Yearly Traffic Safety Analysis

1,588 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Marion County recorded 1,588 total vehicle crashes, a 1.6% decrease from the 1,613 crashes documented in 2021. While the total number of crashes and fatalities (10 in both years) remained relatively stable, the number of people injured in these incidents increased by 9.9%, rising from 538 in 2021 to 591 in 2022. A notable shift was observed in pedestrian-involved incidents, which doubled from 10 to 20 year-over-year.

1,588

-1.5%was 1,613

Total Crash Events

10

Persons Killed

591

9.9%was 538

Persons Injured

241

-0.4%was 242

Hit-and-Run Crashes

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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 Marion County shows a slight decline in the total number of crashes, with a 1.6% decrease from 1,613 in 2021 to 1,588 in 2022. Despite this small reduction in crash volume, the number of resulting injuries saw a notable increase of 9.9% over the same period. The number of fatalities remained unchanged at 10 for both years.

241

Hit-and-Run Crashes — 2022

-0.4% vs prior (242)

The frequency of hit-and-run incidents in Marion County remained remarkably stable between 2021 and 2022. There were 242 hit-and-run crashes in 2021, compared to 241 in 2022. The corresponding hit-and-run rate showed a negligible change, increasing slightly from 15.0% to 15.2% of all crashes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

9

Motorists Killed

Prior: 10-10.0%

19

Pedestrians Injured

Prior: 1090.0%

572

Motorists Injured

Prior: 5288.3%

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 time patterns of crashes in Marion County showed some year-over-year shifts. The most common day for crashes moved from Thursday (267 incidents) in 2021 to Friday (278 incidents) in 2022. However, the peak hour for collisions remained consistent, with the 3 p.m. hour seeing the highest frequency in both years, recording 139 crashes in 2021 and 140 in 2022.

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 distribution of crash severity saw a slight shift between 2021 and 2022. The number of fatal crashes decreased minimally from 10 to 9, representing 0.6% of all crashes in both years. While the count of serious injury crashes fell from 47 to 36, the number of crashes involving possible injuries rose from 86 to 122. Overall, the proportion of crashes resulting in any level of injury increased from 23.9% in 2021 to 26.0% in 2022.

Severity is per crash event (most severe injury). 9 fatal crash events resulted in 10 persons killed.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.6%
-10.0%prior 10
Serious Injury36serious injury crashes2.3%
-23.4%prior 47
Minor Injury254minor injury crashes16%
0.0%prior 254
Possible Injury122possible injury crashes7.7%
41.9%prior 86
No Injury1,167no injury crashes73.5%
-4.0%prior 1,216

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

Environmental conditions for crashes remained broadly consistent year-over-year, with the majority of incidents in both 2021 and 2022 occurring in clear weather and on dry roads. However, there was a notable increase in crashes reported during adverse winter conditions. Crashes on snowy roads increased from 61 in 2021 to 99 in 2022, and incidents on icy roads nearly doubled from 17 to 33.

Weather

Clear995 (62.7%)
-3.0%prior 1,026
Cloudy355 (22.4%)
-6.1%prior 378
Rain95 (6.0%)
-18.1%prior 116
Snow90 (5.7%)
55.2%prior 58
Fog; Smog; Smoke17 (1.1%)
21.4%prior 14
Other/Unknown11 (0.7%)
-26.7%prior 15
Freezing Rain or Freezing Drizzle10 (0.6%)
Blowing Sand; Soil; Dirt; Snow8 (0.5%)
Severe Crosswinds5 (0.3%)
Sleet; Hail2 (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

Daylight1,015 (63.9%)
2.3%prior 992
Dark - Roadway Not Lighted342 (21.5%)
-3.7%prior 355
Dark - Lighted Roadway113 (7.1%)
-31.5%prior 165
Dawn/Dusk85 (5.4%)
4.9%prior 81
Dark - Unknown Roadway Lighting18 (1.1%)
200.0%prior 6
Other/Unknown15 (0.9%)
7.1%prior 14

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

Road Surface

Dry1,212 (76.3%)
-2.3%prior 1,240
Wet230 (14.5%)
-17.6%prior 279
Snow99 (6.2%)
62.3%prior 61
Ice33 (2.1%)
94.1%prior 17
Other/Unknown9 (0.6%)
-30.8%prior 13
Slush3 (0.2%)
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 most common vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, and Honda leading in both 2021 and 2022. While the top makes were stable, the demographics of persons involved in crashes showed some changes as the total number of people involved increased from 3,343 to 3,565. Notably, the proportion of individuals in the 0-15 age group grew from 10.4% of all persons involved in 2021 to 14.1% in 2022.

Top Vehicle Makes (2,622 vehicles)

1
FORD404 (15.4%)
-6.0%prior 430
2
CHEVROLET392 (15%)
-7.8%prior 425
3
HONDA344 (13.1%)
6.8%prior 322
4
TOYOTA188 (7.2%)
2.2%prior 184
5
DODGE160 (6.1%)
-12.6%prior 183
6
HYUNDAI130 (5%)
-7.8%prior 141
7
JEEP93 (3.5%)
8.1%prior 86
8
KIA84 (3.2%)
18.3%prior 71
9
NISSAN75 (2.9%)
-2.6%prior 77
10
GMC71 (2.7%)
7.6%prior 66

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

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

Sex Distribution (3,429 persons with recorded sex)

Male1,901 (55.4%)
7.7%prior 1,765
Female1,528 (44.6%)
6.7%prior 1,432

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: 1,588
  • Total persons involved: 3,565
  • Total vehicles involved: 2,622

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