Yearly Traffic Safety Analysis

64 CRASHES IN
BURTON, OH
2022

All metrics benchmarked against2021

Total crashes remained stable at 64 in both 2022 and 2021. The most notable year-over-year shift was a 50% decrease in hit-and-run crashes, falling from 4 in 2021 to 2 in 2022. This period also saw a slight decrease in total injuries. Overall, the crash landscape remained largely consistent in terms of total incidents.

64

Total Crash Events

0

Persons Killed

22

-4.3%was 23

Persons Injured

2

-50.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 crash numbers remained stable year-over-year, with 64 crashes reported in both 2022 and 2021. Total fatalities remained at 0 in both periods. There was a slight decrease in total injuries, falling from 23 in 2021 to 22 in 2022, representing a 4.3% reduction.

2

Hit-and-Run Crashes — 2022

-50.0% vs prior (4)

Hit-and-run crashes decreased by 50% year-over-year, falling from 4 incidents in 2021 to 2 in 2022. Consequently, the hit-and-run rate decreased from 6.3% of all crashes in 2021 to 3.1% in 2022.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

22

Motorists Injured

Prior: 23-4.3%

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 peak day for crashes shifted from Tuesday in 2021 (16 crashes) to Monday in 2022 (16 crashes). The peak crash hour also changed, moving from 6 PM in 2021 (6 crashes) to 7 AM in 2022 (10 crashes). Monthly crash distribution saw November crashes decrease significantly from 14 in 2021 to 2 in 2022, while September crashes increased from 5 to 9 during the same period.

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

Fatal crashes remained at 0 in both 2022 and 2021. Serious injury crashes (severity A) were stable at 3 in both periods. Minor injury crashes (severity B) decreased from 13 (20.3% of total crashes) in 2021 to 7 (10.9%) in 2022, while no-injury crashes increased from 44 (68.8%) to 49 (76.6%).

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes4.7%
0.0%prior 3
Minor Injury7minor injury crashes10.9%
-46.2%prior 13
Possible Injury5possible injury crashes7.8%
25.0%prior 4
No Injury49no injury crashes76.6%
11.4%prior 44

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

Crashes occurring in clear weather increased from 31 in 2021 to 39 in 2022, while crashes in cloudy conditions decreased from 17 to 12. There was a notable shift in lighting conditions, with crashes occurring in "Dark - Roadway Not Lighted" decreasing from 24 in 2021 to 16 in 2022. Crashes on dry road surfaces increased from 37 to 46, corresponding with a decrease in crashes on wet surfaces from 19 to 12.

Weather

Clear39 (60.9%)
25.8%prior 31
Cloudy12 (18.8%)
-29.4%prior 17
Snow7 (10.9%)
-12.5%prior 8
Rain5 (7.8%)
-37.5%prior 8
Fog; Smog; Smoke1 (1.6%)

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

Lighting

Daylight38 (59.4%)
11.8%prior 34
Dark - Roadway Not Lighted16 (25.0%)
-33.3%prior 24
Dawn/Dusk7 (10.9%)
Dark - Lighted Roadway3 (4.7%)

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

Road Surface

Dry46 (71.9%)
24.3%prior 37
Wet12 (18.8%)
-36.8%prior 19
Snow6 (9.4%)
0.0%prior 6

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 91 in 2021 to 96 in 2022. Sport Utility Vehicles involved in crashes saw a significant increase from 22 in 2021 to 35 in 2022, while Passenger Cars decreased from 31 to 28. The representation of persons aged 0-15 involved in crashes increased from 6 in 2021 to 17 in 2022, and persons aged 55-64 decreased from 20 to 11.

Top Vehicle Makes (96 vehicles)

1
CHEVROLET19 (19.8%)
5.6%prior 18
2
TOYOTA13 (13.5%)
62.5%prior 8
3
FORD13 (13.5%)
-13.3%prior 15
4
HONDA10 (10.4%)
5
JEEP9 (9.4%)
12.5%prior 8
6
KIA6 (6.3%)
7
DODGE4 (4.2%)
-42.9%prior 7
8
GMC4 (4.2%)
9
NISSAN3 (3.1%)
10
FREIGHTLINER2 (2.1%)

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

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

Sex Distribution (129 persons with recorded sex)

Male69 (53.5%)
-2.8%prior 71
Female60 (46.5%)
53.8%prior 39

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 5, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: Burton, OH
  • Total crash records analyzed: 64
  • Total persons involved: 130
  • Total vehicles involved: 96

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). "Burton, OH Crash Intelligence Report: 2022." Published July 5, 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/burton/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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