ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GERMANTOWN, OH · 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/germantown/2024-annual-report
Yearly Traffic Safety Analysis
89 CRASHES IN
GERMANTOWN, OH
2024
In 2024, Germantown experienced 89 crashes, an 11.25% increase from the 80 crashes recorded in 2023. Total injuries saw a substantial rise of 65%, from 20 in 2023 to 33 in 2024. The most notable year-over-year shift was a 100% decrease in fatalities, with 0 fatalities in 2024 compared to 1 in 2023.
89
▲ 11.3%was 80
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
33
▲ 65.0%was 20
Persons Injured
17
▲ 13.3%was 15
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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash incidents, with total crashes rising by 11.25% from 80 in 2023 to 89 in 2024. Concurrently, total injuries increased by 65%, from 20 in 2023 to 33 in 2024. However, fatalities decreased by 100%, from 1 in 2023 to 0 in 2024.
17
Hit-and-Run Crashes — 2024
▲ 13.3% vs prior (15)
Hit-and-run crashes increased from 15 in 2023 to 17 in 2024, representing a 13.3% rise. The hit-and-run rate also saw a slight increase, moving from 18.8% of total crashes in 2023 to 19.1% in 2024. This indicates a marginal upward trend in the proportion of crashes involving a hit-and-run component.
Vulnerable Road User Casualties
0
Motorists Killed
33
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday with 15 crashes in 2023 to Saturday with 19 crashes in 2024. The peak hour for crashes also shifted slightly, from 4 PM with 10 crashes in 2023 to 3 PM with 11 crashes in 2024. This indicates a shift in high-crash periods from midweek afternoons to weekend afternoons.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased by 100%, from 1 in 2023 to 0 in 2024. Injury crashes, however, increased, with serious injuries (code A) rising from 2 in 2023 to 5 in 2024, minor injuries (code B) from 5 to 10, and possible injuries (code C) from 7 to 10. The proportion of crashes resulting in no injury decreased from 81.3% in 2023 to 71.9% in 2024, suggesting a higher injury rate per crash.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 56 (70%) in 2023 to 67 (75.3%) in 2024, while crashes in rainy conditions decreased from 9 (11.3%) to 4 (4.5%). Crashes in dark-lighted roadway conditions increased from 17 (21.3%) in 2023 to 24 (27%) in 2024. The proportion of crashes on dry road surfaces slightly decreased from 81.3% in 2023 to 78.7% in 2024.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The number of passenger cars involved in crashes increased from 74 in 2023 to 87 in 2024, while pick-up trucks decreased from 32 to 28, and sport utility vehicles decreased from 22 to 17. Motorcycle involvement saw a significant increase, rising from 2 in 2023 to 7 in 2024. The age distribution of persons involved showed increases in the 0-15 age group (from 14 to 19) and the 35-44 age group (from 22 to 31).
Top Vehicle Makes (163 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
17 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (178 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: Germantown, OH
- Total crash records analyzed: 89
- Total persons involved: 190
- Total vehicles involved: 163
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). "Germantown, OH Crash Intelligence Report: 2024." Published July 6, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/germantown/2024-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: 2024-01-01 – 2024-12-31
Generated: July 6, 2026 · All rights reserved