Yearly Traffic Safety Analysis

39 CRASHES IN
IOWA, IA
2015

In 2015, Ringgold County recorded 39 total crashes, resulting in 0 fatalities and 22 injuries. A significant portion of these incidents, 64.1%, were single-vehicle crashes. Collisions with animals were the most frequently cited contributing factor, accounting for 20.5% of all crashes.

39

Total Crash Events

0

Persons Killed

22

Persons Injured

0

Fatal Crash Events

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: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

In 2015, there were no fatalities among any road users in Ringgold County. All 22 reported injuries were sustained by motorists involved in crashes. There were no recorded injuries or fatalities involving pedestrians or cyclists during this period.

0

Motorists Killed

22

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in Ringgold County occurred most frequently on Tuesdays, which saw 8 incidents, and on Sundays and Fridays, which each saw 7. The most common time for crashes was the 2 p.m. hour, with 6 recorded events, followed by the 3 p.m. hour with 5 events. Overall, 23 of the 39 crashes, or 59%, happened during daylight hours.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 39 crashes in 2015, none were fatal. Injury-involved crashes accounted for 46.2% of the total, with 3 serious injuries, 6 minor injuries, and 9 possible injuries reported across 18 separate incidents. The remaining 53.8% of crashes, totaling 21 incidents, resulted in no injuries.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes7.7%
Minor Injury6minor injury crashes15.4%
Possible Injury9possible injury crashes23.1%
No Injury21no injury crashes53.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor for crashes was animals in the roadway, cited in 8 incidents (20.5%). Losing control of the vehicle was the second most common factor, noted in 6 crashes (15.4%). Other notable factors included running a stop sign and various forms of driver distraction, which together accounted for another 6 crashes.

Officer-Reported Primary Contributing Cause

Animal8 (20.5%)
Lost Control6 (15.4%)
Ran Stop Sign3 (7.7%)
Driver Distraction: Other interior distraction3 (7.7%)
Ran off road - straight2 (5.1%)
Other (explain in narrative): Other2 (5.1%)
Driver Distraction: Reaching for object(s)/fallen object(s)2 (5.1%)
FTYROW: From stop sign1 (2.6%)
FTYROW: Making left turn1 (2.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner1 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The vast majority of crashes occurred in favorable conditions, with 25 of 39 incidents (64.1%) happening in clear weather. Similarly, 26 crashes (66.7%) took place on dry road surfaces. Daylight conditions were present for 23 crashes, accounting for 59% of the total.

Weather

Clear25 (73.5%)
Cloudy3 (8.8%)
Rain3 (8.8%)
Fog, smoke, smog2 (5.9%)
Freezing rain/drizzle1 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight23 (67.6%)
Dark - roadway not lighted7 (20.6%)
Dawn2 (5.9%)
Dark - roadway lighted1 (2.9%)
Dusk1 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry26 (76.5%)
Wet4 (11.8%)
Other (explain in narrative)1 (2.9%)
Mud, dirt1 (2.9%)
Gravel1 (2.9%)
Ice/frost1 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Among the 78 people involved in crashes, the 35-44 age group was the most represented with 18 individuals, followed by the 16-20 age group with 14 individuals. Of the 55 vehicles involved, Ford was the most frequent make with 10 vehicles. Chevrolet (including abbreviated 'CHEV' entries) accounted for 11 vehicles, and Kia and Dodge ('DODG') each appeared 3 times.

Top Vehicle Makes (55 vehicles)

1
FORD10 (18.2%)
2
CHEVROLET6 (10.9%)
3
CHEV5 (9.1%)
4
BUICK3 (5.5%)
5
KIA3 (5.5%)
6
DODG3 (5.5%)
7
OLDS2 (3.6%)
8
GMC2 (3.6%)
9
HD2 (3.6%)
10
CHRY2 (3.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Sex Distribution (48 persons with recorded sex)

Male30 (62.5%)
Female18 (37.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most common major cause identified in crashes was interaction with an animal, accounting for 8 incidents (20.5%). Losing control was the second leading cause with 6 crashes (15.4%). Running a stop sign and other interior driver distractions were each cited as the major cause in 3 separate crashes (7.7% each).

Major Cause

1
Animal8 (21.1%)
2
Lost Control6 (15.8%)
3
Ran Stop Sign3 (7.9%)
4
Driver Distraction: Other interior distraction3 (7.9%)
5
Ran off road - straight2 (5.3%)
6
Other (explain in narrative): Other2 (5.3%)
7
Driver Distraction: Reaching for object(s)/fallen object(s)2 (5.3%)
8
FTYROW: From stop sign1 (2.6%)
9
FTYROW: Making left turn1 (2.6%)

Showing top 9 of 19 reported. 10 additional (10 total) not shown: Operating vehicle in an reckless, erratic, careless, negligent manner, Ran off road - left, Ran off road - right, Traveling wrong way or on wrong side of road, Cargo/equipment loss or shift, Crossed centerline (undivided), Driver Distraction: Inattentive/lost in thought, Driving too fast for conditions, Exceeded authorized speed, Followed too close.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most frequent first harmful event was a collision with another vehicle in traffic, occurring in 9 crashes. This was closely followed by collisions with an animal, which was the first event in 8 crashes. Collisions with a fixed object, such as a ditch (5 incidents), accounted for a significant portion of the remaining events.

