ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GREEN, 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/green/2022-annual-report
Yearly Traffic Safety Analysis
3,090 CRASHES IN
GREEN, OH
2022
Total crashes in Green decreased by 2.83% year-over-year, from 3180 in 2021 to 3090 in 2022. The most notable shift was an 8.32% reduction in total injuries, decreasing from 1010 to 926. Fatalities remained stable at 18 in both periods.
3,090
▼ -2.8%was 3,180
Total Crash Events
18
Persons Killed
926
▼ -8.3%was 1,010
Persons Injured
376
▼ -4.8%was 395
Hit-and-Run Crashes
Note: "Persons Killed" (18) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) 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, the trend indicates a slight decrease in crash activity, with total crashes falling by 2.83% from 3180 in 2021 to 3090 in 2022. While total fatalities remained constant at 18, total injuries experienced a more significant decline of 8.32%, decreasing from 1010 to 926.
376
Hit-and-Run Crashes — 2022
▼ -4.8% vs prior (395)
Hit-and-run crashes decreased from 395 in 2021 to 376 in 2022, representing a reduction of 19 incidents. Concurrently, the hit-and-run crash rate slightly declined from 12.4% in 2021 to 12.2% in 2022. This indicates a minor downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
3
Pedestrians Killed
15
Motorists Killed
10
Pedestrians Injured
916
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 day for crashes remained Friday in both years, though the count decreased from 550 in 2021 to 500 in 2022. Similarly, the peak hour for crashes remained 5 p.m., with crash counts decreasing from 284 in 2021 to 257 in 2022. This suggests a consistent temporal pattern for peak activity, albeit with reduced volumes.
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 fatal crash rate slightly decreased from 0.57% in 2021 to 0.55% in 2022, with fatal crashes decreasing from 18 to 17. The proportion of serious injuries (A) decreased from 2.0% to 1.7%, and minor injuries (B) decreased from 12.2% to 11.6%. Overall, the percentage of crashes resulting in any injury type (A, B, or C) decreased from 21.8% in 2021 to 20.5% in 2022.
Severity is per crash event (most severe injury). 17 fatal crash events resulted in 18 persons killed.
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
Crashes occurring in clear weather decreased from 1922 in 2021 to 1826 in 2022, while crashes in snowy conditions increased from 116 to 163. Regarding road surface conditions, crashes on wet surfaces decreased from 641 to 587, but crashes on snowy surfaces increased from 98 to 148. Daylight crashes also saw a reduction from 2105 to 2040.
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
The total number of vehicles involved in crashes decreased from 5534 in 2021 to 5364 in 2022. Chevrolet became the most frequently involved vehicle make in 2022 with 813 vehicles, surpassing Ford which dropped from 864 to 771. In terms of persons involved, the 26-34 age group saw a decrease of 134 persons (1092 to 958), while the 65+ age group experienced an increase from 787 to 857 persons.
Top Vehicle Makes (5,364 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
323 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (6,677 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 5, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: Green, OH
- Total crash records analyzed: 3,090
- Total persons involved: 6,915
- Total vehicles involved: 5,364
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). "Green, 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/green/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 5, 2026 · All rights reserved