Yearly Traffic Safety Analysis

999 CRASHES IN
OHIO, OH
2021

In 2021, Clinton County recorded 999 traffic crashes, resulting in 9 fatalities and 314 injuries. A notable characteristic of these incidents is that a majority, 54.9%, did not involve a collision between two moving vehicles, frequently indicating single-vehicle events such as running off the road.

999

Total Crash Events

9

Persons Killed

314

Persons Injured

8.0%

Hit-and-Run Rate

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

80

Hit-and-Run Crashes — 2021

A total of 80 crashes, representing 8.0% of all incidents in Clinton County for the year, were classified as hit-and-run events. This classification is based on the initial determination made by the responding law enforcement officer at the scene.

Vulnerable Road User Casualties

Motorists comprised the entirety of the 9 traffic fatalities recorded in 2021. Additionally, 313 of the 314 total injuries were sustained by motorists. One pedestrian was injured in a crash during this period, while no cyclists were reported as killed or injured.

0

Pedestrians Killed

9

Motorists Killed

1

Pedestrians Injured

313

Motorists Injured

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash occurrences in Clinton County peaked on Wednesdays, with 157 incidents recorded. The most frequent time for crashes was the 4 p.m. hour, which saw 70 events. While a majority of crashes (59.8%) occurred during daylight hours, a substantial number, 327 incidents, happened in dark conditions.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 75.8% or 757 incidents, resulted in no injuries. Injury-related crashes accounted for 23.3% of the total, while 9 crashes (0.9%) were fatal. These 9 fatal crashes led to the deaths of 9 individuals.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.9%
Serious Injury28serious injury crashes2.8%
Minor Injury139minor injury crashes13.9%
Possible Injury66possible injury crashes6.6%
No Injury757no injury crashes75.8%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Road & Environmental Conditions

A significant majority of crashes happened in favorable conditions, with 65.1% occurring in clear weather and 78.3% on dry road surfaces. Correspondingly, 59.8% of incidents took place during daylight hours. Adverse conditions were also a factor, with 108 crashes occurring during rain and 177 on wet roads.

Weather

Clear650 (65.1%)
Cloudy206 (20.6%)
Rain108 (10.8%)
Snow25 (2.5%)
Fog; Smog; Smoke8 (0.8%)
Other/Unknown1 (0.1%)
Sleet; Hail1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight597 (59.8%)
Dark - Roadway Not Lighted261 (26.1%)
Dawn/Dusk74 (7.4%)
Dark - Lighted Roadway62 (6.2%)
Dark - Unknown Roadway Lighting4 (0.4%)
Other/Unknown1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry782 (78.3%)
Wet177 (17.7%)
Snow29 (2.9%)
Ice8 (0.8%)
Other/Unknown2 (0.2%)
Slush1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Among the 2,023 people involved in crashes, the 26-34 age group was the most represented, accounting for 311 individuals, followed by the 16-20 age group with 289 individuals. Of the 1,544 vehicles involved, the most frequent makes were Chevrolet (298), Ford (250), and a tie between Toyota and Honda (106 each).

Top Vehicle Makes (1,544 vehicles)

1
CHEVROLET298 (19.3%)
2
FORD250 (16.2%)
3
TOYOTA106 (6.9%)
4
HONDA106 (6.9%)
5
DODGE104 (6.7%)
6
JEEP64 (4.1%)
7
KIA62 (4%)
8
NISSAN60 (3.9%)
9
GMC49 (3.2%)
10
HYUNDAI49 (3.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (1,949 persons with recorded sex)

Male1,111 (57.0%)
Female838 (43.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Crash Location (First Harmful Event)

The first harmful event in 754 crashes, or 75.5% of the total, occurred on the roadway itself. A significant portion of incidents, 224 crashes (22.4%), were run-off-road events, with the first harmful event taking place on the roadside, shoulder, or in the median.

Crash Location (First Harmful Event)

"Other" combines 2 smaller categories (2 records): Driveway/Alley access (1), Crossover (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Traffic Control Device

Analysis of the 1,544 vehicles in crashes shows that a majority, 1,108 vehicles, were involved in incidents at locations with no traffic control devices present. For comparison, 282 vehicles were in crashes at locations with a traffic signal, and 142 were at locations controlled by a stop sign.

