Yearly Traffic Safety Analysis

11,803 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In Lucas County, total traffic crashes decreased by 3.8% from 12,266 in 2022 to 11,803 in 2023. Despite this overall reduction in collisions, the most notable year-over-year shift was a significant 32.5% increase in traffic fatalities, which rose from 40 to 53.

11,803

▼ -3.8%was 12,266

Total Crash Events

▲ 32.5%was 40

Persons Killed

4,457

▼ -3.8%was 4,635

Persons Injured

2,931

▼ -6.2%was 3,126

Hit-and-Run Crashes

Note: "Persons Killed" (53) counts individual fatalities across all crash events. "Fatal" in the severity table below (51) 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 for traffic incidents in Lucas County shows a decrease in volume but an increase in severity. Total crashes fell by 3.8% and total injuries decreased by a similar 3.8%. However, this positive trend was offset by a substantial 32.5% rise in fatalities, from 40 in 2022 to 53 in 2023.

2,931

Hit-and-Run Crashes — 2023

▼ -6.2% vs prior (3,126)

The number of hit-and-run incidents decreased from 3,126 in 2022 to 2,931 in 2023. This decline is reflected in the hit-and-run rate, which fell from 25.5% of all crashes in the prior year to 24.8% in the current year. The trend for hit-and-run crashes is moving downward, consistent with the overall reduction in total crashes.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 3↑133.3%

Motorists Killed

Prior: 37↑24.3%

110

Pedestrians Injured

Prior: 101↑8.9%

4,347

Motorists Injured

Prior: 4,534↓-4.1%

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 largely consistent between the two periods. Friday continued to be the peak day for crashes in both 2023 (1,930 incidents) and 2022 (1,985 incidents). Similarly, the 4 p.m. hour was the peak time for collisions in both years, accounting for 1,022 crashes in 2023 and 1,124 in 2022, reflecting the overall decrease in crash volume without a shift in daily or weekly patterns.

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 worsened year-over-year. The number of fatal crashes increased from 38 in 2022 to 51 in 2023, and the fatal crash rate rose from 0.31% to 0.43%. In contrast, the number of crashes involving serious injuries decreased from 234 to 208. The proportion of non-injury crashes remained stable at 74.3% across both years.

Severity is per crash event (most severe injury). 51 fatal crash events resulted in 53 persons killed.

Outcome by Severity (Crash Events)

Fatal51fatal crashes0.4%

↑34.2%prior 38

Serious Injury208serious injury crashes1.8%

↓-11.1%prior 234

Minor Injury1,466minor injury crashes12.4%

↓-6.1%prior 1,562

Possible Injury1,310possible injury crashes11.1%

↓-0.8%prior 1,321

No Injury8,768no injury crashes74.3%

↓-3.8%prior 9,111

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 majority of crashes in both 2022 and 2023 occurred during daylight (66.3% in 2023) and on dry roads (75.2% in 2023). However, there was a proportional increase in crashes under adverse weather conditions in the current period. Crashes in the rain increased from 1,100 in 2022 to 1,420 in 2023, and collisions on wet road surfaces rose from 2,107 to 2,408 over the same period.

Weather

Clear7,574 (64.2%)

↓-7.1%prior 8,152

Cloudy2,191 (18.6%)

↓-6.1%prior 2,333

Rain1,420 (12.0%)

↑29.1%prior 1,100

Snow381 (3.2%)

↓-16.1%prior 454

Other/Unknown135 (1.1%)

↑7.1%prior 126

Fog; Smog; Smoke65 (0.6%)

↑124.1%prior 29

Freezing Rain or Freezing Drizzle19 (0.2%)

↓-29.6%prior 27

Sleet; Hail10 (0.1%)

↓-50.0%prior 20

Severe Crosswinds6 (0.1%)

↓-40.0%prior 10

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

↓-86.7%prior 15

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

Lighting

Daylight7,821 (66.3%)

↓-2.8%prior 8,050

Dark - Lighted Roadway2,570 (21.8%)

↓-9.3%prior 2,833

Dawn/Dusk687 (5.8%)

↑16.0%prior 592

Dark - Roadway Not Lighted513 (4.3%)

↓-3.9%prior 534

Dark - Unknown Roadway Lighting135 (1.1%)

↓-21.1%prior 171

Other/Unknown77 (0.7%)

↓-10.5%prior 86

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

Road Surface

Dry8,873 (75.2%)

↓-5.2%prior 9,355

Wet2,408 (20.4%)

↑14.3%prior 2,107

Snow263 (2.2%)

↓-45.9%prior 486

Ice133 (1.1%)

↓-29.3%prior 188

Other/Unknown108 (0.9%)

↓-4.4%prior 113

Sand; Mud; Dirt; Oil; Gravel8 (0.1%)

Slush8 (0.1%)

↓-42.9%prior 14

Water (Standing; Moving)2 (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 remained consistent, with Chevrolet (3,452), Ford (3,346), and Dodge (1,904) being the top three in 2023, mirroring the ranking from 2022. The distribution of vehicle types was also stable, led by Passenger Cars and Sport Utility Vehicles in both years. The age demographics of persons involved in crashes showed no significant shifts, with the 26-34 age group representing the largest cohort in both periods.

Top Vehicle Makes (22,648 vehicles)

CHEVROLET3,452 (15.2%)

↓-5.5%prior 3,651

FORD3,346 (14.8%)

↓-8.1%prior 3,639

DODGE1,904 (8.4%)

↓-6.2%prior 2,030

JEEP1,562 (6.9%)

↑2.4%prior 1,526

HONDA1,544 (6.8%)

↑7.6%prior 1,435

TOYOTA1,032 (4.6%)

↓-2.5%prior 1,059

CHRYSLER914 (4%)

↓-4.9%prior 961

KIA849 (3.7%)

↑2.2%prior 831

GMC787 (3.5%)

↑6.2%prior 741

NISSAN688 (3%)

↓-5.8%prior 730

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

2,977 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (26,168 persons with recorded sex)

Male13,769 (52.6%)

↓-2.3%prior 14,090

Female12,399 (47.4%)

↓-3.6%prior 12,858

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 6, 2026

Data Coverage

Reporting period: 2023-01-01 through 2023-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 11,803
Total persons involved: 28,229
Total vehicles involved: 22,648

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 6, 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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11,803 CRASHES INOHIO, OH2023