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Yearly Traffic Safety Analysis

12,926 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Summit County recorded 12,926 total traffic crashes, a decrease of 11.5% from the 14,604 crashes documented in 2022. While overall crashes and injuries declined, the most notable shift was an increase in the rate of crashes resulting in a fatality or serious injury. Total fatalities rose slightly from 45 to 46 year-over-year.

12,926

▼ -11.5%was 14,604

Total Crash Events

▲ 2.2%was 45

Persons Killed

3,914

▼ -9.7%was 4,335

Persons Injured

2,512

▼ -14.7%was 2,944

Hit-and-Run Crashes

Note: "Persons Killed" (46) counts individual fatalities across all crash events. "Fatal" in the severity table below (45) 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

Traffic safety data for Summit County shows a downward trend in overall crash volume. Total crashes fell by 1,678 incidents from 14,604 in 2022 to 12,926 in 2023. Similarly, total injuries decreased by 9.7% from 4,335 to 3,914. However, the number of fatalities increased slightly from 45 to 46.

2,512

Hit-and-Run Crashes — 2023

▼ -14.7% vs prior (2,944)

Hit-and-run incidents trended downward in 2023 compared to the prior year. The total number of hit-and-run crashes decreased by 14.7%, from 2,944 in 2022 to 2,512 in 2023. The hit-and-run rate also fell, with such incidents comprising 19.4% of all crashes in 2023, down from 20.2% in 2022.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 9↑33.3%

Motorists Killed

Prior: 36↓-5.6%

140

Pedestrians Injured

Prior: 116↑20.7%

3,774

Motorists Injured

Prior: 4,219↓-10.5%

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 remained consistent year-over-year. Friday was the peak day for crashes in both 2023 (2,090 crashes) and 2022 (2,471 crashes), and the 4 p.m. hour was the peak hour in both periods (1,163 and 1,240 crashes, respectively). The overall reduction in crashes was reflected in these peak times, with 381 fewer crashes on Fridays and 77 fewer crashes during the 4 p.m. hour in 2023 compared to the prior year.

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 decreased, the severity of crashes increased year-over-year. The fatal crash rate rose from 0.28% in 2022 to 0.35% in 2023, with fatal crashes increasing from 41 to 45. The proportion of crashes involving a serious injury also grew, accounting for 2.0% of all crashes (254 incidents) in 2023 compared to 1.5% (220 incidents) in 2022.

Severity is per crash event (most severe injury). 45 fatal crash events resulted in 46 persons killed.

Outcome by Severity (Crash Events)

Fatal45fatal crashes0.3%

↑9.8%prior 41

Serious Injury254serious injury crashes2%

↑15.5%prior 220

Minor Injury1,327minor injury crashes10.3%

↓-10.9%prior 1,489

Possible Injury1,179possible injury crashes9.1%

↓-16.0%prior 1,403

No Injury10,121no injury crashes78.3%

↓-11.6%prior 11,451

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

The distribution of crashes by lighting conditions remained nearly identical between the two periods, with daylight crashes accounting for approximately 67% in both years. Regarding road surface, crashes on snowy roads decreased significantly from 826 in 2022 to 418 in 2023. However, crashes occurring in rainy weather increased from 1,332 to 1,545 over the same period.

Weather

Clear7,138 (55.2%)

↓-13.2%prior 8,225

Cloudy3,373 (26.1%)

↓-10.6%prior 3,774

Rain1,545 (12.0%)

↑16.0%prior 1,332

Snow623 (4.8%)

↓-35.3%prior 963

Other/Unknown161 (1.2%)

↓-17.9%prior 196

Fog; Smog; Smoke53 (0.4%)

↑10.4%prior 48

Freezing Rain or Freezing Drizzle12 (0.1%)

↓-52.0%prior 25

Sleet; Hail11 (0.1%)

↓-45.0%prior 20

Severe Crosswinds8 (0.1%)

↑14.3%prior 7

Blowing Sand; Soil; Dirt; Snow2 (0.0%)

↓-85.7%prior 14

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

Lighting

Daylight8,713 (67.4%)

↓-12.1%prior 9,914

Dark - Lighted Roadway2,520 (19.5%)

↓-13.5%prior 2,913

Dawn/Dusk783 (6.1%)

↑3.3%prior 758

Dark - Roadway Not Lighted718 (5.6%)

↓-11.4%prior 810

Other/Unknown112 (0.9%)

↓-18.2%prior 137

Dark - Unknown Roadway Lighting80 (0.6%)

↑11.1%prior 72

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

Road Surface

Dry9,539 (73.8%)

↓-11.0%prior 10,720

Wet2,690 (20.8%)

↑0.4%prior 2,678

Snow418 (3.2%)

↓-49.4%prior 826

Other/Unknown137 (1.1%)

↓-19.9%prior 171

Ice115 (0.9%)

↓-29.0%prior 162

Slush14 (0.1%)

↓-64.1%prior 39

Water (Standing; Moving)12 (0.1%)

↑100.0%prior 6

Sand; Mud; Dirt; Oil; Gravel1 (0.0%)

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

Vehicles & Demographics

The primary vehicle makes involved in crashes were consistent year-over-year, with Ford (3,261) and Chevrolet (3,107) leading in 2023, similar to the prior year. The age distribution of persons involved in crashes also remained largely stable, though there was a slight proportional increase in the 65+ age group, which grew from representing 10.3% of persons in 2022 to 11.1% in 2023.

Top Vehicle Makes (24,228 vehicles)

FORD3,261 (13.5%)

↓-11.6%prior 3,688

CHEVROLET3,107 (12.8%)

↓-13.6%prior 3,597

HONDA1,883 (7.8%)

↓-8.4%prior 2,056

TOYOTA1,817 (7.5%)

↓-12.1%prior 2,067

KIA1,289 (5.3%)

↑0.3%prior 1,285

HYUNDAI1,197 (4.9%)

↓-8.2%prior 1,304

JEEP1,179 (4.9%)

↓-9.6%prior 1,304

NISSAN1,121 (4.6%)

↓-13.0%prior 1,288

DODGE1,114 (4.6%)

↓-24.3%prior 1,472

OTHER/UNKNOWN731 (3%)

↑14.4%prior 639

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

2,379 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (28,471 persons with recorded sex)

Male15,284 (53.7%)

↓-9.1%prior 16,821

Female13,187 (46.3%)

↓-9.5%prior 14,564

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: August 22, 2026

Data Coverage

Reporting period: 2023-01-01 through 2023-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 12,926
Total persons involved: 30,655
Total vehicles involved: 24,228

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 August 22, 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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