Yearly Traffic Safety Analysis

9 CRASHES IN
FRANKFORT, OH
2022

All metrics benchmarked against2021

Total crashes in Frankfort decreased by 18.18%, from 11 crashes in the prior year to 9 crashes in the current year. Despite this overall decrease, total injuries increased from 0 in the prior year to 4 in the current year. Additionally, both DUI-related and speeding-related crashes, which were absent in the prior year, were reported in the current year.

9

-18.2%was 11

Total Crash Events

0

Persons Killed

4

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 total number of crashes in Frankfort decreased by 18.18% year-over-year, from 11 crashes in the prior year to 9 crashes in the current year. Fatalities remained stable at zero in both periods. However, the number of injuries increased significantly from 0 in the prior year to 4 in the current year.

1

Hit-and-Run Crashes — 2022

11.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 0%

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 periods, though the number of crashes on Fridays decreased from 4 in the prior year to 3 in the current year. The peak crash hour shifted from 6p in the prior year to 4p in the current year, with both hours recording 2 crashes. There was a notable decrease in crashes on Wednesdays, from 3 to 1, and an increase on Mondays, from 0 to 2.

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

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes11.1%
Possible Injury1possible injury crashes11.1%
No Injury7no injury crashes77.8%

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 remained constant at 6 in both periods, while cloudy weather crashes decreased from 5 to 3. Regarding lighting conditions, crashes during daylight increased from 5 to 6, and crashes in dark, unlighted conditions decreased from 5 to 2. Crashes on dry road surfaces decreased from 10 to 5, while crashes on wet surfaces increased from 1 to 3, and one crash occurred on ice in the current year, which was not present in the prior year.

Weather

Clear6 (66.7%)
0.0%prior 6
Cloudy3 (33.3%)
-40.0%prior 5

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

Lighting

Daylight6 (66.7%)
20.0%prior 5
Dark - Roadway Not Lighted2 (22.2%)
-60.0%prior 5
Dawn/Dusk1 (11.1%)

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

Road Surface

Dry5 (55.6%)
-50.0%prior 10
Wet3 (33.3%)
Ice1 (11.1%)

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

Vehicles & Demographics

Top Vehicle Makes (15 vehicles)

1
CHEVROLET3 (20%)
2
DODGE2 (13.3%)
3
FORD2 (13.3%)
4
HYUNDAI2 (13.3%)
5
TOYOTA1 (6.7%)
6
BUICK1 (6.7%)
7
JEEP1 (6.7%)
8
KIA1 (6.7%)
9
PONTIAC1 (6.7%)

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

Sex Distribution (18 persons with recorded sex)

Female11 (61.1%)
0.0%prior 11
Male7 (38.9%)
-36.4%prior 11

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: Frankfort, OH
  • Total crash records analyzed: 9
  • Total persons involved: 18
  • Total vehicles involved: 15

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). "Frankfort, 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/frankfort/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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Frankfort, OH Crash Report — 2022 | ThatCarHitMe.com