ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/ohio/statewide/2022-annual-report
Yearly Traffic Safety Analysis
1,746 CRASHES IN
OHIO, OH
2022
In Scioto County, total traffic crashes remained stable, with 1,746 incidents in 2022 compared to 1,734 in 2021, an increase of less than 1%. While overall volume was steady, the number of fatalities rose from 7 to 9. The most notable year-over-year shift was a significant decrease in crashes involving a driver under the influence, which fell from 120 in 2021 to 61 in 2022.
1,746
▲ 0.7%was 1,734
Total Crash Events
9
▲ 28.6%was 7
Persons Killed
606
▲ 5.8%was 573
Persons Injured
245
▼ -3.9%was 255
Hit-and-Run Crashes
Note: "Persons Killed" (9) 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
Overall crash volume in Scioto County was stable, increasing by just 12 incidents (0.7%) from 1,734 in 2021 to 1,746 in 2022. However, the severity of these crashes worsened, with total injuries rising 5.8% from 573 to 606 and total fatalities increasing from 7 to 9 people.
245
Hit-and-Run Crashes — 2022
▼ -3.9% vs prior (255)
Hit-and-run incidents showed a slight downward trend in Scioto County. The total number of hit-and-run crashes decreased from 255 in 2021 to 245 in 2022. Consequently, the hit-and-run rate as a percentage of all crashes fell from 14.7% to 14.0%.
Vulnerable Road User Casualties
3
Pedestrians Killed
6
Motorists Killed
6
Pedestrians Injured
600
Motorists Injured
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 peak hour for crashes remained the 4 p.m. hour in both 2021 and 2022, though the number of incidents in that hour decreased from 143 to 133. The most common day for crashes shifted from Wednesday (284 crashes) in 2021 to Friday (307 crashes) in 2022. This change was driven by a notable increase in Friday crashes year-over-year.
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 number of fatal crashes increased from 7 in 2021 to 9 in 2022, raising the fatal crash rate from 0.4% to 0.5% of all incidents. The count and proportion of serious injury crashes were unchanged at 55 incidents, representing 3.2% of crashes in both years. Minor injury crashes saw a proportional increase, rising from 13.1% to 14.2% of all collisions.
Outcome by Severity (Crash Events)
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 by environmental conditions was largely consistent between the two years. The proportion of crashes occurring on dry road surfaces increased slightly from 74.0% to 76.3%. Crashes in daylight conditions remained the majority but saw their share of the total decrease from 66.9% in 2021 to 64.4% in 2022, while crashes on unlighted dark roadways increased from 19.0% to 20.7%.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
Passenger Cars, Sport Utility Vehicles, and Pickups were the three most common vehicle types in collisions for both periods, with relatively stable numbers. Chevrolet was the top make involved in crashes in both years with an identical count of 625, while the number of Fords involved decreased from 488 to 417. The 35-44 age group became the largest cohort of people involved in crashes in 2022 with 521 individuals, surpassing the 26-34 age group, which was the largest in 2021 with 533 individuals.
Top Vehicle Makes (2,879 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
207 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,446 persons with recorded sex)
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: 1,746
- Total persons involved: 3,606
- Total vehicles involved: 2,879
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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2022-01-01 – 2022-12-31
Generated: July 6, 2026 · All rights reserved