Yearly Traffic Safety Analysis

1,041 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Darke County recorded 1,041 total crashes, a slight decrease of 0.9% from the 1,050 crashes reported in 2022. While overall crash numbers remained relatively stable, the number of hit-and-run incidents saw a significant year-over-year decline, falling from 122 in 2022 to 82 in 2023. Fatalities also decreased, with 10 deaths recorded in 2023 compared to 14 in the prior year.

1,041

▼ -0.9%was 1,050

Total Crash Events

10

▼ -28.6%was 14

Persons Killed

334

▼ -1.8%was 340

Persons Injured

82

▼ -32.8%was 122

Hit-and-Run Crashes

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Darke County showed a slight decline in 2023 compared to the previous year. Total crashes decreased by approximately 0.9%, from 1,050 in 2022 to 1,041 in 2023. This downward trend was also reflected in crash outcomes, with total fatalities decreasing from 14 to 10 and total injuries falling from 340 to 334.

82

Hit-and-Run Crashes — 2023

▼ -32.8% vs prior (122)

There was a notable downward trend in hit-and-run incidents in 2023 compared to the previous year. The total number of hit-and-run crashes decreased from 122 in 2022 to 82 in 2023. Consequently, the hit-and-run rate, which measures the percentage of all crashes that are hit-and-runs, fell from 11.6% to 7.9%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

10

Motorists Killed

Prior: 13↓-23.1%

5

Pedestrians Injured

Prior: 8↓-37.5%

329

Motorists Injured

Prior: 332↓-0.9%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between 2022 and 2023. In 2023, the peak day for crashes was Thursday with 178 incidents, a change from Tuesday (163 crashes) in the prior year. The busiest hour for crashes also shifted earlier in the day, moving from 6 p.m. in 2022 (77 crashes) to 3 p.m. in 2023 (89 crashes).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes showed a positive trend, with a decrease in the most severe incidents. The number of fatal crashes fell from 11 in 2022 to 9 in 2023, and the fatal crash rate per 100 crashes declined from 1.05 to 0.86. The proportion of crashes resulting in serious injury increased slightly from 3.5% to 3.9%, while the share of no-injury crashes rose from 75.9% to 78.0%.

Severity is per crash event (most severe injury). 9 fatal crash events resulted in 10 persons killed.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.9%
↓-18.2%prior 11
Serious Injury41serious injury crashes3.9%
↑10.8%prior 37
Minor Injury124minor injury crashes11.9%
↑1.6%prior 122
Possible Injury55possible injury crashes5.3%
↓-33.7%prior 83
No Injury812no injury crashes78%
↑1.9%prior 797

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The conditions under which crashes occurred remained broadly similar year-over-year, with most incidents happening in clear weather on dry roads. In 2023, crashes on dry roads constituted a larger share of the total, rising to 82.4% from 77.2% in 2022. Correspondingly, crashes on wet, snowy, or icy surfaces decreased, with a combined total of 197 such incidents in 2023 compared to 228 in the prior year.

Weather

Clear765 (73.5%)
↑5.7%prior 724
Cloudy143 (13.7%)
↓-15.4%prior 169
Rain77 (7.4%)
↑14.9%prior 67
Snow26 (2.5%)
↓-43.5%prior 46
Fog; Smog; Smoke11 (1.1%)
↓-35.3%prior 17
Other/Unknown10 (1.0%)
↓-16.7%prior 12
Sleet; Hail3 (0.3%)
Blowing Sand; Soil; Dirt; Snow2 (0.2%)
↓-83.3%prior 12
Severe Crosswinds2 (0.2%)
Freezing Rain or Freezing Drizzle2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight542 (52.1%)
↓-4.6%prior 568
Dark - Roadway Not Lighted354 (34.0%)
↑2.3%prior 346
Dawn/Dusk69 (6.6%)
↑4.5%prior 66
Dark - Lighted Roadway65 (6.2%)
↑10.2%prior 59
Other/Unknown9 (0.9%)
↓-10.0%prior 10
Dark - Unknown Roadway Lighting2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry858 (82.4%)
↑5.8%prior 811
Wet133 (12.8%)
↓-11.9%prior 151
Snow22 (2.1%)
↓-37.1%prior 35
Ice21 (2.0%)
↓-50.0%prior 42
Other/Unknown5 (0.5%)
↓-44.4%prior 9
Sand; Mud; Dirt; Oil; Gravel2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes were consistent between the two periods, with passenger cars, SUVs, and pickups being the most common. The top five vehicle makes remained Chevrolet, Ford, Dodge, Honda, and GMC, though Dodge (105 vehicles) surpassed Honda (103 vehicles) in 2023. An analysis of persons involved shows a shift in age demographics, with an increase in individuals aged 16-20 (from 203 to 240) and 65+ (from 243 to 272).

Top Vehicle Makes (1,568 vehicles)

1
CHEVROLET327 (20.9%)
↓-1.2%prior 331
2
FORD228 (14.5%)
↓-3.8%prior 237
3
DODGE105 (6.7%)
↑59.1%prior 66
4
HONDA103 (6.6%)
↓-5.5%prior 109
5
GMC81 (5.2%)
↑26.6%prior 64
6
TOYOTA72 (4.6%)
↑16.1%prior 62
7
JEEP45 (2.9%)
↓-13.5%prior 52
8
NISSAN45 (2.9%)
↓-4.3%prior 47
9
BUICK43 (2.7%)
↓-21.8%prior 55
10
CHRYSLER42 (2.7%)
↓-25.0%prior 56

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (1,713 persons with recorded sex)

Male1,003 (58.6%)
↑1.9%prior 984
Female710 (41.4%)
↓-3.9%prior 739

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,041
  • Total persons involved: 1,780
  • Total vehicles involved: 1,568

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: 2023." Published July 6, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2023-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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Darke County, OH Crash Report — 2023 | ThatCarHitMe.com