Yearly Traffic Safety Analysis

3,303 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Richland County recorded 3,303 vehicle crashes, a 7.8% decrease from the 3,584 crashes reported in 2022. Despite the overall decline in collisions and a 10% drop in total injuries to 1,112, the number of fatalities remained unchanged at 17 for both years. This stability in fatalities, coupled with fewer overall crashes, resulted in an increase in the fatal crash rate from 0.42% in 2022 to 0.51% in 2023.

3,303

-7.8%was 3,584

Total Crash Events

17

Persons Killed

1,112

-10.0%was 1,235

Persons Injured

440

-12.7%was 504

Hit-and-Run Crashes

Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) 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

Overall traffic crash trends in Richland County showed a notable decrease year-over-year. Total crashes fell by 7.8% from 3,584 in 2022 to 3,303 in 2023, and total injuries declined by nearly 10% from 1,235 to 1,112. However, the number of fatalities held steady at 17 across both periods, indicating that while crash frequency decreased, the outcomes of the most severe incidents did not follow the same downward trend.

440

Hit-and-Run Crashes — 2023

-12.7% vs prior (504)

Incidents of hit-and-run crashes saw a decrease in both count and rate from 2022 to 2023. The total number of hit-and-run crashes fell from 504 in 2022 to 440 in 2023. Correspondingly, the hit-and-run rate as a percentage of all crashes declined from 14.1% to 13.3%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

16

Motorists Killed

Prior: 160.0%

19

Pedestrians Injured

Prior: 1526.7%

1,093

Motorists Injured

Prior: 1,220-10.4%

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 temporal patterns of crashes in Richland County remained consistent year-over-year. Friday continued to be the peak day for crashes in 2023 with 593 incidents, closely mirroring the 613 crashes on Fridays in 2022. The evening commute hour of 5 p.m. also remained the peak time for collisions in both periods, accounting for 278 crashes in 2023 and 259 in 2022.

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

While total crashes decreased, the fatal crash rate increased from 0.42% in 2022 to 0.51% in 2023, with 17 fatal crashes in 2023 compared to 15 in the prior year. The proportion of crashes resulting in any injury remained stable at approximately 23.5% for both periods. However, the share of serious injury crashes saw a slight decline, dropping from 1.9% of all crashes in 2022 to 1.5% in 2023.

Outcome by Severity (Crash Events)

Fatal17fatal crashes0.5%
13.3%prior 15
Serious Injury50serious injury crashes1.5%
-27.5%prior 69
Minor Injury425minor injury crashes12.9%
-3.0%prior 438
Possible Injury297possible injury crashes9%
-12.6%prior 340
No Injury2,514no injury crashes76.1%
-7.6%prior 2,722

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 majority of crashes in both years occurred in clear weather and daylight on dry roads. In 2023, 74.4% of crashes happened on dry road surfaces, an increase from 70.2% in 2022. There was a significant year-over-year reduction in crashes occurring on snow or ice, which fell from a combined 388 incidents in 2022 to 149 in 2023. The proportion of crashes in daylight remained stable at around 62% for both periods.

Weather

Clear1,999 (60.5%)
-3.4%prior 2,070
Cloudy676 (20.5%)
-15.7%prior 802
Rain405 (12.3%)
22.4%prior 331
Snow180 (5.4%)
-41.0%prior 305
Fog; Smog; Smoke19 (0.6%)
-20.8%prior 24
Other/Unknown9 (0.3%)
-25.0%prior 12
Sleet; Hail8 (0.2%)
-27.3%prior 11
Severe Crosswinds5 (0.2%)
Blowing Sand; Soil; Dirt; Snow1 (0.0%)
-90.0%prior 10
Freezing Rain or Freezing Drizzle1 (0.0%)
-94.1%prior 17

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

Lighting

Daylight2,045 (61.9%)
-8.3%prior 2,231
Dark - Roadway Not Lighted692 (21.0%)
-3.9%prior 720
Dark - Lighted Roadway357 (10.8%)
-17.9%prior 435
Dawn/Dusk193 (5.8%)
10.9%prior 174
Dark - Unknown Roadway Lighting9 (0.3%)
0.0%prior 9
Other/Unknown7 (0.2%)
-53.3%prior 15

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

Road Surface

Dry2,458 (74.4%)
-2.3%prior 2,517
Wet686 (20.8%)
6.2%prior 646
Snow101 (3.1%)
-64.6%prior 285
Ice48 (1.5%)
-53.4%prior 103
Other/Unknown8 (0.2%)
-33.3%prior 12
Slush1 (0.0%)
-94.1%prior 17
Water (Standing; Moving)1 (0.0%)

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 remained consistent, with passenger cars and SUVs being the most common in both 2023 and 2022. The top five vehicle makes were identical across both years (Chevrolet, Ford, Honda, Dodge, Toyota), though all saw a decrease in total crash involvement in 2023. Analysis of persons involved shows the 26-34 age group had the highest representation in both periods, though their count decreased from 1,102 to 1,013.

Top Vehicle Makes (5,356 vehicles)

1
CHEVROLET989 (18.5%)
-8.8%prior 1,084
2
FORD745 (13.9%)
-12.0%prior 847
3
HONDA386 (7.2%)
0.5%prior 384
4
DODGE342 (6.4%)
-4.5%prior 358
5
TOYOTA312 (5.8%)
-20.0%prior 390
6
JEEP266 (5%)
-1.5%prior 270
7
KIA221 (4.1%)
11.1%prior 199
8
NISSAN187 (3.5%)
-20.4%prior 235
9
HYUNDAI184 (3.4%)
10.2%prior 167
10
GMC173 (3.2%)
-17.6%prior 210

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

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

Sex Distribution (6,688 persons with recorded sex)

Male3,597 (53.8%)
-6.9%prior 3,865
Female3,091 (46.2%)
-1.4%prior 3,136

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 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 3,303
  • Total persons involved: 6,993
  • Total vehicles involved: 5,356

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 5, 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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Richland County, OH Crash Report — 2023 | ThatCarHitMe.com