First Harmful Event

1
Collision with: Vehicle in traffic9 (23.7%)
2
Collision with: Animal8 (21.1%)
3
Other (explain in narrative)6 (15.8%)
4
Collision with fixed object: Ditch5 (13.2%)
5
Collision with fixed object: Culvert/pipe opening2 (5.3%)
6
Collision with fixed object: Tree1 (2.6%)
7
Collision with: Other non-fixed object (explain in narrative)1 (2.6%)
8
Non-collision events: Other non-collision (explain in narrative)1 (2.6%)
9
Non-collision events: Overturn/rollover1 (2.6%)

Showing top 9 of 13 reported. 4 additional (4 total) not shown: Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Building, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Guardrail - face.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

The majority of crashes, 20 out of 39 (51.3%), occurred at non-junction locations along a road segment. Intersections were the site of 8 crashes, with 6 at four-way intersections and 2 at T-intersections. Driveway access was related to 3 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature20 (58.8%)
2
Intersection: Four-way intersection6 (17.6%)
3
Non-intersection: Driveway access (related, not in)3 (8.8%)
4
Intersection: T-intersection2 (5.9%)
5
Non-intersection: Other non-intersection (explain in narrative)2 (5.9%)
6
Intersection: Other intersection (explain in narrative)1 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, with 22 units recorded. Light trucks and pickups were the next most frequent with 13 vehicles, followed by Sport Utility Vehicles (SUVs) with 10. Motorcycles were involved in 3 crashes, and tractor-trailers were involved in 2.

Vehicle Type

"Other" combines 2 smaller categories (2 records): Passenger van (seats 9-15) (1), Farm tractor (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

A large majority of vehicles involved in crashes were in areas with no traffic controls present, accounting for 41 of the 55 vehicles. Stop signs were the most common form of traffic control noted, present for 7 vehicles. A No Passing Zone was noted for one vehicle involved in a crash.

Traffic Control Device

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common area of damage, reported for 15 vehicles. Front corners were the primary point of damage for 8 vehicles, while the rear was the most damaged area for 4 vehicles. This suggests a mix of frontal, angle, and rear-end collision dynamics.

Most Damaged Area

"Other" combines 8 smaller categories (12 records): Driver side - front (2), Driver side - middle (2), Passenger side - front (2), Top (2), Non-collision/no damage (1), Rear - passenger side corner (1), Undercarriage (1), Passenger side - rear (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Crashes by City

Within Ringgold County, Mount Ayr experienced the highest number of crashes with 18 incidents. Kellerton and Redding followed with 2 crashes each. Several other towns, including Blockton, Delphos, Tingley, and Diagonal, each recorded a single crash.

Crashes by City

1
MOUNT AYR18 (69.2%)
2
KELLERTON2 (7.7%)
3
REDDING2 (7.7%)
4
BLOCKTON1 (3.8%)
5
DELPHOS1 (3.8%)
6
TINGLEY1 (3.8%)
7
DIAGONAL1 (3.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

Crashes predominantly occurred on paved roads, which accounted for 34 of the 39 total incidents (87.2%). Unpaved roads, such as gravel or dirt, were the site of 5 crashes, representing 12.8% of the total for the year.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most common estimated property damage cost was in the $1,500 to $7,500 range, which applied to 27 of the 39 crashes. Ten crashes resulted in damages between $7,500 and $25,000. Only one crash was estimated to have damage exceeding $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events were the most frequent manner of crash, accounting for 25 incidents or 64.1% of the total. Among multi-vehicle crashes, broadside collisions were the most common with 6 incidents (15.4%), followed by rear-end and opposite-direction sideswipe collisions, each with 3 incidents.

Manner of Collision

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The vast majority of vehicles involved in crashes were moving essentially straight prior to the incident, with this action recorded for 44 of the 55 vehicles. Turning left was the pre-crash action for 5 vehicles. Backing was noted for 2 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight44 (84.6%)
2
Turning left5 (9.6%)
3
Backing2 (3.8%)
4
Negotiating a curve1 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Drivers constituted the overwhelming majority of individuals involved in crashes, with 73 of the 78 total persons being drivers (93.6%). The remaining 5 individuals were passengers. No pedestrians or other non-occupant types were involved in crashes.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 78 people involved in crashes, 22 sustained some level of injury. This included 3 serious injuries, 8 minor injuries, and 11 possible injuries. There were no fatalities recorded among any persons involved in crashes during this period.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Among the individuals for whom safety equipment use was recorded, 10 were noted as using a shoulder and lap belt. Four individuals were recorded as using no safety equipment. One person used a DOT-compliant helmet, and another was in a forward-facing child safety seat.

Occupant Safety Equipment

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Single-vehicle crashes were the most common type, with 25 of the 39 total incidents (64.1%) involving only one vehicle. Twelve crashes involved two vehicles (30.8%). The remaining two crashes were multi-vehicle incidents involving three vehicles each.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS 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: ArcGIS 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: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 39
  • Total persons involved: 78
  • Total vehicles involved: 55

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). "iowa, IA Crash Intelligence Report: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-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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