Yearly Traffic Safety Analysis

1,606 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Marion County recorded 1,606 vehicle crashes, an increase from the 1,525 crashes documented in 2023, representing a 5.3% year-over-year rise. While total fatalities decreased from 11 to 8, the number of persons injured in these incidents grew by 17.9%, from 591 in the prior period to 697 in the current period.

1,606

5.3%was 1,525

Total Crash Events

8

-27.3%was 11

Persons Killed

697

17.9%was 591

Persons Injured

204

-2.4%was 209

Hit-and-Run Crashes

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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

Overall traffic crash trends in Marion County show an increase in volume and injuries year-over-year. Total crashes rose by 5.3% from 1,525 in 2023 to 1,606 in 2024. Concurrently, total injuries increased by 17.9%, while fatalities saw a decrease from 11 to 8.

204

Hit-and-Run Crashes — 2024

-2.4% vs prior (209)

Hit-and-run incidents showed a slight downward trend in Marion County. The total number of hit-and-run crashes decreased from 209 in 2023 to 204 in 2024. Correspondingly, the hit-and-run rate fell from 13.7% of all crashes in the prior period to 12.7% in the current period.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 0%

6

Motorists Killed

Prior: 11-45.5%

12

Pedestrians Injured

Prior: 771.4%

685

Motorists Injured

Prior: 58417.3%

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 temporal patterns of crashes in Marion County showed some shifts between 2023 and 2024. The peak day for collisions moved from Wednesday (244 crashes) in the prior year to Friday (276 crashes) in the current year. The peak hour for crashes remained consistent at 3 p.m. in both periods, though the number of incidents during that hour decreased from 122 to 115.

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

The severity of crashes in Marion County shifted year-over-year. The percentage of fatal crashes decreased from 0.7% of total incidents in 2023 to 0.5% in 2024. Conversely, the proportion of crashes resulting in an injury of any severity increased, rising from 27.2% of all crashes to 29.6%. This was driven by an increase in the share of minor injury crashes, which grew from 14.7% to 16.1% of the total.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.5%
-20.0%prior 10
Serious Injury38serious injury crashes2.4%
-7.3%prior 41
Minor Injury258minor injury crashes16.1%
15.2%prior 224
Possible Injury179possible injury crashes11.1%
20.1%prior 149
No Injury1,123no injury crashes69.9%
2.0%prior 1,101

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

The environmental conditions during crashes remained largely consistent year-over-year, with most incidents in both periods occurring in daylight on dry roads. In 2024, crashes in clear weather accounted for 68.1% of the total, a slight decrease from 70.0% in 2023. A notable shift occurred in crashes on snowy roads, which increased from 1.4% of all incidents in the prior year to 4.0% in the current year, with the absolute count rising from 21 to 65.

Weather

Clear1,094 (68.1%)
2.4%prior 1,068
Cloudy271 (16.9%)
3.8%prior 261
Rain149 (9.3%)
13.7%prior 131
Snow66 (4.1%)
73.7%prior 38
Other/Unknown12 (0.7%)
-29.4%prior 17
Fog; Smog; Smoke8 (0.5%)
-11.1%prior 9
Sleet; Hail4 (0.2%)
Severe Crosswinds2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight1,016 (63.3%)
3.4%prior 983
Dark - Roadway Not Lighted335 (20.9%)
7.4%prior 312
Dark - Lighted Roadway133 (8.3%)
-5.7%prior 141
Dawn/Dusk104 (6.5%)
55.2%prior 67
Dark - Unknown Roadway Lighting9 (0.6%)
12.5%prior 8
Other/Unknown9 (0.6%)
-35.7%prior 14

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,245 (77.5%)
1.6%prior 1,225
Wet281 (17.5%)
11.1%prior 253
Snow65 (4.0%)
209.5%prior 21
Ice7 (0.4%)
-41.7%prior 12
Other/Unknown6 (0.4%)
-25.0%prior 8
Sand; Mud; Dirt; Oil; Gravel1 (0.1%)
Water (Standing; Moving)1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

An analysis of vehicles and persons involved in crashes shows some demographic shifts year-over-year. The top three vehicle makes remained Chevrolet, Ford, and Honda, but Ford (384 vehicles) surpassed Honda (335 vehicles) for the second-most common make in 2024. Regarding persons involved, the largest cohort shifted from the 35-44 age group in 2023 to the 26-34 age group in 2024. The number of individuals aged 65 and older involved in crashes also increased from 424 to 465.

Top Vehicle Makes (2,660 vehicles)

1
CHEVROLET421 (15.8%)
-3.0%prior 434
2
FORD384 (14.4%)
15.0%prior 334
3
HONDA335 (12.6%)
-5.1%prior 353
4
TOYOTA209 (7.9%)
5.0%prior 199
5
DODGE168 (6.3%)
9.8%prior 153
6
HYUNDAI133 (5%)
9.9%prior 121
7
JEEP110 (4.1%)
10.0%prior 100
8
GMC92 (3.5%)
9.5%prior 84
9
NISSAN85 (3.2%)
11.8%prior 76
10
KIA81 (3%)
-12.0%prior 92

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

152 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (3,334 persons with recorded sex)

Male1,806 (54.2%)
5.9%prior 1,705
Female1,528 (45.8%)
2.2%prior 1,495

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 5, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,606
  • Total persons involved: 3,452
  • Total vehicles involved: 2,660

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: 2024." Published July 5, 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/statewide/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

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Marion County, OH Crash Report — 2024 | ThatCarHitMe.com