Monthly Traffic Safety Analysis

24,364 CRASHES IN
OHIO, OH
DECEMBER 2022

All metrics benchmarked againstDecember 2021

In December 2022, there were 24,364 total crashes recorded in Ohio, a 3.9% increase from the 23,458 crashes in December 2021. While overall fatalities and injuries saw a slight decrease, the most notable year-over-year shift was a substantial increase in crashes occurring in adverse weather, with incidents in snow conditions rising from 578 to 2,594.

24,364

3.9%was 23,458

Total Crash Events

96

-3.0%was 99

Persons Killed

7,661

-1.4%was 7,768

Persons Injured

4,142

4.9%was 3,947

Hit-and-Run Crashes

Note: "Persons Killed" (96) counts individual fatalities across all crash events. "Fatal" in the severity table below (88) 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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume increased by 3.9% in December 2022 compared to the same month in the prior year, rising from 23,458 to 24,364. Despite the rise in total crashes, the number of people killed or injured saw a slight decline. Total fatalities decreased from 99 to 96, and total injuries fell from 7,768 to 7,661.

4,142

Hit-and-Run Crashes — December 2022

4.9% vs prior (3,947)

Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. In December 2022, there were 4,142 hit-and-run crashes, up from 3,947 in December 2021. This represents a slight increase in the hit-and-run rate, which rose from 16.8% to 17.0% of all crashes.

Vulnerable Road User Casualties

17

Pedestrians Killed

Prior: 21-19.0%

79

Motorists Killed

Prior: 781.3%

188

Pedestrians Injured

Prior: 230-18.3%

7,473

Motorists Injured

Prior: 7,538-0.9%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-12-01 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 of day with the highest crash frequency remained consistent year-over-year, with the 5 PM hour being the peak in both December 2022 (2,236 crashes) and December 2021 (2,275 crashes). However, the peak day for crashes shifted from Wednesday (4,177 crashes) in the prior period to Friday (4,815 crashes) in the current period. Crashes on both Thursdays and Fridays saw notable increases in December 2022 compared to the previous year.

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

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

Crash Severity Breakdown

The severity of crashes decreased slightly in December 2022 compared to the previous year. The number of fatal crashes fell from 97 to 88, and the fatal crash rate per 100 crashes dropped from 0.41 to 0.36. The proportion of crashes resulting in any injury (serious, minor, or possible) also decreased from 23.0% to 22.1% of all incidents. Correspondingly, the share of crashes with no reported injuries increased from 76.6% to 77.6%.

Severity is per crash event (most severe injury). 88 fatal crash events resulted in 96 persons killed.

Outcome by Severity (Crash Events)

Fatal88fatal crashes0.4%
-9.3%prior 97
Serious Injury383serious injury crashes1.6%
-13.2%prior 441
Minor Injury2,651minor injury crashes10.9%
-0.3%prior 2,659
Possible Injury2,345possible injury crashes9.6%
1.9%prior 2,301
No Injury18,897no injury crashes77.6%
5.2%prior 17,960

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

Severity Distribution (Crash Events)

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

Road & Environmental Conditions

The most significant year-over-year change was in weather and road surface conditions. In December 2022, crashes occurring in snow increased from 578 to 2,594, and those on icy roads rose from 290 to 1,374. Consequently, the proportion of crashes on dry roads fell from 68.1% in the prior year to 54.7% in the current year. In contrast, lighting conditions at the time of crashes remained stable, with the distribution between daylight, dark-lighted roadways, and dark-unlighted roadways showing minimal change.

Weather

Clear9,967 (40.9%)
-15.0%prior 11,726
Cloudy7,966 (32.7%)
16.0%prior 6,870
Rain2,664 (10.9%)
-27.7%prior 3,686
Snow2,594 (10.6%)
348.8%prior 578
Blowing Sand; Soil; Dirt; Snow413 (1.7%)
Other/Unknown282 (1.2%)
13.7%prior 248
Fog; Smog; Smoke271 (1.1%)
58.5%prior 171
Severe Crosswinds143 (0.6%)
186.0%prior 50
Freezing Rain or Freezing Drizzle38 (0.2%)
-37.7%prior 61
Sleet; Hail26 (0.1%)
-61.2%prior 67

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

Lighting

Daylight11,512 (47.3%)
5.7%prior 10,890
Dark - Lighted Roadway6,127 (25.1%)
0.8%prior 6,080
Dark - Roadway Not Lighted4,724 (19.4%)
3.8%prior 4,549
Dawn/Dusk1,610 (6.6%)
3.4%prior 1,557
Other/Unknown220 (0.9%)
10.6%prior 199
Dark - Unknown Roadway Lighting171 (0.7%)
-6.6%prior 183

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

Road Surface

Dry13,323 (54.7%)
-16.6%prior 15,978
Wet6,288 (25.8%)
-2.6%prior 6,455
Snow2,986 (12.3%)
602.6%prior 425
Ice1,374 (5.6%)
373.8%prior 290
Other/Unknown192 (0.8%)
-5.4%prior 203
Slush182 (0.7%)
203.3%prior 60
Sand; Mud; Dirt; Oil; Gravel10 (0.0%)
-54.5%prior 22
Water (Standing; Moving)9 (0.0%)
-64.0%prior 25

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

Vehicles & Demographics

The types and makes of vehicles involved in crashes remained broadly consistent year-over-year. Passenger Cars, Sport Utility Vehicles, and Pick-ups were the three most common vehicle types in both December 2022 and December 2021. The top vehicle makes involved, led by Chevrolet and Ford, also showed no significant changes in ranking or volume. Similarly, the age distribution of persons in crashes was stable, with the 26-34 age group representing the largest cohort in both periods.

Top Vehicle Makes (42,605 vehicles)

1
CHEVROLET6,325 (14.8%)
0.2%prior 6,311
2
FORD6,013 (14.1%)
2.0%prior 5,894
3
HONDA3,557 (8.3%)
-2.7%prior 3,655
4
TOYOTA3,397 (8%)
5.8%prior 3,210
5
DODGE2,125 (5%)
3.1%prior 2,062
6
NISSAN1,933 (4.5%)
0.7%prior 1,919
7
JEEP1,808 (4.2%)
10.0%prior 1,644
8
KIA1,723 (4%)
10.8%prior 1,555
9
HYUNDAI1,710 (4%)
4.8%prior 1,632
10
GMC1,181 (2.8%)
8.5%prior 1,088

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

3,981 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (50,727 persons with recorded sex)

Male27,925 (55.0%)
6.0%prior 26,344
Female22,802 (45.0%)
0.8%prior 22,625

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

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 24,364
  • Total persons involved: 53,857
  • Total vehicles involved: 42,605

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