Yearly Traffic Safety Analysis

1,207 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In Huron County, total traffic crashes decreased slightly from 1,232 in 2021 to 1,207 in 2022, a 2.0% reduction. While total fatalities remained unchanged at four, the number of fatal crashes increased from three to four. One of the most notable year-over-year shifts was a 32.9% decrease in crashes involving a driver suspected of being under the influence, which fell from 76 to 51 incidents.

1,207

-2.0%was 1,232

Total Crash Events

4

Persons Killed

359

0.8%was 356

Persons Injured

75

-19.4%was 93

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Huron County showed a slight decline between 2021 and 2022. The total number of crashes decreased by 2.0%, from 1,232 to 1,207. Despite this small drop in total incidents, the number of people injured saw a marginal increase from 356 to 359, while fatalities held steady at four year-over-year.

75

Hit-and-Run Crashes — 2022

-19.4% vs prior (93)

Hit-and-run incidents in Huron County saw a notable decrease between 2021 and 2022. The total number of hit-and-run crashes fell from 93 to 75. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, declined from 7.5% in 2021 to 6.2% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

4

Motorists Killed

Prior: 40.0%

4

Pedestrians Injured

Prior: 7-42.9%

355

Motorists Injured

Prior: 3491.7%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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 2022, Friday was the peak day for crashes with 222 incidents, a change from 2021 when Monday was the most frequent day with 193 crashes. The peak hour also shifted from 3 p.m. in 2021 (96 crashes) to 5 p.m. in 2022 (101 crashes), indicating a potential change in evening commute collision patterns.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes showed mixed changes year-over-year. The number of fatal crashes increased from 3 in 2021 to 4 in 2022, raising the fatal crash rate from 0.24% to 0.33%. Conversely, crashes resulting in serious injuries decreased from 29 to 23. Crashes involving minor injuries increased from 155 to 165, while those with no injuries reported decreased from 977 to 952.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.3%
33.3%prior 3
Serious Injury23serious injury crashes1.9%
-20.7%prior 29
Minor Injury165minor injury crashes13.7%
6.5%prior 155
Possible Injury63possible injury crashes5.2%
-7.4%prior 68
No Injury952no injury crashes78.9%
-2.6%prior 977

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crash conditions remained largely stable between 2021 and 2022, with no major shifts in weather or road surface contributions. In both years, clear weather and dry roads were the predominant conditions, accounting for 63.9% and 75.5% of crashes in 2022, respectively, compared to 63.1% and 77.0% in 2021. There was a slight increase in the proportion of crashes occurring in dark, unlighted conditions, which rose from 29.3% of all crashes in 2021 to 32.8% in 2022.

Weather

Clear771 (63.9%)
-0.9%prior 778
Cloudy253 (21.0%)
-11.5%prior 286
Rain80 (6.6%)
-5.9%prior 85
Snow70 (5.8%)
29.6%prior 54
Fog; Smog; Smoke16 (1.3%)
45.5%prior 11
Other/Unknown8 (0.7%)
33.3%prior 6
Blowing Sand; Soil; Dirt; Snow3 (0.2%)
Freezing Rain or Freezing Drizzle3 (0.2%)
-40.0%prior 5
Sleet; Hail2 (0.2%)
Severe Crosswinds1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight651 (53.9%)
-1.5%prior 661
Dark - Roadway Not Lighted396 (32.8%)
9.7%prior 361
Dark - Lighted Roadway85 (7.0%)
-13.3%prior 98
Dawn/Dusk65 (5.4%)
-35.6%prior 101
Dark - Unknown Roadway Lighting5 (0.4%)
-16.7%prior 6
Other/Unknown5 (0.4%)
0.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry911 (75.5%)
-4.0%prior 949
Wet172 (14.3%)
-9.5%prior 190
Snow75 (6.2%)
23.0%prior 61
Ice37 (3.1%)
48.0%prior 25
Other/Unknown5 (0.4%)
Slush4 (0.3%)
Sand; Mud; Dirt; Oil; Gravel2 (0.2%)
Water (Standing; Moving)1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The composition of vehicles involved in crashes and driver demographics remained consistent year-over-year. Passenger cars, Sport Utility Vehicles, and Pick-ups were the top three vehicle types involved in both 2021 and 2022, with nearly identical involvement counts. Similarly, the top vehicle makes, led by Chevrolet and Ford, saw only minor fluctuations in their numbers, reflecting the overall stability in crash volume. The age distribution of persons involved in crashes also showed no significant changes between the two periods.

Top Vehicle Makes (1,807 vehicles)

1
CHEVROLET372 (20.6%)
-5.8%prior 395
2
FORD334 (18.5%)
-9.7%prior 370
3
DODGE102 (5.6%)
-16.4%prior 122
4
HONDA100 (5.5%)
19.0%prior 84
5
KIA95 (5.3%)
26.7%prior 75
6
TOYOTA84 (4.6%)
1.2%prior 83
7
JEEP82 (4.5%)
-3.5%prior 85
8
GMC67 (3.7%)
26.4%prior 53
9
HYUNDAI67 (3.7%)
52.3%prior 44
10
BUICK48 (2.7%)
14.3%prior 42

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (2,360 persons with recorded sex)

Male1,325 (56.1%)
2.6%prior 1,292
Female1,035 (43.9%)
4.5%prior 990

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,207
  • Total persons involved: 2,458
  • Total vehicles involved: 1,807

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: 2022." Published July 5, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2022-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 — 2022 | ThatCarHitMe.com