Yearly Traffic Safety Analysis

267 CRASHES IN
IOWA, IA
2015

In 2015, Floyd County recorded 267 total traffic crashes, resulting in 1 fatality and 72 injuries. A significant portion of these incidents, 74 crashes or 27.7%, were attributed to collisions with animals.

267

Total Crash Events

1

Persons Killed

72

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Motor vehicle occupants represented the vast majority of casualties in 2015. One motorist was killed and 69 were injured. In addition, three pedestrians were injured in crashes during this period. No cyclist fatalities or injuries were reported.

0

Pedestrians Killed

1

Motorists Killed

3

Pedestrians Injured

69

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 Floyd County during 2015 occurred most frequently on Fridays, with 48 incidents reported. The single busiest hour for crashes was the 5 p.m. hour, which saw 26 crashes. Overall, 135 crashes, representing 50.6% of the total, 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 267 crashes, 209 (78.3%) resulted in no injuries, being property-damage-only incidents. The remaining crashes included 57 that caused non-fatal injuries and one fatal crash. This single fatal crash resulted in one fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
Serious Injury8serious injury crashes3%
Minor Injury17minor injury crashes6.4%
Possible Injury32possible injury crashes12%
No Injury209no injury crashes78.3%

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 most frequently cited contributing factor in Floyd County crashes was 'Animal,' which was involved in 74 incidents, or 27.7% of all crashes. Following this, 'Driving too fast for conditions' was noted in 20 crashes (7.5%), while 'Lost Control' and 'Ran off road - left' were each factors in 17 crashes (6.4%).

Officer-Reported Primary Contributing Cause

Animal74 (27.7%)
Driving too fast for conditions20 (7.5%)
Ran off road - left17 (6.4%)
Lost Control17 (6.4%)
FTYROW: At uncontrolled intersection13 (4.9%)
FTYROW: From stop sign11 (4.1%)
Ran off road - straight10 (3.7%)
Ran Stop Sign10 (3.7%)
Driver Distraction: Other interior distraction8 (3%)
Followed too close8 (3%)

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

Road & Environmental Conditions

A substantial portion of crashes occurred in ideal conditions, with 130 incidents (48.7%) happening in clear weather and 123 (46.1%) on dry road surfaces. Crashes during daylight hours accounted for 135 incidents (50.6%). Adverse road surface conditions were present in numerous crashes, including 34 on ice or frost and 26 on snow.

Weather

Clear130 (62.8%)
Cloudy35 (16.9%)
Snow25 (12.1%)
Rain5 (2.4%)
Blowing Snow4 (1.9%)
Freezing rain/drizzle3 (1.4%)
Sleet, hail2 (1.0%)
Fog, smoke, smog1 (0.5%)
Severe Winds1 (0.5%)
Blowing sand, soil, dirt1 (0.5%)

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

Lighting

Daylight135 (65.2%)
Dark - roadway not lighted41 (19.8%)
Dark - roadway lighted20 (9.7%)
Dusk7 (3.4%)
Dawn3 (1.4%)
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry123 (59.4%)
Ice/frost34 (16.4%)
Snow26 (12.6%)
Wet11 (5.3%)
Slush6 (2.9%)
Gravel6 (2.9%)
Other (explain in narrative)1 (0.5%)

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

Vehicles & Demographics

Analysis of persons involved in crashes shows the 35-44 age group was most represented, with 74 individuals, followed by the 45-54 age group with 72 individuals. Among the 397 vehicles involved, Chevrolet was the most frequent make with 87 vehicles, followed by Ford with 66, and Dodge with 27.

Top Vehicle Makes (397 vehicles)

1
FORD66 (16.6%)
2
CHEV56 (14.1%)
3
CHEVROLET31 (7.8%)
4
DODG15 (3.8%)
5
BUIC15 (3.8%)
6
GMC13 (3.3%)
7
PONTIAC12 (3%)
8
PONT12 (3%)
9
DODGE12 (3%)
10
CHRY11 (2.8%)

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

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

Sex Distribution (365 persons with recorded sex)

Male211 (57.8%)
Female154 (42.2%)

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

Major Cause

The leading major cause of crashes was interaction with an animal, cited in 74 incidents. 'Driving too fast for conditions' was the second most common cause, contributing to 20 crashes. 'Ran off road - left' and 'Lost Control' were each identified as the major cause in 17 crashes.

