Yearly Traffic Safety Analysis

12,155 CRASHES IN
CLEVELAND, OH
2023

All metrics benchmarked against2022

In 2023, Cleveland experienced 12,155 crashes, a decrease from the 14,850 crashes reported in 2022. This represents an 18.15% reduction in total crashes year-over-year. Despite the overall decrease in crashes, total fatalities saw a significant increase of 22.73%, rising from 44 in 2022 to 54 in 2023.

12,155

▼ -18.1%was 14,850

Total Crash Events

54

▲ 22.7%was 44

Persons Killed

6,270

▼ -11.3%was 7,065

Persons Injured

4,137

▼ -18.2%was 5,058

Hit-and-Run Crashes

Note: "Persons Killed" (54) counts individual fatalities across all crash events. "Fatal" in the severity table below (53) 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, crash incidents in Cleveland showed a downward trend from 2022 to 2023, with total crashes decreasing by 18.15% and total injuries decreasing by 11.25%. However, this decline in crash volume was accompanied by an increase in total fatalities, which rose by 22.73%.

4,137

Hit-and-Run Crashes — 2023

▼ -18.2% vs prior (5,058)

The number of hit-and-run crashes decreased from 5,058 in 2022 to 4,137 in 2023, representing an 18.21% reduction. Despite this decrease in raw count, the hit-and-run crash rate remained largely stable, shifting only slightly from 34.1% of total crashes in 2022 to 34% in 2023.

Vulnerable Road User Casualties

10

Pedestrians Killed

Prior: 10→0.0%

44

Motorists Killed

Prior: 34↑29.4%

189

Pedestrians Injured

Prior: 209↓-9.6%

6,081

Motorists Injured

Prior: 6,856↓-11.3%

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 remained consistent year-over-year, with Friday continuing to be the peak day for crashes and 4 p.m. remaining the peak hour. While crashes decreased across all days of the week, Friday experienced the largest reduction in raw crash count, falling from 2,526 in 2022 to 1,878 in 2023.

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

The overall severity distribution of crashes shifted in 2023 compared to 2022, with a higher proportion of crashes resulting in injury or fatality. The percentage of fatal crashes increased from 0.3% to 0.4% of all crashes. Similarly, crashes resulting in serious, minor, or possible injuries each saw slight increases in their respective proportions of total crashes.

Severity is per crash event (most severe injury). 53 fatal crash events resulted in 54 persons killed.

Outcome by Severity (Crash Events)

Fatal53fatal crashes0.4%
↑23.3%prior 43
Serious Injury302serious injury crashes2.5%
↓-11.2%prior 340
Minor Injury1,225minor injury crashes10.1%
↓-12.3%prior 1,397
Possible Injury2,387possible injury crashes19.6%
↓-16.2%prior 2,847
No Injury8,188no injury crashes67.4%
↓-19.9%prior 10,223

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

Crash conditions saw shifts in 2023, particularly regarding weather and road surface. The proportion of crashes occurring in 'Clear' weather increased from 59.00% to 61.78%, while crashes in 'Snow' conditions decreased from 6.27% to 3.84%. Correspondingly, crashes on 'Dry' road surfaces rose from 70.93% to 74.55%, and those on 'Snow' or 'Ice' surfaces saw their proportions decrease significantly.

Weather

Clear7,509 (61.8%)
↓-14.3%prior 8,757
Cloudy2,345 (19.3%)
↓-27.8%prior 3,246
Rain1,310 (10.8%)
↑4.7%prior 1,251
Snow467 (3.8%)
↓-49.8%prior 931
Other/Unknown423 (3.5%)
↓-14.0%prior 492
Freezing Rain or Freezing Drizzle37 (0.3%)
↓-30.2%prior 53
Fog; Smog; Smoke33 (0.3%)
↑17.9%prior 28
Sleet; Hail24 (0.2%)
↓-64.2%prior 67
Blowing Sand; Soil; Dirt; Snow4 (0.0%)
↓-75.0%prior 16
Severe Crosswinds3 (0.0%)
↓-66.7%prior 9

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

Lighting

Daylight7,721 (63.5%)
↓-17.2%prior 9,322
Dark - Lighted Roadway3,278 (27.0%)
↓-21.7%prior 4,188
Dawn/Dusk659 (5.4%)
↓-14.9%prior 774
Other/Unknown262 (2.2%)
↓-11.8%prior 297
Dark - Unknown Roadway Lighting120 (1.0%)
↓-13.7%prior 139
Dark - Roadway Not Lighted115 (0.9%)
↓-11.5%prior 130

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

Road Surface

Dry9,061 (74.5%)
↓-14.0%prior 10,533
Wet2,240 (18.4%)
↓-13.1%prior 2,579
Snow365 (3.0%)
↓-62.0%prior 961
Other/Unknown340 (2.8%)
↓-8.8%prior 373
Ice123 (1.0%)
↓-62.7%prior 330
Slush13 (0.1%)
↓-75.9%prior 54
Water (Standing; Moving)13 (0.1%)
↓-13.3%prior 15

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 18.21% from 28,818 in 2022 to 23,571 in 2023. The top four vehicle makes involved in crashes remained Chevrolet, Ford, Toyota, and Honda in both years, though Nissan replaced Kia in the top five. All top vehicle makes saw a reduction in their involvement counts, aligning with the overall decrease in crash incidents.

Top Vehicle Makes (23,571 vehicles)

1
CHEVROLET2,686 (11.4%)
↓-21.0%prior 3,399
2
FORD2,639 (11.2%)
↓-21.0%prior 3,339
3
TOYOTA1,654 (7%)
↓-19.2%prior 2,047
4
HONDA1,626 (6.9%)
↓-19.7%prior 2,026
5
NISSAN1,238 (5.3%)
↓-16.2%prior 1,477
6
KIA1,178 (5%)
↓-22.3%prior 1,516
7
JEEP989 (4.2%)
↓-18.9%prior 1,219
8
HYUNDAI948 (4%)
↓-23.5%prior 1,239
9
DODGE916 (3.9%)
↓-25.0%prior 1,221
10
OTHER/UNKNOWN512 (2.2%)
↑77.8%prior 288

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

5,061 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (24,267 persons with recorded sex)

Male13,363 (55.1%)
↓-16.0%prior 15,902
Female10,904 (44.9%)
↓-17.6%prior 13,225

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: Cleveland, OH
  • Total crash records analyzed: 12,155
  • Total persons involved: 28,208
  • Total vehicles involved: 23,571

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). "Cleveland, 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/cleveland/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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Cleveland, OH Crash Report — 2023 | ThatCarHitMe.com