Yearly Traffic Safety Analysis

1,056 CRASHES IN
OHIO, OH
2021

In 2021, Darke County recorded 1,056 traffic crashes, resulting in 9 fatalities and 323 injuries. A significant portion of these incidents were single-vehicle crashes, which accounted for 50.2% of the total. Notably, collisions with animals, primarily deer, were a major factor, comprising 249 separate crashes.

1,056

Total Crash Events

9

Persons Killed

323

Persons Injured

10.8%

Hit-and-Run Rate

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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

114

Hit-and-Run Crashes — 2021

In 2021, 114 crashes in Darke County were classified as hit-and-run incidents, representing 10.8% of all crashes. This designation is based on the responding officer's initial report at the scene.

Vulnerable Road User Casualties

In 2021, all 9 traffic fatalities in Darke County were motorists, and an additional 315 motorists were injured. There were no cyclist fatalities or injuries recorded for the year. While no pedestrians were killed, 8 pedestrians sustained injuries in crashes.

0

Pedestrians Killed

9

Motorists Killed

8

Pedestrians Injured

315

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

Crashes in Darke County occurred most frequently on Fridays, with 182 incidents recorded. The single busiest hour for crashes was 7 p.m., which saw 85 crashes. A notable peak occurred during the late afternoon and early evening hours from 3 p.m. to 7 p.m., which collectively accounted for 380 crashes.

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 in Darke County, 77.5% (818 incidents), resulted in no injuries and were property-damage-only. Injury-related crashes accounted for the remaining 22.5% of incidents. There were 8 fatal crashes recorded, which resulted in a total of 9 fatalities.

Severity is per crash event (most severe injury). 8 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.8%
Serious Injury27serious injury crashes2.6%
Minor Injury102minor injury crashes9.7%
Possible Injury101possible injury crashes9.6%
No Injury818no injury crashes77.5%

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

The majority of crashes occurred in ideal driving conditions, with 66.2% happening in clear weather and 76.6% on a dry road surface. Over half of the crashes, 574 incidents, occurred during daylight hours. Crashes in adverse weather included 84 in rain and 38 in snow, while 331 crashes occurred on unlighted roads in the dark.

Weather

Clear699 (66.2%)
Cloudy201 (19.0%)
Rain84 (8.0%)
Snow38 (3.6%)
Other/Unknown17 (1.6%)
Fog; Smog; Smoke8 (0.8%)
Freezing Rain or Freezing Drizzle7 (0.7%)
Sleet; Hail1 (0.1%)
Blowing Sand; Soil; Dirt; Snow1 (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

Daylight574 (54.4%)
Dark - Roadway Not Lighted331 (31.3%)
Dark - Lighted Roadway77 (7.3%)
Dawn/Dusk57 (5.4%)
Other/Unknown15 (1.4%)
Dark - Unknown Roadway Lighting2 (0.2%)

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

Road Surface

Dry809 (76.6%)
Wet168 (15.9%)
Snow37 (3.5%)
Ice23 (2.2%)
Other/Unknown13 (1.2%)
Slush3 (0.3%)
Water (Standing; Moving)2 (0.2%)
Sand; Mud; Dirt; Oil; Gravel1 (0.1%)

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

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was most represented with 277 individuals, followed by the 65+ age group with 266 individuals. The most common vehicle makes involved in crashes were Chevrolet (345 vehicles), Ford (281 vehicles), and Dodge (101 vehicles).

Top Vehicle Makes (1,612 vehicles)

1
CHEVROLET345 (21.4%)
2
FORD281 (17.4%)
3
DODGE101 (6.3%)
4
HONDA88 (5.5%)
5
TOYOTA87 (5.4%)
6
GMC69 (4.3%)
7
BUICK64 (4%)
8
JEEP52 (3.2%)
9
CHRYSLER47 (2.9%)
10
HYUNDAI44 (2.7%)

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

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

Sex Distribution (1,763 persons with recorded sex)

Male1,014 (57.5%)
Female749 (42.5%)

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 the majority of crashes, 828 incidents, occurred on the roadway itself. However, a notable 213 crashes, or 20.2% of the total, were run-off-road events where the first harmful event happened on the roadside, shoulder, median, or outside the trafficway.

