Yearly Traffic Safety Analysis

1,264 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Huron County recorded 1,264 vehicle crashes, a 3.8% increase from the 1,218 crashes documented in 2023. Despite the rise in total incidents, the number of fatalities saw a significant year-over-year decrease, falling from 11 in 2023 to 4 in 2024.

1,264

3.8%was 1,218

Total Crash Events

4

-63.6%was 11

Persons Killed

397

7.9%was 368

Persons Injured

68

-15.0%was 80

Hit-and-Run Crashes

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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, total crashes in Huron County increased by 3.8% from 2023 to 2024, rising from 1,218 to 1,264 incidents. While the number of crashes rose, fatalities decreased substantially from 11 to 4. The number of people injured also increased, from 368 in the prior period to 397 in the current period.

68

Hit-and-Run Crashes — 2024

-15.0% vs prior (80)

The number of hit-and-run incidents in Huron County decreased from 80 in 2023 to 68 in 2024. This corresponds to a downward trend in the hit-and-run rate, which fell from 6.6% of all crashes in the prior year to 5.4% in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

3

Motorists Killed

Prior: 11-72.7%

5

Pedestrians Injured

Prior: 8-37.5%

392

Motorists Injured

Prior: 3608.9%

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

Crash patterns shifted slightly between the two periods. While Friday remained the peak day for crashes in both 2023 (202 crashes) and 2024 (216 crashes), the peak hour for incidents moved from 7 a.m. in 2023 (94 crashes) to 6 p.m. in 2024 (88 crashes). Crash volumes in the last three months of the year were higher in 2024 (456 crashes) compared to 2023 (399 crashes).

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

In 2024, there was a significant decrease in crash lethality, with fatal crashes dropping from 11 (0.9% of total) in 2023 to 4 (0.3% of total) in 2024. However, the number of crashes resulting in serious injuries increased from 30 to 37, representing a rise in proportion from 2.5% to 2.9% of all crashes. The proportion of crashes with no injuries remained stable, accounting for 78.0% in 2023 and 78.6% in 2024.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.3%
-63.6%prior 11
Serious Injury37serious injury crashes2.9%
23.3%prior 30
Minor Injury141minor injury crashes11.2%
-9.6%prior 156
Possible Injury88possible injury crashes7%
23.9%prior 71
No Injury994no injury crashes78.6%
4.6%prior 950

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 distribution of crashes across various environmental conditions remained stable from 2023 to 2024. In both periods, the majority of incidents occurred in daylight (51.4% in 2023, 52.8% in 2024) and on dry road surfaces (78.8% in 2023, 79.4% in 2024). There were no significant shifts in the proportion of crashes occurring in adverse weather, lighting, or road surface conditions.

Weather

Clear823 (65.1%)
2.1%prior 806
Cloudy264 (20.9%)
22.2%prior 216
Rain106 (8.4%)
-9.4%prior 117
Snow49 (3.9%)
2.1%prior 48
Fog; Smog; Smoke16 (1.3%)
-15.8%prior 19
Other/Unknown3 (0.2%)
-40.0%prior 5
Severe Crosswinds2 (0.2%)
Sleet; Hail1 (0.1%)

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

Lighting

Daylight668 (52.8%)
6.7%prior 626
Dark - Roadway Not Lighted388 (30.7%)
7.5%prior 361
Dawn/Dusk104 (8.2%)
-4.6%prior 109
Dark - Lighted Roadway95 (7.5%)
-13.6%prior 110
Dark - Unknown Roadway Lighting5 (0.4%)
-44.4%prior 9
Other/Unknown4 (0.3%)

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

Road Surface

Dry1,004 (79.4%)
4.6%prior 960
Wet192 (15.2%)
-3.5%prior 199
Snow40 (3.2%)
21.2%prior 33
Ice22 (1.7%)
37.5%prior 16
Slush3 (0.2%)
Other/Unknown1 (0.1%)
Sand; Mud; Dirt; Oil; Gravel1 (0.1%)
Water (Standing; Moving)1 (0.1%)

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

Vehicles & Demographics

Chevrolet and Ford remained the top two vehicle makes involved in crashes in both periods, with Chevrolet increasing from 359 to 406 vehicles and Ford from 358 to 383. The number of Jeeps involved in crashes rose from 82 to 102, while the count for Dodge vehicles decreased from 128 to 102. An analysis of persons involved shows an increased representation of the 16-20 age group, which grew from 277 individuals in 2023 to 327 in 2024.

Top Vehicle Makes (1,859 vehicles)

1
CHEVROLET406 (21.8%)
13.1%prior 359
2
FORD383 (20.6%)
7.0%prior 358
3
JEEP102 (5.5%)
24.4%prior 82
4
DODGE102 (5.5%)
-20.3%prior 128
5
TOYOTA99 (5.3%)
-3.9%prior 103
6
HONDA89 (4.8%)
-11.0%prior 100
7
GMC75 (4%)
44.2%prior 52
8
KIA72 (3.9%)
1.4%prior 71
9
HYUNDAI69 (3.7%)
25.5%prior 55
10
CHRYSLER48 (2.6%)
-12.7%prior 55

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

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

Sex Distribution (2,305 persons with recorded sex)

Male1,266 (54.9%)
3.4%prior 1,224
Female1,039 (45.1%)
1.6%prior 1,023

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: ohio, OH
  • Total crash records analyzed: 1,264
  • Total persons involved: 2,390
  • Total vehicles involved: 1,859

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 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/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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Huron County, OH Crash Report — 2024 | ThatCarHitMe.com