Yearly Traffic Safety Analysis

1,924 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In Ross County, total traffic crashes decreased by 4.6% from 2,017 in 2021 to 1,924 in 2022. This overall reduction was accompanied by a significant drop in traffic-related fatalities, which fell from 13 in the prior year to 8 in the current year, a 38.5% decrease. The total number of injuries also saw a slight decline from 756 to 737.

1,924

-4.6%was 2,017

Total Crash Events

8

-38.5%was 13

Persons Killed

737

-2.5%was 756

Persons Injured

218

-8.0%was 237

Hit-and-Run Crashes

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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

The overall trend in traffic incidents in Ross County is downward year-over-year. Total crashes fell by 4.6%, from 2,017 in 2021 to 1,924 in 2022. This trend extends to crash severity, with total fatalities decreasing from 13 to 8 and total injuries declining from 756 to 737 over the same period.

218

Hit-and-Run Crashes — 2022

-8.0% vs prior (237)

Hit-and-run incidents saw a decrease in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell from 237 in 2021 to 218 in 2022. The hit-and-run rate also declined slightly, from 11.8% in the prior year to 11.3% in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

7

Motorists Killed

Prior: 12-41.7%

8

Pedestrians Injured

Prior: 9-11.1%

729

Motorists Injured

Prior: 747-2.4%

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 showed little change between the two years. Friday remained the peak day for crashes in both 2022 (322 crashes) and 2021 (354 crashes). The peak hour for incidents shifted slightly earlier, moving from the 4 p.m. hour in 2021 (173 crashes) to the 3 p.m. hour in 2022 (164 crashes).

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 lessened in 2022 compared to the previous year. The fatal crash rate fell from 0.59% to 0.42%, with fatal crashes decreasing from 12 to 8. The proportion of crashes resulting in serious injuries also saw a slight decline from 2.7% to 2.6%, while the percentage of crashes with no injuries increased from 73.4% to 73.5%.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.4%
-33.3%prior 12
Serious Injury50serious injury crashes2.6%
-9.1%prior 55
Minor Injury321minor injury crashes16.7%
-2.4%prior 329
Possible Injury131possible injury crashes6.8%
-6.4%prior 140
No Injury1,414no injury crashes73.5%
-4.5%prior 1,481

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

The distribution of crashes across various environmental conditions remained largely unchanged year-over-year. In both 2021 and 2022, approximately 76.7% of crashes occurred on dry road surfaces and around 63.5% took place in daylight. The proportion of crashes in clear weather was 57.1% in 2022, a minor decrease from 59.0% in 2021, indicating no significant shift in the role of adverse conditions.

Weather

Clear1,099 (57.1%)
-7.6%prior 1,190
Cloudy528 (27.4%)
-0.2%prior 529
Rain179 (9.3%)
-14.4%prior 209
Snow68 (3.5%)
25.9%prior 54
Fog; Smog; Smoke32 (1.7%)
39.1%prior 23
Other/Unknown7 (0.4%)
-22.2%prior 9
Sleet; Hail7 (0.4%)
Freezing Rain or Freezing Drizzle2 (0.1%)
Severe Crosswinds2 (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

Daylight1,220 (63.4%)
-5.3%prior 1,288
Dark - Roadway Not Lighted458 (23.8%)
-4.2%prior 478
Dark - Lighted Roadway127 (6.6%)
10.4%prior 115
Dawn/Dusk108 (5.6%)
-8.5%prior 118
Other/Unknown7 (0.4%)
-30.0%prior 10
Dark - Unknown Roadway Lighting4 (0.2%)
-50.0%prior 8

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

Road Surface

Dry1,478 (76.8%)
-4.5%prior 1,547
Wet328 (17.0%)
-9.4%prior 362
Snow70 (3.6%)
29.6%prior 54
Ice38 (2.0%)
-5.0%prior 40
Sand; Mud; Dirt; Oil; Gravel4 (0.2%)
Slush4 (0.2%)
-20.0%prior 5
Other/Unknown2 (0.1%)
-71.4%prior 7

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

Vehicles & Demographics

The top vehicle makes involved in crashes were consistent year-over-year, with Chevrolet (498) and Ford (484) leading in 2022, similar to 2021. An analysis of persons involved in crashes reveals a shift in age groups; the proportion of individuals aged 16-20 increased from 11.4% of total persons in 2021 to 13.0% in 2022. Conversely, the 0-15 age group's representation decreased from 12.3% to 9.3%.

Top Vehicle Makes (3,126 vehicles)

1
CHEVROLET498 (15.9%)
-2.5%prior 511
2
FORD484 (15.5%)
-4.9%prior 509
3
TOYOTA266 (8.5%)
20.9%prior 220
4
HONDA228 (7.3%)
-12.6%prior 261
5
HYUNDAI210 (6.7%)
-2.3%prior 215
6
DODGE180 (5.8%)
-21.1%prior 228
7
KIA161 (5.2%)
14.2%prior 141
8
JEEP145 (4.6%)
-8.8%prior 159
9
NISSAN120 (3.8%)
-15.5%prior 142
10
GMC88 (2.8%)
2.3%prior 86

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

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

Sex Distribution (4,006 persons with recorded sex)

Male2,152 (53.7%)
-4.6%prior 2,255
Female1,854 (46.3%)
-5.4%prior 1,960

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 6, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,924
  • Total persons involved: 4,151
  • Total vehicles involved: 3,126

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 6, 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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Ross County, OH Crash Report — 2022 | ThatCarHitMe.com