Crash Location (First Harmful Event)

"Other" combines 1 smaller categories (1 records): In Median (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 traffic controls present at crash locations shows that the majority of vehicles involved, 1,252 out of 1,612, were in areas with no traffic control device. In contrast, 211 vehicles were involved in crashes at intersections with stop signs and 118 at locations with traffic signals.

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

The most common contributing factor cited for drivers was "Drove off Road," which was noted for 221 vehicles. This was followed by "Failure to Yield" for 179 vehicles and "Following too Close / ACDA" for 138 vehicles. These three factors were associated with over a third of the vehicles for which a circumstance was determined.

Driver Contributing Factor

1
Drove off Road221 (27.5%)
2
Failure to Yield179 (22.2%)
3
Following too Close / ACDA138 (17.1%)
4
Other Improper Action56 (7%)
5
Left of Center38 (4.7%)
6
Improper Backing35 (4.3%)
7
Not Discernible19 (2.4%)
8
Improper Passing18 (2.2%)
9
Improper Lane Change18 (2.2%)

Showing top 9 of 23 reported. 14 additional (83 total) not shown: Improper Turn, Swerving to Avoid, Ran Red Light, Ran Stop Sign, Load shifting/Falling/Spilling, Improper Start From a Parked Position, Operating Defective Equipment, Wrong Way, Unsafe Speed, Opening Door into Roadway, Lying in Roadway, Stopped or Parked Illegally, Vision Obstruction, Improper Crossing.

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

Commercial / Truck Involvement

A total of 76 commercial trucks were involved in crashes in 2021. Of these, 52 were identified as semi-tractor trailers and 24 were classified as other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

Crashes in 2021 involved 32 vulnerable road users and motorcyclists. This included 21 motorcyclists, 8 pedestrians, and 3 bicyclists. These crashes are notable due to the higher risk of severe injury or fatality for the unprotected user.

Animal-Involved Crashes

Collisions with animals were a significant factor in Darke County crashes, accounting for 249 incidents, or 23.6% of the yearly total. The vast majority of these, 229 crashes, specifically involved deer. An additional 20 crashes were attributed to collisions with other types of animals.

Impairment (Alcohol / Drugs)

Impairment was a factor in 45 crashes, representing 4.3% of all incidents. Of these, alcohol was suspected in 29 crashes, drugs in 11 crashes, and a combination of both in 5 crashes. These figures represent a minimum, as impairment can be difficult to determine at the scene.

Driver Condition

While most drivers were recorded as "Apparently Normal," several adverse driver conditions were noted in a total of 54 cases. A total of 36 drivers were suspected to be under the influence of medications, drugs, or alcohol. An additional 10 drivers were reported as having fallen asleep, fainted, or being fatigued.

Driver Condition

1
Apparently Normal1,347 (91.9%)
2
Other/Unknown64 (4.4%)
3
Under the Influence of Medications / Drugs / Alcohol36 (2.5%)
4
Fell Asleep; Fainted; Fatigued; etc.10 (0.7%)
5
Physical Impairment4 (0.3%)
6
Illness2 (0.1%)
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 1,497 drivers involved in crashes, a specific distraction was identified for 72 of them. The most common issues were general distractions from outside the vehicle (27 drivers) and inside the vehicle (24 drivers). Electronic device use was cited as a distraction for a total of 12 drivers.

Driver Distraction

1
Not Distracted1,304 (90.4%)
2
Other/Unknown67 (4.6%)
3
Other distraction outside the vehicle27 (1.9%)
4
Other distraction inside the vehicle24 (1.7%)
5
Manually operating an electronic communication device (texting; typing; dialing)6 (0.4%)
6
Other activity with an electronic device6 (0.4%)
7
Passenger6 (0.4%)
8
Talking on hand-held communication device3 (0.2%)

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 vast majority of crashes, 960 out of 1,056, occurred on straight and level road segments. However, roadway geometry played a role in some incidents, with 62 crashes (5.9%) occurring on curves and 51 crashes (4.8%) taking place 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 distribution of crashes across Darke County shows a high concentration in Greenville, which accounted for 459 crashes, or 43.5% of the county's total. Other townships with notable crash volumes include Adams with 66 crashes, Van Buren with 60, and Neave with 45.

