Yearly Traffic Safety Analysis

1,854 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Ashtabula County recorded 1,854 total vehicle crashes, a 3.3% decrease from the 1,917 crashes documented in 2022. Despite the overall reduction in collisions, the number of fatalities rose from 14 to 19 year-over-year, representing a 35.7% increase.

1,854

-3.3%was 1,917

Total Crash Events

19

35.7%was 14

Persons Killed

682

0.4%was 679

Persons Injured

165

Hit-and-Run Crashes

Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) 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 collisions in Ashtabula County saw a modest decline in 2023, with 63 fewer crashes than in the prior year, a 3.3% decrease. However, this trend did not extend to crash outcomes, as total injuries remained stable at 682 compared to 679, and total fatalities increased by 35.7% from 14 to 19.

165

Hit-and-Run Crashes — 2023

0.0% vs prior (165)

The number of hit-and-run crashes in Ashtabula County remained unchanged, with 165 incidents reported in both 2023 and 2022. However, because the total number of crashes decreased in 2023, the hit-and-run rate saw a slight increase. These incidents accounted for 8.9% of all crashes in 2023, up from 8.6% in the previous year.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 1200.0%

16

Motorists Killed

Prior: 1323.1%

15

Pedestrians Injured

Prior: 887.5%

667

Motorists Injured

Prior: 671-0.6%

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 showed some shifts between the two periods. While the peak hour for collisions remained stable at 3 p.m. in both 2023 (146 crashes) and 2022 (149 crashes), the peak day shifted from Friday (316 crashes) in 2022 to Thursday (294 crashes) in 2023. Crashes on Fridays saw a notable decrease from 316 to 271 year-over-year.

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 severity of crashes worsened in 2023. The number of fatal crashes increased from 14 to 19, pushing the fatal crash rate up from 0.73% to 1.02%. The proportion of serious injury crashes decreased slightly from 3.7% to 3.4%, while minor injury crashes saw a small increase from 15.4% to 16.1% of all incidents. Crashes resulting in no injury made up a slightly smaller share of the total, at 72.4% in 2023 compared to 73.0% in 2022.

Outcome by Severity (Crash Events)

Fatal19fatal crashes1%
35.7%prior 14
Serious Injury63serious injury crashes3.4%
-11.3%prior 71
Minor Injury298minor injury crashes16.1%
0.7%prior 296
Possible Injury131possible injury crashes7.1%
-3.7%prior 136
No Injury1,343no injury crashes72.4%
-4.1%prior 1,400

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 proportion of crashes occurring on dry roads increased from 68.2% in 2022 to 71.2% in 2023. Correspondingly, crashes on snow-covered roads decreased significantly, accounting for 5.1% of incidents in 2023 compared to 9.7% in the prior year. Crashes in dark, unlighted conditions saw a proportional increase, rising from 24.0% of all crashes in 2022 to 26.7% in 2023. Collisions during clear weather decreased as a share of the total, while those in cloudy and rainy conditions increased.

Weather

Clear952 (51.3%)
-11.4%prior 1,074
Cloudy552 (29.8%)
14.3%prior 483
Rain201 (10.8%)
21.1%prior 166
Snow114 (6.1%)
-26.9%prior 156
Fog; Smog; Smoke17 (0.9%)
88.9%prior 9
Freezing Rain or Freezing Drizzle9 (0.5%)
28.6%prior 7
Sleet; Hail7 (0.4%)
-12.5%prior 8
Other/Unknown2 (0.1%)
-66.7%prior 6

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

Lighting

Daylight1,080 (58.3%)
-7.1%prior 1,163
Dark - Roadway Not Lighted495 (26.7%)
7.6%prior 460
Dark - Lighted Roadway166 (9.0%)
-9.3%prior 183
Dawn/Dusk104 (5.6%)
0.0%prior 104
Dark - Unknown Roadway Lighting6 (0.3%)
Other/Unknown3 (0.2%)

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

Road Surface

Dry1,320 (71.2%)
1.0%prior 1,307
Wet406 (21.9%)
16.3%prior 349
Snow94 (5.1%)
-49.2%prior 185
Ice16 (0.9%)
-69.8%prior 53
Slush13 (0.7%)
-18.8%prior 16
Sand; Mud; Dirt; Oil; Gravel3 (0.2%)
Other/Unknown2 (0.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent year-over-year, with Chevrolet (466), Ford (414), and Honda (229) being the top three in 2023, similar to the prior year. In terms of persons involved, the 16-20 age group saw its representation increase from 11.6% in 2022 to 12.8% in 2023. Conversely, the proportion of individuals in the 26-34 age group decreased from 14.8% to 13.5% over the same period.

Top Vehicle Makes (2,864 vehicles)

1
CHEVROLET466 (16.3%)
-2.1%prior 476
2
FORD414 (14.5%)
2.0%prior 406
3
HONDA229 (8%)
-10.5%prior 256
4
TOYOTA197 (6.9%)
-7.5%prior 213
5
JEEP148 (5.2%)
0.0%prior 148
6
DODGE148 (5.2%)
-13.5%prior 171
7
HYUNDAI114 (4%)
2.7%prior 111
8
GMC111 (3.9%)
4.7%prior 106
9
KIA111 (3.9%)
16.8%prior 95
10
NISSAN85 (3%)
-5.6%prior 90

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

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

Sex Distribution (3,869 persons with recorded sex)

Male2,143 (55.4%)
-3.7%prior 2,225
Female1,726 (44.6%)
4.7%prior 1,648

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: 1,854
  • Total persons involved: 3,989
  • Total vehicles involved: 2,864

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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Ashtabula County, OH Crash Report — 2023 | ThatCarHitMe.com