Traffic Control Device

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Driver Contributing Factor

Among driver-related actions contributing to crashes, the most common was 'Drove off Road,' cited for 167 vehicles. This was followed by 'Following too Close / ACDA' (Assured Clear Distance Ahead) for 145 vehicles and 'Failure to Yield' for 113 vehicles. 'Unsafe Speed' was a factor for another 67 vehicles.

Driver Contributing Factor

1
Drove off Road167 (21%)
2
Following too Close / ACDA145 (18.3%)
3
Failure to Yield113 (14.2%)
4
Unsafe Speed67 (8.4%)
5
Improper Lane Change45 (5.7%)
6
Ran Red Light36 (4.5%)
7
Other Improper Action33 (4.2%)
8
Not Discernible30 (3.8%)
9
Improper Turn30 (3.8%)

Showing top 9 of 19 reported. 10 additional (128 total) not shown: Swerving to Avoid, Left of Center, Improper Backing, Ran Stop Sign, Operating Defective Equipment, Improper Passing, Load shifting/Falling/Spilling, Improper Start From a Parked Position, Vision Obstruction, Wrong Way.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Commercial / Truck Involvement

Commercial trucks were involved in 94 crashes, representing 9.4% of all incidents in the county. Of these, 74 crashes involved a semi-tractor trailer, while the remaining 20 involved other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

A total of 17 crashes involved motorcyclists or vulnerable road users. These included 13 crashes with motorcyclists, 2 with bicyclists, and 2 with pedestrians. Combined, the 4 crashes involving pedestrians and bicyclists represent a key area of focus for traffic safety.

Animal-Involved Crashes

Crashes involving animals accounted for 195 incidents, or 19.5% of the total for the year. The vast majority of these, 182 crashes, were strikes involving deer, while 13 crashes involved other types of animals.

Impairment (Alcohol / Drugs)

A total of 64 crashes, or 6.4% of all incidents, were recorded as involving an impaired driver. Among the 64 drivers identified as impaired, 34 were under the influence of alcohol, 22 were under the influence of drugs, and 8 were noted to have used both alcohol and drugs.

Driver Condition

Beyond normal driving conditions, several specific driver states were noted among the 1,483 drivers involved in crashes. A total of 58 drivers were identified as being under the influence of medications, drugs, or alcohol. Additionally, 20 drivers were reported to have fallen asleep, fainted, or been fatigued, while illness was cited for 9 drivers.

Driver Condition

1
Apparently Normal1,305 (88.5%)
2
Other/Unknown77 (5.2%)
3
Under the Influence of Medications / Drugs / Alcohol58 (3.9%)
4
Fell Asleep; Fainted; Fatigued; etc.20 (1.4%)
5
Illness9 (0.6%)
6
Physical Impairment3 (0.2%)
7
Emotional (E.G.; Depressed; Angry; Disturbed)2 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Driver Distraction

Among the 1,483 drivers involved in crashes, specific distractions were identified for a subset. The most cited distraction was an 'other distraction inside the vehicle' for 34 drivers, followed by an 'other distraction outside the vehicle' for 15 drivers. Manually operating an electronic communication device was noted for 9 drivers.

Driver Distraction

1
Not Distracted1,296 (88.9%)
2
Other/Unknown89 (6.1%)
3
Other distraction inside the vehicle34 (2.3%)
4
Other distraction outside the vehicle15 (1%)
5
Manually operating an electronic communication device (texting; typing; dialing)9 (0.6%)
6
Other activity with an electronic device5 (0.3%)
7
Passenger5 (0.3%)
8
Talking on hands-free communication device3 (0.2%)
9
Talking on hand-held communication device1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Road Alignment

The majority of crashes (73.9%) occurred on straight, level sections of road. However, road geometry played a role in a notable number of incidents, with 10.2% of crashes (102) happening on curves and 19.6% (196) occurring on grades.

Road Alignment

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Top Cities

The geographic distribution of crashes was concentrated in a few key areas, with the city of Wilmington accounting for 250 incidents, or 25.0% of the county's total. The next highest volumes were seen in Union with 146 crashes, Chester with 102 crashes, and Liberty with 81 crashes.

