 PM in the prior year (1,090 crashes) to 4 PM in the current year (1,132 crashes), representing a 4.72% increase at 4 PM. Crashes on Wednesday saw the largest increase, rising by 12.10% from 1,968 to 2,206.

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

The fatal crash rate decreased from 0.27% in the prior year to 0.2% in the current year. While serious injury crashes (Severity A) increased by 21.09% (from 147 to 178), minor injury (Severity B) and possible injury (Severity C) crashes both decreased by 0.24% and 7.26% respectively. The proportion of 'No Injury' crashes increased from 76.7% to 78.1% of all crashes.

Severity is per crash event (most severe injury). 28 fatal crash events resulted in 30 persons killed.

Outcome by Severity (Crash Events)

Fatal28fatal crashes0.2%
-24.3%prior 37
Serious Injury178serious injury crashes1.3%
21.1%prior 147
Minor Injury1,693minor injury crashes11.9%
-0.2%prior 1,697
Possible Injury1,213possible injury crashes8.6%
-7.3%prior 1,308
No Injury11,068no injury crashes78.1%
5.7%prior 10,475

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

Crashes occurring in 'Clear' weather conditions increased by 4.80%, from 9,661 to 10,125. Crashes during 'Rain' increased by 13.08% (from 1,651 to 1,867), while 'Cloudy' conditions saw a 9.28% decrease in crashes. Crashes on 'Wet' road surfaces increased by 7.27%, from 2,586 to 2,774.

Weather

Clear10,125 (71.4%)
4.8%prior 9,661
Rain1,867 (13.2%)
13.1%prior 1,651
Cloudy1,809 (12.8%)
-9.3%prior 1,994
Snow179 (1.3%)
7.2%prior 167
Other/Unknown165 (1.2%)
13.8%prior 145
Fog; Smog; Smoke19 (0.1%)
5.6%prior 18
Sleet; Hail6 (0.0%)
-64.7%prior 17
Blowing Sand; Soil; Dirt; Snow5 (0.0%)
Freezing Rain or Freezing Drizzle4 (0.0%)
Severe Crosswinds1 (0.0%)
-88.9%prior 9

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

Lighting

Daylight9,401 (66.3%)
4.8%prior 8,970
Dark - Lighted Roadway3,621 (25.5%)
-1.2%prior 3,665
Dawn/Dusk709 (5.0%)
15.8%prior 612
Dark - Roadway Not Lighted228 (1.6%)
19.4%prior 191
Other/Unknown138 (1.0%)
-5.5%prior 146
Dark - Unknown Roadway Lighting83 (0.6%)
3.8%prior 80

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

Road Surface

Dry11,103 (78.3%)
2.7%prior 10,808
Wet2,774 (19.6%)
7.3%prior 2,586
Other/Unknown126 (0.9%)
8.6%prior 116
Snow120 (0.8%)
14.3%prior 105
Ice45 (0.3%)
12.5%prior 40
Sand; Mud; Dirt; Oil; Gravel6 (0.0%)
Slush3 (0.0%)
Water (Standing; Moving)3 (0.0%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 4.14%, from 27,117 to 28,241. Sport Utility Vehicles involved in crashes increased by 10.40%, from 5,049 to 5,574, while the involvement of Passenger Cars increased by 2.19%. Among vehicle makes, TOYOTA saw a 7.61% increase in involvement, and JEEP increased by 13.26%. The age group 0-15 saw a 10.32% decrease in persons involved in crashes, while the 65+ age group increased by 5.76%.

Top Vehicle Makes (28,241 vehicles)

1
FORD3,269 (11.6%)
-0.8%prior 3,294
2
CHEVROLET3,220 (11.4%)
-0.3%prior 3,230
3
TOYOTA3,039 (10.8%)
7.6%prior 2,824
4
HONDA2,933 (10.4%)
4.2%prior 2,815
5
NISSAN1,802 (6.4%)
4.4%prior 1,726
6
HYUNDAI1,278 (4.5%)
6.9%prior 1,195
7
KIA1,161 (4.1%)
5.7%prior 1,098
8
DODGE892 (3.2%)
-1.2%prior 903
9
JEEP854 (3%)
13.3%prior 754
10
MAZDA578 (2%)
10.5%prior 523

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

3,777 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (26,206 persons with recorded sex)

Male14,647 (55.9%)
5.1%prior 13,940
Female11,559 (44.1%)
1.3%prior 11,408

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: Cincinnati, OH
  • Total crash records analyzed: 14,180
  • Total persons involved: 29,345
  • Total vehicles involved: 28,241

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). "Cincinnati, 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/cincinnati/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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Cincinnati, OH Crash Report — 2024 | ThatCarHitMe.com