Yearly Traffic Safety Analysis

4,046 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Lake County recorded 4,046 total traffic crashes, a 1.7% increase from the 3,977 crashes reported in 2023. While overall crashes saw a slight rise, the most significant year-over-year change was a 95.8% increase in bicycle-involved crashes, which rose from 24 in 2023 to 47 in 2024. Total injuries resulting from crashes decreased by 5.1% from 1,331 to 1,263, while fatalities increased by one, from 10 to 11.

4,046

1.7%was 3,977

Total Crash Events

11

10.0%was 10

Persons Killed

1,263

-5.1%was 1,331

Persons Injured

442

-7.1%was 476

Hit-and-Run Crashes

Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) 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

Crash data for Lake County indicates a relatively stable but mixed trend year-over-year. Total crashes increased by 1.7%, from 3,977 in 2023 to 4,046 in 2024. In contrast, the number of people injured in these incidents decreased by 5.1% to 1,263, while the number of fatalities rose from 10 to 11.

442

Hit-and-Run Crashes — 2024

-7.1% vs prior (476)

Hit-and-run incidents in Lake County saw a downward trend in 2024 compared to the previous year. The total number of hit-and-run crashes decreased from 476 in 2023 to 442 in 2024. This corresponds to a reduction in the hit-and-run rate, which fell from 12.0% of all crashes in the prior period to 10.9% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

11

Motorists Killed

Prior: 922.2%

29

Pedestrians Injured

Prior: 35-17.1%

1,234

Motorists Injured

Prior: 1,296-4.8%

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 timing of crashes in Lake County showed some shifts between 2023 and 2024. The peak day for collisions moved from Friday (678 crashes) in the prior year to Thursday (692 crashes) in the current year. The afternoon rush hour remained the most frequent time for crashes, with the 4 p.m. hour being the peak in both periods, recording 387 crashes in 2023 and 363 in 2024.

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 Lake County saw a slight shift towards less severe outcomes. While the number of fatal crashes increased by one from 10 to 11, they remained stable at 0.3% of all crashes in both years. The proportion of crashes resulting in a serious injury decreased from 2.5% (99 crashes) in 2023 to 2.0% (82 crashes) in 2024. Correspondingly, no-injury crashes increased as a share of the total, from 75.5% to 76.2%.

Outcome by Severity (Crash Events)

Fatal11fatal crashes0.3%
10.0%prior 10
Serious Injury82serious injury crashes2%
-17.2%prior 99
Minor Injury501minor injury crashes12.4%
3.1%prior 486
Possible Injury370possible injury crashes9.1%
-2.9%prior 381
No Injury3,082no injury crashes76.2%
2.7%prior 3,001

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

Crash conditions remained broadly similar year-over-year, with most incidents in both periods occurring in daylight on dry roads. However, there was a notable increase in crashes happening during adverse winter weather. Crashes attributed to snowy weather conditions rose from 226 in 2023 to 344 in 2024, and collisions on snow-covered road surfaces increased from 144 to 285. The proportion of crashes in daylight (70.3%) and on dry roads (72.8%) in 2024 were comparable to the prior year.

Weather

Clear2,353 (58.2%)
1.5%prior 2,318
Cloudy860 (21.3%)
-5.1%prior 906
Rain446 (11.0%)
-3.5%prior 462
Snow344 (8.5%)
52.2%prior 226
Other/Unknown12 (0.3%)
-7.7%prior 13
Fog; Smog; Smoke10 (0.2%)
-37.5%prior 16
Sleet; Hail8 (0.2%)
-60.0%prior 20
Blowing Sand; Soil; Dirt; Snow5 (0.1%)
Freezing Rain or Freezing Drizzle5 (0.1%)
-28.6%prior 7
Severe Crosswinds3 (0.1%)
-40.0%prior 5

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

Lighting

Daylight2,843 (70.3%)
0.3%prior 2,835
Dark - Lighted Roadway744 (18.4%)
8.1%prior 688
Dark - Roadway Not Lighted229 (5.7%)
4.1%prior 220
Dawn/Dusk216 (5.3%)
1.9%prior 212
Other/Unknown8 (0.2%)
-11.1%prior 9
Dark - Unknown Roadway Lighting6 (0.1%)
-53.8%prior 13

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

Road Surface

Dry2,947 (72.8%)
-0.6%prior 2,965
Wet733 (18.1%)
-8.0%prior 797
Snow285 (7.0%)
97.9%prior 144
Ice48 (1.2%)
60.0%prior 30
Slush20 (0.5%)
-25.9%prior 27
Water (Standing; Moving)6 (0.1%)
Other/Unknown5 (0.1%)
-58.3%prior 12
Sand; Mud; Dirt; Oil; Gravel2 (0.0%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet (905), Ford (880), and Honda (633) being the top three in 2024, mirroring the previous year's rankings. An analysis of persons involved shows a demographic shift, with an increase in the number of individuals aged 65 and older, who accounted for 14.9% of all persons in crashes in 2024, up from 13.8% in 2023. The vehicle types involved saw a continued trend of more Sport Utility Vehicles (2,109 in 2024 vs. 1,953 in 2023) and fewer Passenger Cars (3,586 vs. 3,738).

Top Vehicle Makes (7,409 vehicles)

1
CHEVROLET905 (12.2%)
-2.8%prior 931
2
FORD880 (11.9%)
2.1%prior 862
3
HONDA633 (8.5%)
-2.2%prior 647
4
OTHER/UNKNOWN624 (8.4%)
-2.5%prior 640
5
TOYOTA533 (7.2%)
-6.0%prior 567
6
KIA401 (5.4%)
7.8%prior 372
7
JEEP359 (4.8%)
7.2%prior 335
8
NISSAN357 (4.8%)
14.8%prior 311
9
HYUNDAI337 (4.5%)
5.3%prior 320
10
SUBARU281 (3.8%)
33.8%prior 210

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

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

Sex Distribution (9,168 persons with recorded sex)

Male4,931 (53.8%)
0.5%prior 4,905
Female4,237 (46.2%)
0.3%prior 4,225

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: ohio, OH
  • Total crash records analyzed: 4,046
  • Total persons involved: 9,403
  • Total vehicles involved: 7,409

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 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/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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Lake County, OH Crash Report — 2024 | ThatCarHitMe.com