Top Cities

1
Greenville459 (43.5%)
2
Adams66 (6.3%)
3
Van Buren60 (5.7%)
4
Neave45 (4.3%)
5
Monroe35 (3.3%)
6
Butler33 (3.1%)
7
Harrison31 (2.9%)
8
Washington31 (2.9%)
9
Twin29 (2.7%)

Showing top 9 of 34 reported. 25 additional (267 total) not shown: Wayne, Brown, Liberty, Franklin, Versailles, York, Mississinawa, Jackson, Richland, Allen, Union City, Patterson, Wabash, New Madison, Hollansburg, Castine, Ansonia, Gettysburg, Bradford, Palestine, Yorkshire, Gordon, North Star, Osgood, Pitsburg.

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

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was driving straight ahead, which was the case for 1,029 of the 1,612 vehicles (63.8%). Other frequent actions preceding a collision included slowing or stopping in traffic (123 vehicles) and making a left turn (120 vehicles).

Pre-Crash Driver Action

1
Straight Ahead1,029 (63.8%)
2
Slowing or Stopped In Traffic123 (7.6%)
3
Making Left Turn120 (7.4%)
4
Parked84 (5.2%)
5
Making Right Turn45 (2.8%)
6
Backing42 (2.6%)
7
Negotiating a Curve39 (2.4%)
8
Entering Traffic Lane36 (2.2%)
9
Other/Unknown35 (2.2%)

Showing top 9 of 16 reported. 7 additional (59 total) not shown: Overtaking/Passing, Changing Lanes, Walking; Running; Jogging; Playing, Leaving Traffic Lane, Driverless, Other Non-Motorist, Making U-Turn.

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

Manner of Collision

Over half of all crashes in Darke County, 572 incidents or 54.2%, were not collisions between two moving vehicles, a category that primarily consists of single-vehicle crashes. Among multi-vehicle crashes, the most common types were angle collisions (194 crashes) and rear-end collisions (133 crashes).

Manner of Collision

"Other" combines 2 smaller categories (22 records): Head-on (21), Rear-to-rear (1).

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 628 of the 1,612 vehicles. Sport utility vehicles (396 vehicles) and pickup trucks (294 vehicles) were also frequently involved. Commercial vehicles, including semi-tractors, single-unit trucks, and buses, comprised 5.6% of the vehicles in crashes.

Vehicle Type

"Other" combines 12 smaller categories (77 records): Single Unit Truck (19), Cargo Van (12), Farm Equipment (9), Pedestrian/Skater (8), Other Vehicle (7), Van (9-15 Seats) (6), Heavy Equipment (4), Bus (16+ Passengers) (4), Bicycle (3), Snowmobile (2), All Terrain Vehicle (ATV/UTV) (2), Motorcycle 3 Wheeled (1).

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

Person Type

Of the 1,850 individuals involved in traffic crashes, the majority were drivers, accounting for 1,497 people or 80.9% of the total. Passengers (occupants) made up another 345 individuals (18.6%). A small fraction, 8 individuals, 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

Across all 1,850 people involved in crashes, 9 individuals sustained fatal injuries and 323 sustained some level of injury. This means that 17.9% of all persons involved were either killed or injured. The remaining 1,457 individuals were not injured.

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

Safety equipment usage was recorded for most motor vehicle occupants, with 1,499 individuals documented as using a shoulder and lap belt. However, 131 occupants used no safety equipment at all. This represents a notable portion of individuals who were unprotected in a crash.

Occupant Safety Equipment

"Other" combines 2 smaller categories (10 records): Lap Belt Only Used (8), Shoulder Belt Only Used (2).

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

The crashes were nearly evenly split between single-vehicle and two-vehicle incidents. Single-vehicle crashes accounted for 530 incidents, or 50.2% of the total, while two-vehicle crashes accounted for 501 incidents (47.4%). Multi-vehicle pile-ups involving three or more vehicles were less common, comprising just 25 crashes in total.

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: 1,056
  • Total persons involved: 1,850
  • Total vehicles involved: 1,612

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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Darke County, OH Crash Report — 2021 | ThatCarHitMe.com