Yearly Traffic Safety Analysis

1,295 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Huron County recorded 1,295 total vehicle crashes, a 2.5% increase from the 1,264 crashes reported in 2024. While overall crashes and injuries saw slight increases, crashes involving a driver under the influence (DUI) decreased by 21% year-over-year, from 62 to 49 incidents.

1,295

▲ 2.5%was 1,264

Total Crash Events

▲ 25.0%was 4

Persons Killed

409

▲ 3.0%was 397

Persons Injured

▲ 16.2%was 68

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Huron County showed a slight increase year-over-year. Total crashes rose by 2.5%, from 1,264 in 2024 to 1,295 in 2025. Similarly, the number of people injured increased by 3.0% to 409, and total fatalities rose from 4 to 5.

Hit-and-Run Crashes — 2025

▲ 16.2% vs prior (68)

Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. There were 79 hit-and-run crashes in 2025, an increase of 16.2% from the 68 recorded in 2024. The hit-and-run rate consequently rose from 5.4% to 6.1% of all crashes during this period.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 1↓-100.0%

Motorists Killed

Prior: 3↑66.7%

Pedestrians Injured

Prior: 5↑40.0%

402

Motorists Injured

Prior: 392↑2.6%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In 2025, the peak day for crashes was Monday with 211 incidents, a change from 2024 when Friday was the peak day with 216 crashes. The peak hour also moved earlier in the day, from 6 p.m. in 2024 (88 crashes) to 2 p.m. in 2025 (84 crashes).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate increased from 0.32% in 2024 to 0.39% in 2025, with 5 fatal crashes compared to 4 in the prior year. While the proportion of serious injury crashes decreased from 2.9% to 2.1%, crashes resulting in minor injuries rose from 11.2% to 13.9% of all incidents. The share of non-injury crashes decreased slightly from 78.6% to 77.3%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.4%

↑25.0%prior 4

Serious Injury27serious injury crashes2.1%

↓-27.0%prior 37

Minor Injury180minor injury crashes13.9%

↑27.7%prior 141

Possible Injury82possible injury crashes6.3%

↓-6.8%prior 88

No Injury1,001no injury crashes77.3%

↑0.7%prior 994

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The most significant shift in crash conditions was related to winter weather. Crashes occurring in snow conditions more than doubled, from 49 in 2024 to 120 in 2025, and those on snowy roads increased from 40 to 132. Consequently, the proportion of crashes on dry roads decreased from 79.4% to 72.4% year-over-year. The distribution of crashes by lighting conditions remained largely consistent, with daylight crashes accounting for 56.1% of incidents in 2025 compared to 52.8% in 2024.

Weather

Clear779 (60.2%)

↓-5.3%prior 823

Cloudy274 (21.2%)

↑3.8%prior 264

Snow120 (9.3%)

↑144.9%prior 49

Rain92 (7.1%)

↓-13.2%prior 106

Fog; Smog; Smoke17 (1.3%)

↑6.3%prior 16

Severe Crosswinds4 (0.3%)

Blowing Sand; Soil; Dirt; Snow3 (0.2%)

Sleet; Hail3 (0.2%)

Other/Unknown2 (0.2%)

Freezing Rain or Freezing Drizzle1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight726 (56.1%)

↑8.7%prior 668

Dark - Roadway Not Lighted386 (29.8%)

↓-0.5%prior 388

Dark - Lighted Roadway88 (6.8%)

↓-7.4%prior 95

Dawn/Dusk85 (6.6%)

↓-18.3%prior 104

Dark - Unknown Roadway Lighting8 (0.6%)

↑60.0%prior 5

Other/Unknown2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry938 (72.4%)

↓-6.6%prior 1,004

Wet180 (13.9%)

↓-6.3%prior 192

Snow132 (10.2%)

↑230.0%prior 40

Ice38 (2.9%)

↑72.7%prior 22

Slush6 (0.5%)

Other/Unknown1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The makeup of vehicles involved in crashes saw minor shifts, with Ford (384 vehicles) narrowly surpassing Chevrolet (380 vehicles) as the most common make in 2025, reversing the order from the previous year. An analysis of persons involved shows increases across several age groups, particularly the 21-25 group which grew from 237 to 283 individuals, and the 65+ group which increased from 307 to 338. The 16-20 age group also saw an increase in involvement, from 327 to 343 persons.

Top Vehicle Makes (1,936 vehicles)

FORD384 (19.8%)

↑0.3%prior 383

CHEVROLET380 (19.6%)

↓-6.4%prior 406

KIA108 (5.6%)

↑50.0%prior 72

DODGE105 (5.4%)

↑2.9%prior 102

HONDA104 (5.4%)

↑16.9%prior 89

HYUNDAI100 (5.2%)

↑44.9%prior 69

JEEP97 (5%)

↓-4.9%prior 102

TOYOTA83 (4.3%)

↓-16.2%prior 99

GMC61 (3.2%)

↓-18.7%prior 75

BUICK53 (2.7%)

↑17.8%prior 45

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (2,415 persons with recorded sex)

Male1,335 (55.3%)

↑5.5%prior 1,266

Female1,080 (44.7%)

↑3.9%prior 1,039

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
Report generated: July 5, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 1,295
Total persons involved: 2,484
Total vehicles involved: 1,936

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: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2025-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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1,295 CRASHES INOHIO, OH2025