ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · JUNE 2024
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/june-2024-report
Monthly Traffic Safety Analysis
263 CRASHES IN
OHIO, OH
JUNE 2024
In Allen County, total traffic crashes increased from 209 in June 2023 to 263 in June 2024, a 25.8% rise. This increase was accompanied by a rise in total injuries from 89 to 103, while fatalities remained at zero for both periods. The most notable year-over-year shift was the significant increase in the raw number of crashes across most categories, including those involving minor injuries and hit-and-runs.
263
▲ 25.8%was 209
Total Crash Events
0
Persons Killed
103
▲ 15.7%was 89
Persons Injured
51
▲ 70.0%was 30
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 · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Allen County indicates a rising trend year-over-year. Total crashes increased by 25.8%, from 209 in June 2023 to 263 in June 2024. Similarly, the number of people injured in these incidents grew by 15.7%, from 89 to 103, though no fatalities were recorded in either period.
51
Hit-and-Run Crashes — June 2024
▲ 70.0% vs prior (30)
Hit-and-run incidents increased in both count and rate year-over-year. The number of hit-and-run crashes rose from 30 in June 2023 to 51 in June 2024. This pushed the hit-and-run rate up from 14.4% to 19.4% of all crashes, indicating a worsening trend for this crash type.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
3
Pedestrians Injured
100
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak time for crashes remained consistent, with both periods showing a peak on Fridays and during the 4 p.m. hour. However, a notable shift occurred in the daily distribution of crashes. Wednesdays saw a substantial increase, rising from 20 crashes in June 2023 to become the second-busiest day with 42 crashes in June 2024.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
No fatal crashes were recorded in either June 2023 or June 2024. However, the severity of non-fatal crashes increased. Crashes resulting in serious injuries rose from 7 to 11, and minor injury crashes increased from 22 to 41. Consequently, the proportion of crashes with no reported injuries decreased from 74.2% to 72.2% year-over-year.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record
Road & Environmental Conditions
While the majority of crashes in both periods occurred during daylight in clear weather, there was a proportional increase in incidents under adverse conditions. The percentage of crashes on wet roads grew from 9.6% in June 2023 to 14.4% in June 2024. Similarly, crashes occurring in rainy conditions increased from 7.2% to 10.7% of the total.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field
Vehicles & Demographics
Ford, Chevrolet, and Honda remained the top three vehicle makes involved in crashes, with each showing an increase in total count compared to the prior year. A notable demographic shift was observed among persons involved in crashes; the 16-20 age group saw its involvement increase from 59 individuals to 99, becoming the largest single age cohort in June 2024.
Top Vehicle Makes (475 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records
40 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (579 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2024-06-01 through 2024-06-30 (30 days)
- Geographic scope: ohio, OH
- Total crash records analyzed: 263
- Total persons involved: 612
- Total vehicles involved: 475
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: June 2024." Published July 6, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/june-2024-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: 2024-06-01 – 2024-06-30
Generated: July 6, 2026 · All rights reserved