Yearly Traffic Safety Analysis

2,059 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Erie County recorded 2,059 total vehicle crashes, a 14.1% decrease from the 2,398 crashes documented in 2021. This overall reduction in collisions was accompanied by declines in fatalities and injuries. The most significant year-over-year change was a 48.8% drop in crashes involving a driver under the influence (DUI), which fell from 160 incidents in 2021 to 82 in 2022.

2,059

-14.1%was 2,398

Total Crash Events

9

-18.2%was 11

Persons Killed

745

-8.3%was 812

Persons Injured

248

-27.3%was 341

Hit-and-Run Crashes

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety metrics in Erie County improved in 2022 compared to 2021. Total crashes decreased by 14.1% from 2,398 to 2,059. Similarly, the number of persons injured fell by 8.3% from 812 to 745, and total fatalities decreased by 18.2% from 11 to 9.

248

Hit-and-Run Crashes — 2022

-27.3% vs prior (341)

Hit-and-run crashes decreased significantly in 2022 compared to the prior year. The total count of hit-and-run incidents fell from 341 in 2021 to 248 in 2022, representing a 27.3% reduction. The hit-and-run rate, which is the percentage of all crashes classified as a hit-and-run, also declined from 14.2% to 12.0%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

9

Motorists Killed

Prior: 10-10.0%

10

Pedestrians Injured

Prior: 12-16.7%

735

Motorists Injured

Prior: 800-8.1%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes showed a consistent pattern between the two periods, though at a lower volume in 2022. Friday remained the peak day for crashes in both years, with 325 incidents in 2022 compared to 402 in 2021. The 3 p.m. hour was also the peak time for collisions in both periods, accounting for 137 crashes in 2022 and 180 in the prior year.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes lessened in 2022 compared to the previous year. The number of fatal crashes decreased from 9 in 2021 to 5 in 2022, with their share of total crashes falling from 0.4% to 0.2%. The proportion of crashes involving a serious injury also declined from 2.9% to 2.0%. Consequently, the percentage of crashes resulting in no injury increased from 76.6% in 2021 to 78.1% in 2022.

Severity is per crash event (most severe injury). 5 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.2%
-44.4%prior 9
Serious Injury41serious injury crashes2%
-41.4%prior 70
Minor Injury247minor injury crashes12%
-20.6%prior 311
Possible Injury157possible injury crashes7.6%
-8.7%prior 172
No Injury1,609no injury crashes78.1%
-12.4%prior 1,836

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

While the majority of crashes in both years occurred in clear weather and on dry roads, there was a slight shift toward a higher proportion of incidents in adverse conditions in 2022. The share of crashes in adverse weather (rain, snow, etc.) increased from 14.0% in 2021 to 17.4% in 2022, with snow-related crashes rising from 109 to 145. Correspondingly, the proportion of crashes on non-dry road surfaces grew from 21.1% to 24.9%. Lighting conditions for crashes remained stable year-over-year.

Weather

Clear1,286 (62.5%)
-14.8%prior 1,510
Cloudy378 (18.4%)
-27.7%prior 523
Rain153 (7.4%)
-27.1%prior 210
Snow145 (7.0%)
33.0%prior 109
Other/Unknown23 (1.1%)
-20.7%prior 29
Blowing Sand; Soil; Dirt; Snow21 (1.0%)
Fog; Smog; Smoke20 (1.0%)
122.2%prior 9
Sleet; Hail15 (0.7%)
Severe Crosswinds13 (0.6%)
Freezing Rain or Freezing Drizzle5 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight1,259 (61.1%)
-12.4%prior 1,438
Dark - Roadway Not Lighted405 (19.7%)
-12.3%prior 462
Dark - Lighted Roadway239 (11.6%)
-25.3%prior 320
Dawn/Dusk117 (5.7%)
-14.6%prior 137
Other/Unknown31 (1.5%)
-11.4%prior 35
Dark - Unknown Roadway Lighting8 (0.4%)
33.3%prior 6

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry1,529 (74.3%)
-18.5%prior 1,876
Wet280 (13.6%)
-18.4%prior 343
Snow155 (7.5%)
63.2%prior 95
Ice61 (3.0%)
0.0%prior 61
Other/Unknown17 (0.8%)
0.0%prior 17
Slush15 (0.7%)
Water (Standing; Moving)2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The primary vehicle types and makes involved in crashes remained consistent year-over-year, with passenger cars, SUVs, and pickups being the most frequent. Ford and Chevrolet were the top two makes involved in collisions in both 2021 and 2022, with their numbers declining in line with the overall trend. An analysis of persons involved in crashes shows a demographic shift, with the 0-15 age group's representation increasing from 8.4% of all persons in 2021 to 10.9% in 2022.

Top Vehicle Makes (3,459 vehicles)

1
FORD620 (17.9%)
-28.7%prior 870
2
CHEVROLET567 (16.4%)
-18.5%prior 696
3
HONDA217 (6.3%)
-13.2%prior 250
4
DODGE190 (5.5%)
-10.0%prior 211
5
TOYOTA174 (5%)
3.0%prior 169
6
JEEP171 (4.9%)
-0.6%prior 172
7
KIA152 (4.4%)
-2.6%prior 156
8
GMC111 (3.2%)
8.8%prior 102
9
HYUNDAI101 (2.9%)
6.3%prior 95
10
NISSAN92 (2.7%)
3.4%prior 89

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (4,405 persons with recorded sex)

Male2,441 (55.4%)
-6.3%prior 2,606
Female1,964 (44.6%)
-8.5%prior 2,146

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 2,059
  • Total persons involved: 4,653
  • Total vehicles involved: 3,459

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: 2022." Published July 6, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2022-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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Erie County, OH Crash Report — 2022 | ThatCarHitMe.com