Yearly Traffic Safety Analysis

618 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In Champaign County, total traffic crashes increased by 7.5% from 575 in 2023 to 618 in 2024. This period also saw a 24.1% rise in injuries and a 40% increase in fatalities. One of the most significant shifts was a 45.3% decrease in crashes involving a driver under the influence (DUI), which fell from 53 incidents in the prior year to 29 in the current year.

618

7.5%was 575

Total Crash Events

7

40.0%was 5

Persons Killed

252

24.1%was 203

Persons Injured

64

-5.9%was 68

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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 safety trends in Champaign County worsened year-over-year. Total crashes rose from 575 to 618, marking a 7.5% increase. The number of people injured increased by 24.1% from 203 to 252, and the number of fatalities rose from 5 to 7.

64

Hit-and-Run Crashes — 2024

-5.9% vs prior (68)

Hit-and-run incidents showed a downward trend in Champaign County. The total number of hit-and-run crashes decreased from 68 in 2023 to 64 in 2024. The hit-and-run rate, as a percentage of all crashes, also declined from 11.8% to 10.4% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

7

Motorists Killed

Prior: 475.0%

5

Pedestrians Injured

Prior: 425.0%

247

Motorists Injured

Prior: 19924.1%

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 showed a slight shift between the two periods. The peak day for crashes moved from Friday (102 crashes) in the prior year to Thursday (108 crashes) in the current year. Similarly, the peak hour for collisions shifted from the 3 p.m. hour in 2023 to the 4 p.m. hour in 2024, which recorded 66 crashes.

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

While the number of fatal crashes increased from 5 to 6 year-over-year, the distribution of injury severity shifted. The proportion of crashes resulting in serious injuries decreased from 7.1% to 4.9%. Conversely, crashes involving possible injuries saw a notable increase, rising from 6.3% of all crashes in the prior year to 10.2% in the current year.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1%
20.0%prior 5
Serious Injury30serious injury crashes4.9%
-26.8%prior 41
Minor Injury81minor injury crashes13.1%
15.7%prior 70
Possible Injury63possible injury crashes10.2%
75.0%prior 36
No Injury438no injury crashes70.9%
3.5%prior 423

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

While the majority of crashes in both years occurred in clear weather on dry roads, the data shows a significant increase in crashes under adverse winter conditions. Crashes occurring in snow more than doubled from 14 to 35 incidents year-over-year. Correspondingly, collisions on snowy or icy road surfaces also saw a marked increase, rising from a combined 20 incidents in 2023 to 47 in 2024.

Weather

Clear432 (69.9%)
9.6%prior 394
Cloudy82 (13.3%)
-11.8%prior 93
Rain57 (9.2%)
11.8%prior 51
Snow35 (5.7%)
150.0%prior 14
Other/Unknown5 (0.8%)
-16.7%prior 6
Fog; Smog; Smoke5 (0.8%)
-44.4%prior 9
Sleet; Hail2 (0.3%)

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

Lighting

Daylight411 (66.5%)
5.4%prior 390
Dark - Roadway Not Lighted113 (18.3%)
5.6%prior 107
Dark - Lighted Roadway48 (7.8%)
23.1%prior 39
Dawn/Dusk38 (6.1%)
31.0%prior 29
Other/Unknown5 (0.8%)
-50.0%prior 10
Dark - Unknown Roadway Lighting3 (0.5%)

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

Road Surface

Dry466 (75.4%)
3.1%prior 452
Wet100 (16.2%)
3.1%prior 97
Snow29 (4.7%)
163.6%prior 11
Ice18 (2.9%)
100.0%prior 9
Other/Unknown4 (0.6%)
-20.0%prior 5
Slush1 (0.2%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes—Chevrolet, Honda, and Ford—remained consistent across both years, with their involvement increasing in line with the overall rise in crashes. An analysis of persons involved in crashes shows the largest year-over-year increases occurred in the 26-34 and 65+ age groups. Both demographics saw an increase of 42 individuals involved in crashes compared to the prior year.

Top Vehicle Makes (1,063 vehicles)

1
CHEVROLET201 (18.9%)
23.3%prior 163
2
HONDA180 (16.9%)
22.4%prior 147
3
FORD155 (14.6%)
16.5%prior 133
4
DODGE61 (5.7%)
-14.1%prior 71
5
HYUNDAI46 (4.3%)
48.4%prior 31
6
TOYOTA45 (4.2%)
-11.8%prior 51
7
KIA30 (2.8%)
66.7%prior 18
8
JEEP28 (2.6%)
-22.2%prior 36
9
NISSAN27 (2.5%)
3.8%prior 26
10
GMC25 (2.4%)
-26.5%prior 34

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

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

Sex Distribution (1,277 persons with recorded sex)

Male734 (57.5%)
12.9%prior 650
Female543 (42.5%)
12.9%prior 481

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: 618
  • Total persons involved: 1,315
  • Total vehicles involved: 1,063

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