Yearly Traffic Safety Analysis

1,121 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Washington County recorded 1,121 total crashes, a 5.1% decrease from the 1,181 crashes reported in 2021. The most notable change year-over-year was a significant 19.4% reduction in the number of people injured, which fell from 448 in 2021 to 361 in 2022. However, the number of fatalities increased from 7 to 8 during the same period.

1,121

-5.1%was 1,181

Total Crash Events

8

14.3%was 7

Persons Killed

361

-19.4%was 448

Persons Injured

77

-23.0%was 100

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

Overall, traffic crashes in Washington County showed a downward trend from 2021 to 2022, with total incidents decreasing by 5.1% from 1,181 to 1,121. This decline was accompanied by a 19.4% drop in total injuries. In contrast, the number of fatalities increased by one person, from 7 in 2021 to 8 in 2022.

77

Hit-and-Run Crashes — 2022

-23.0% vs prior (100)

Hit-and-run incidents saw a notable decrease in 2022 compared to the previous year. The total number of hit-and-run crashes fell by 23%, from 100 in 2021 to 77 in 2022. Correspondingly, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also trended down from 8.5% to 6.9%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 3-66.7%

7

Motorists Killed

Prior: 475.0%

5

Pedestrians Injured

Prior: 425.0%

356

Motorists Injured

Prior: 444-19.8%

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 2021 and 2022. The peak day for crashes moved from Friday, with 210 incidents in 2021, to Thursday, with 187 incidents in 2022. Similarly, the peak hour for collisions shifted from the 3 p.m. hour in 2021 (105 crashes) to the 4 p.m. hour in 2022 (95 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

In 2022, the fatal crash rate increased to 0.71% from 0.51% in the prior year, with 8 fatal crashes compared to 6. The proportion of crashes resulting in any form of injury (serious, minor, or possible) decreased from a combined 28.2% of all crashes in 2021 to 24.2% in 2022. Correspondingly, the share of crashes with no reported injuries rose from 71.3% to 75.2% year-over-year.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.7%
33.3%prior 6
Serious Injury31serious injury crashes2.8%
-22.5%prior 40
Minor Injury134minor injury crashes12%
-17.3%prior 162
Possible Injury105possible injury crashes9.4%
-19.8%prior 131
No Injury843no injury crashes75.2%
0.1%prior 842

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 environmental conditions during crashes remained largely consistent between 2021 and 2022. In both years, the majority of crashes occurred in clear weather (61.5% in 2022 vs. 63.8% in 2021) and on dry roads (77.1% vs. 77.9%). Crashes in daylight accounted for 67.6% of incidents in 2022, a slight proportional decrease from 69.1% in the prior year, indicating no major shifts in conditions.

Weather

Clear690 (61.6%)
-8.4%prior 753
Cloudy257 (22.9%)
4.5%prior 246
Rain102 (9.1%)
-7.3%prior 110
Snow50 (4.5%)
11.1%prior 45
Fog; Smog; Smoke9 (0.8%)
-43.8%prior 16
Other/Unknown6 (0.5%)
-25.0%prior 8
Blowing Sand; Soil; Dirt; Snow4 (0.4%)
Sleet; Hail2 (0.2%)
Freezing Rain or Freezing Drizzle1 (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

Daylight758 (67.6%)
-7.1%prior 816
Dark - Roadway Not Lighted232 (20.7%)
-0.9%prior 234
Dark - Lighted Roadway61 (5.4%)
3.4%prior 59
Dawn/Dusk53 (4.7%)
-17.2%prior 64
Other/Unknown9 (0.8%)
28.6%prior 7
Dark - Unknown Roadway Lighting8 (0.7%)

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

Road Surface

Dry864 (77.1%)
-6.1%prior 920
Wet181 (16.1%)
-10.0%prior 201
Snow46 (4.1%)
53.3%prior 30
Ice21 (1.9%)
5.0%prior 20
Other/Unknown6 (0.5%)
0.0%prior 6
Slush2 (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 top three vehicle makes involved in crashes—Ford, Chevrolet, and Toyota—remained the same in 2022 as in 2021, with counts for each decreasing slightly. The largest age group of persons involved in crashes shifted from the 26-34 bracket in 2021 (372 people) to the 35-44 bracket in 2022 (332 people). The proportional representation of other age groups remained relatively stable.

Top Vehicle Makes (1,823 vehicles)

1
FORD324 (17.8%)
-5.5%prior 343
2
CHEVROLET287 (15.7%)
-10.0%prior 319
3
TOYOTA182 (10%)
-2.2%prior 186
4
HONDA103 (5.7%)
5.1%prior 98
5
DODGE93 (5.1%)
-13.9%prior 108
6
NISSAN88 (4.8%)
35.4%prior 65
7
GMC82 (4.5%)
28.1%prior 64
8
KIA71 (3.9%)
-17.4%prior 86
9
JEEP62 (3.4%)
-26.2%prior 84
10
HYUNDAI57 (3.1%)
-17.4%prior 69

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

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

Sex Distribution (2,216 persons with recorded sex)

Male1,249 (56.4%)
-5.8%prior 1,326
Female967 (43.6%)
-9.6%prior 1,070

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: 1,121
  • Total persons involved: 2,268
  • Total vehicles involved: 1,823

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