Monthly Traffic Safety Analysis

21,119 CRASHES IN
OHIO, OH
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Ohio recorded 21,119 total traffic crashes, a 5.3% increase from the 20,056 crashes documented in September 2023. Despite the rise in overall collisions, the most notable year-over-year shift was a significant 22.4% decrease in traffic-related fatalities, which fell from 125 to 97.

21,119

5.3%was 20,056

Total Crash Events

97

-22.4%was 125

Persons Killed

8,187

0.1%was 8,176

Persons Injured

3,566

2.2%was 3,490

Hit-and-Run Crashes

Note: "Persons Killed" (97) counts individual fatalities across all crash events. "Fatal" in the severity table below (95) 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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows an increase in total crashes, rising by 5.3% from 20,056 in September 2023 to 21,119 in September 2024. However, the severity of these incidents decreased, as total injuries remained nearly stable with a 0.1% increase, while fatalities dropped by 22.4% compared to the same month in the prior year.

3,566

Hit-and-Run Crashes — September 2024

2.2% vs prior (3,490)

The absolute number of hit-and-run incidents increased from 3,490 in September 2023 to 3,566 in September 2024. However, due to a larger increase in total crashes, the hit-and-run rate trended downward. The proportion of all crashes classified as a hit-and-run decreased from 17.4% in the prior year to 16.9% in the current period.

Vulnerable Road User Casualties

7

Pedestrians Killed

Prior: 12-41.7%

90

Motorists Killed

Prior: 113-20.4%

241

Pedestrians Injured

Prior: 2371.7%

7,946

Motorists Injured

Prior: 7,9390.1%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes remained largely consistent year-over-year. Friday was the peak day for collisions in both September 2024 (3,648 crashes) and September 2023 (4,057 crashes). The peak hour for crashes shifted slightly later in the day, moving from the 3 p.m. hour in the prior period (1,722 crashes) to the 4 p.m. hour in the current period (1,793 crashes).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash outcomes were less severe in September 2024 compared to the prior year, with the fatal crash rate declining from 0.61% to 0.45%. While the proportion of serious injury crashes increased slightly from 2.9% to 3.0%, the share of both minor and possible injury crashes decreased. Consequently, the percentage of crashes resulting in no injury rose from 71.5% in September 2023 to 72.7% in September 2024.

Severity is per crash event (most severe injury). 95 fatal crash events resulted in 97 persons killed.

Outcome by Severity (Crash Events)

Fatal95fatal crashes0.4%
-22.1%prior 122
Serious Injury625serious injury crashes3%
8.1%prior 578
Minor Injury2,936minor injury crashes13.9%
1.2%prior 2,902
Possible Injury2,116possible injury crashes10%
-0.3%prior 2,122
No Injury15,347no injury crashes72.7%
7.1%prior 14,332

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Road & Environmental Conditions

A greater proportion of crashes occurred under adverse conditions in September 2024 compared to the previous year. The share of crashes happening in the rain increased from 5.4% to 14.3% of the monthly total. Similarly, collisions on wet road surfaces more than doubled as a percentage of all crashes, rising from 9.1% to 19.2%. The proportion of crashes in daylight remained stable at around 71% for both periods.

Weather

Clear14,537 (68.8%)
-1.2%prior 14,720
Cloudy3,289 (15.6%)
-14.6%prior 3,851
Rain3,022 (14.3%)
180.1%prior 1,079
Other/Unknown188 (0.9%)
35.3%prior 139
Fog; Smog; Smoke65 (0.3%)
-74.9%prior 259
Severe Crosswinds11 (0.1%)
Sleet; Hail4 (0.0%)
Freezing Rain or Freezing Drizzle2 (0.0%)
Snow1 (0.0%)
-80.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight14,934 (70.7%)
4.5%prior 14,296
Dark - Lighted Roadway2,661 (12.6%)
3.9%prior 2,560
Dark - Roadway Not Lighted2,043 (9.7%)
6.5%prior 1,918
Dawn/Dusk1,201 (5.7%)
15.1%prior 1,043
Other/Unknown183 (0.9%)
28.0%prior 143
Dark - Unknown Roadway Lighting97 (0.5%)
1.0%prior 96

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry16,917 (80.1%)
-6.7%prior 18,124
Wet4,056 (19.2%)
122.7%prior 1,821
Other/Unknown120 (0.6%)
23.7%prior 97
Water (Standing; Moving)15 (0.1%)
Sand; Mud; Dirt; Oil; Gravel8 (0.0%)
-42.9%prior 14
Snow2 (0.0%)
Ice1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes remained consistent year-over-year. Passenger Cars, Sport Utility Vehicles, and Pick-up trucks were the top three vehicle types in both periods, with their counts increasing in line with the overall rise in crashes. The ranking of the top three vehicle makes was also unchanged, with Chevrolet, Ford, and Honda being the most frequently involved in both September 2024 and September 2023.

Top Vehicle Makes (38,630 vehicles)

1
CHEVROLET5,327 (13.8%)
1.7%prior 5,238
2
FORD5,263 (13.6%)
3.5%prior 5,087
3
HONDA3,649 (9.4%)
4.9%prior 3,478
4
TOYOTA3,101 (8%)
10.1%prior 2,816
5
NISSAN1,794 (4.6%)
11.4%prior 1,611
6
DODGE1,653 (4.3%)
-1.5%prior 1,678
7
JEEP1,600 (4.1%)
7.3%prior 1,491
8
KIA1,580 (4.1%)
5.8%prior 1,494
9
HYUNDAI1,511 (3.9%)
5.4%prior 1,433
10
OTHER/UNKNOWN1,117 (2.9%)
16.2%prior 961

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

3,257 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (46,628 persons with recorded sex)

Male25,699 (55.1%)
5.6%prior 24,325
Female20,929 (44.9%)
3.6%prior 20,194

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 21,119
  • Total persons involved: 49,177
  • Total vehicles involved: 38,630

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: September 2024." Published July 5, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/september-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

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Ohio (Statewide) Crash Report — September 2024 | ThatCarHitMe.com