Top Cities

1
Wilmington250 (25%)
2
Union146 (14.6%)
3
Chester102 (10.2%)
4
Liberty81 (8.1%)
5
Washington48 (4.8%)
6
Vernon47 (4.7%)
7
Green46 (4.6%)
8
Blanchester46 (4.6%)
9
Adams39 (3.9%)

Showing top 9 of 21 reported. 12 additional (194 total) not shown: Marion, Richland, Clark, Jefferson, Wilson, Wayne, Sabina, New Vienna, Clarksville, Midland, Martinsville, Port William.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Pre-Crash Driver Action

Of the 1,544 vehicles involved in crashes, the most common pre-crash action was 'Straight Ahead,' reported for 955 vehicles. The next most frequent actions were 'Slowing or Stopped In Traffic' for 163 vehicles and 'Making Left Turn' for 120 vehicles.

Pre-Crash Driver Action

1
Straight Ahead955 (61.9%)
2
Slowing or Stopped In Traffic163 (10.6%)
3
Making Left Turn120 (7.8%)
4
Negotiating a Curve82 (5.3%)
5
Parked56 (3.6%)
6
Making Right Turn46 (3%)
7
Changing Lanes35 (2.3%)
8
Backing30 (1.9%)
9
Entering Traffic Lane19 (1.2%)

Showing top 9 of 15 reported. 6 additional (38 total) not shown: Overtaking/Passing, Other/Unknown, Leaving Traffic Lane, Making U-Turn, Entering or Crossing Specified Location, Driverless.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Manner of Collision

The most common type of crash was 'Not Collision Between Two Vehicles in Transport,' which accounted for 548 incidents or 54.9% of the total. Among crashes involving multiple vehicles, angle collisions were the most frequent type, with 189 incidents (18.9%), followed by rear-end collisions with 136 incidents (13.6%).

Manner of Collision

"Other" combines 2 smaller categories (12 records): Other/Unknown (8), Rear-to-rear (4).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 738 of the 1,544 vehicles (47.8%). Sport Utility Vehicles (318) and Pick-up trucks (249) were the next most frequent. Commercial vehicles, including semi-tractors, single-unit trucks, and buses, were involved in 8.5% of incidents.

Vehicle Type

"Other" combines 11 smaller categories (56 records): Cargo Van (19), Motorcycle 2 Wheeled (13), Van (9-15 Seats) (8), Farm Equipment (4), Bus (16+ Passengers) (3), Bicycle (2), Heavy Equipment (2), Motorhome (2), Pedestrian/Skater (1), Other Vehicle (1), Wheelchair (Any type) (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Person Type

Among the 2,023 individuals involved in traffic incidents, 1,483 (73.3%) were drivers. Passengers, or occupants, accounted for another 538 individuals (26.6%). A small fraction, 2 individuals (0.1%), were pedestrians.

Person Type

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Person Injury Severity

Of the 2,023 people involved in crashes, 1,691 (83.6%) sustained no injuries. A total of 314 individuals were injured, representing 15.5% of all persons involved. Fatal injuries were recorded for 9 individuals, accounting for 0.4% of the total.

Person Injury Severity

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Occupant Safety Equipment

Among vehicle occupants, 1,719 individuals were reported as using a shoulder and lap belt. However, 113 individuals were recorded as using no safety equipment at all. An additional 74 children were secured in a child restraint system, including forward-facing, rear-facing, and booster seats.

Occupant Safety Equipment

"Other" combines 3 smaller categories (10 records): Helmet Used (6), Shoulder Belt Only Used (3), Lighting - Pedestrian / Bicycle Only (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Crashes were nearly evenly split between single-vehicle and two-vehicle incidents. Single-vehicle crashes accounted for 491 events (49.2% of the total), while 478 crashes (47.8%) involved two vehicles. Crashes involving three or more vehicles were less common, making up 3.0% of all incidents.

Vehicles Per Crash

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

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: 2021-01-01 through 2021-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 999
  • Total persons involved: 2,023
  • Total vehicles involved: 1,544

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: 2021." Published July 6, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2021-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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Clinton County, OH Crash Report — 2021 | ThatCarHitMe.com