Yearly Traffic Safety Analysis

1,385 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Union County recorded 1,385 total crashes, a 9.1% increase from the 1,269 crashes reported in 2021. This rise in collisions was accompanied by an increase in fatalities, which grew from 5 in 2021 to 7 in 2022. The number of serious injury crashes also saw a notable increase, rising from 32 to 43 year-over-year.

1,385

9.1%was 1,269

Total Crash Events

7

40.0%was 5

Persons Killed

460

5.0%was 438

Persons Injured

132

5.6%was 125

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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

Crash data for Union County indicates an upward trend from 2021 to 2022. Total crashes increased by 9.1%, from 1,269 to 1,385. Similarly, the number of people injured rose by 5.0% from 438 to 460, and total fatalities increased from 5 to 7.

132

Hit-and-Run Crashes — 2022

5.6% vs prior (125)

The number of hit-and-run incidents in Union County increased from 125 in 2021 to 132 in 2022. However, due to the overall increase in total crashes during the same period, the hit-and-run rate slightly decreased. Hit-and-runs constituted 9.5% of all crashes in 2022, down from 9.9% in the prior year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

6

Motorists Killed

Prior: 520.0%

5

Pedestrians Injured

Prior: 2150.0%

455

Motorists Injured

Prior: 4364.4%

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 in Union County remained largely consistent between 2021 and 2022. Friday was the peak day for crashes in both years, with 246 incidents in 2022 and 247 in 2021. The peak hour for crashes shifted slightly earlier, from the 5 p.m. hour in 2021 (109 crashes) to the 4 p.m. hour in 2022 (122 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 increased in 2022 compared to the prior year. The fatal crash rate rose from 0.39% to 0.51%, with 7 fatal crashes in 2022 versus 5 in 2021. The proportion of crashes resulting in serious injuries also increased, from 2.5% of crashes in 2021 to 3.1% in 2022.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.5%
40.0%prior 5
Serious Injury43serious injury crashes3.1%
34.4%prior 32
Minor Injury151minor injury crashes10.9%
3.4%prior 146
Possible Injury125possible injury crashes9%
1.6%prior 123
No Injury1,059no injury crashes76.5%
10.0%prior 963

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 different environmental conditions remained highly consistent between 2021 and 2022. In both years, a majority of incidents occurred in Daylight (58.7% in 2022 vs. 59.3% in 2021) and on Dry road surfaces (76.7% in both periods). Crashes in Clear weather also accounted for a similar proportion of the total, representing 66.8% of crashes in 2022 compared to 65.0% in 2021, indicating no significant shift in the role of adverse conditions.

Weather

Clear925 (66.8%)
12.1%prior 825
Cloudy240 (17.3%)
4.8%prior 229
Rain116 (8.4%)
8.4%prior 107
Snow65 (4.7%)
-5.8%prior 69
Fog; Smog; Smoke10 (0.7%)
11.1%prior 9
Other/Unknown9 (0.6%)
12.5%prior 8
Freezing Rain or Freezing Drizzle8 (0.6%)
-50.0%prior 16
Blowing Sand; Soil; Dirt; Snow7 (0.5%)
Severe Crosswinds4 (0.3%)
Sleet; Hail1 (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

Daylight813 (58.7%)
8.1%prior 752
Dark - Roadway Not Lighted359 (25.9%)
13.2%prior 317
Dawn/Dusk103 (7.4%)
21.2%prior 85
Dark - Lighted Roadway92 (6.6%)
8.2%prior 85
Other/Unknown10 (0.7%)
-44.4%prior 18
Dark - Unknown Roadway Lighting8 (0.6%)
-33.3%prior 12

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

Road Surface

Dry1,063 (76.8%)
9.1%prior 974
Wet213 (15.4%)
6.5%prior 200
Snow66 (4.8%)
34.7%prior 49
Ice29 (2.1%)
3.6%prior 28
Other/Unknown8 (0.6%)
-38.5%prior 13
Slush4 (0.3%)
Water (Standing; Moving)2 (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 top three vehicle makes involved in crashes remained Honda, Ford, and Chevrolet in both 2021 and 2022. While Honda's involvement decreased from 496 to 469 vehicles, it remained the most common make, and Ford's involvement increased from 243 to 326 vehicles. An analysis of persons involved in crashes shows a higher representation from the 65+ age group, which accounted for 9.6% of individuals in 2022, up from 8.3% in 2021.

Top Vehicle Makes (2,236 vehicles)

1
HONDA469 (21%)
-5.4%prior 496
2
FORD326 (14.6%)
34.2%prior 243
3
CHEVROLET228 (10.2%)
0.0%prior 228
4
TOYOTA173 (7.7%)
39.5%prior 124
5
OTHER/UNKNOWN128 (5.7%)
96.9%prior 65
6
NISSAN89 (4%)
25.4%prior 71
7
DODGE88 (3.9%)
-7.4%prior 95
8
HYUNDAI72 (3.2%)
75.6%prior 41
9
JEEP55 (2.5%)
-16.7%prior 66
10
KIA43 (1.9%)
-8.5%prior 47

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

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

Sex Distribution (2,827 persons with recorded sex)

Male1,632 (57.7%)
13.6%prior 1,436
Female1,195 (42.3%)
10.6%prior 1,080

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: 1,385
  • Total persons involved: 2,919
  • Total vehicles involved: 2,236

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

ThatCarHitMe.com · An Injuria.ai Company

Union County, OH Crash Report — 2022 | ThatCarHitMe.com