Major Cause

1
Animal74 (27.9%)
2
Driving too fast for conditions20 (7.5%)
3
Ran off road - left17 (6.4%)
4
Lost Control17 (6.4%)
5
FTYROW: At uncontrolled intersection13 (4.9%)
6
FTYROW: From stop sign11 (4.2%)
7
Ran off road - straight10 (3.8%)
8
Ran Stop Sign10 (3.8%)
9
Driver Distraction: Other interior distraction8 (3%)

Showing top 9 of 37 reported. 28 additional (85 total) not shown: Followed too close, Ran Traffic Signal, Improper Backing, FTYROW: Making left turn, Driver Distraction: Inattentive/lost in thought, FTYROW: From driveway, Other (explain in narrative): No improper action, Made improper turn, Driver Distraction: Exterior distraction, FTYROW: Other (explain in narrative), Crossed centerline (undivided), Swerving/Evasive Action, Improper or erratic lane changing, FTYROW: From yield sign, Driver Distraction: Reaching for object(s)/fallen object(s), Failed to keep in proper lane, Operating vehicle in an reckless, erratic, careless, negligent manner, Other (explain in narrative): Other, Passing: Other passing (explain in narrative), Aggressive driving/road rage, Driver Distraction: Adjusting devices (radio, climate), Cargo/equipment loss or shift, Exceeded authorized speed, Equipment failure, FTYROW: To pedestrian, FTYROW: Making right turn on red signal, Driver Distraction: Talking on a hand-held device, Failed to yield to emergency vehicle.

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

First Harmful Event

The most common first harmful event was a 'Collision with a vehicle in traffic,' which occurred in 108 crashes. The second most frequent event was a 'Collision with an animal,' recorded in 74 crashes. Other notable events included 'Overturn/rollover' and collision with a ditch, each accounting for 14 incidents.

First Harmful Event

1
Collision with: Vehicle in traffic108 (41.4%)
2
Collision with: Animal74 (28.4%)
3
Collision with fixed object: Ditch14 (5.4%)
4
Non-collision events: Overturn/rollover14 (5.4%)
5
Collision with fixed object: Utility pole/light support6 (2.3%)
6
Non-collision events: Jackknife4 (1.5%)
7
Collision with: Parked motor vehicle4 (1.5%)
8
Collision with fixed object: Guardrail - face3 (1.1%)
9
Collision with: Struck/struck by object/cargo/person from other vehicle3 (1.1%)

Showing top 9 of 28 reported. 19 additional (31 total) not shown: Collision with fixed object: Tree, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with fixed object: Traffic sign support, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Fence, Collision with: Re-entering roadway, Collision with fixed object: Ground, Collision with fixed object: Mailbox, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Snow bank, Collision with fixed object: Culvert/pipe opening, Collision with: Thrown or falling object, Collision with fixed object: Building, Miscellaneous events: Fire/explosion, Miscellaneous events: Hit and run, Other (explain in narrative), Collision with fixed object: Embankment.

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

Roadway Junction / Feature

Crashes were more likely to occur away from intersections, with 96 incidents recorded at non-junction locations. A total of 87 crashes occurred at intersections, with four-way intersections being the most common type, accounting for 62 of these incidents. Driveway-related crashes contributed another 14 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature96 (45.9%)
2
Intersection: Four-way intersection62 (29.7%)
3
Intersection: T-intersection19 (9.1%)
4
Non-intersection: Driveway access (within)7 (3.3%)
5
Non-intersection: Driveway access (related, not in)7 (3.3%)
6
Intersection: Other intersection (explain in narrative)4 (1.9%)
7
Non-intersection: Crossover-related3 (1.4%)
8
Non-intersection: Other non-intersection (explain in narrative)3 (1.4%)
9
Non-intersection: Railroad grade crossing3 (1.4%)

Showing top 9 of 13 reported. 4 additional (5 total) not shown: Non-intersection: Alley, Intersection: Y-intersection, Intersection: L-intersection, Interchange-related: Off-ramp, diverge area.

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 168 units recorded. Sport utility vehicles were the second most frequent with 84 units, followed by four-tire light trucks with 67. Tractor/semi-trailers were involved in 22 crashes, and motorcycles were involved in 4.

Vehicle Type

"Other" combines 7 smaller categories (10 records): Farm tractor (2), Single-unit truck (>= 3 axles) (2), Cargo/panel van (2), Limousine/taxi (seats 9-15) (1), Other (explain in narrative) (1), School bus (seats > 15) (1), Passenger van (seats 9-15) (1).

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

Traffic Control Device

The vast majority of crashes, 237, occurred where no traffic controls were present. Crashes at locations with traffic signals accounted for 51 incidents, while those with stop signs accounted for 36 incidents.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): Other (explain in narrative) (1).

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

Most Damaged Area

The most common area of vehicle damage was the front, which was the primary impact point for 84 vehicles. Front-corner impacts were also frequent, with 47 vehicles damaged on the driver-side front corner and 38 on the passenger-side front corner. Rear-end damage was recorded for 22 vehicles.

Most Damaged Area

"Other" combines 10 smaller categories (80 records): Passenger side - front (14), Driver side - front (13), Rear - driver side corner (12), Top (11), Driver side - rear (11), Other (explain in narrative) (5), Non-collision/no damage (5), Rear - passenger side corner (5), Undercarriage (3), Cargo loss (1).

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

Crashes by City

Within Floyd County, Charles City had the highest volume of crashes, with 126 incidents recorded. Other municipalities with notable crash counts include Nora Springs with 9 crashes, and both Rockford and the town of Floyd with 7 crashes each. A total of 161 crashes were recorded within city limits, while the remaining 106 occurred in unincorporated areas of the county.

Crashes by City

1
CHARLES CITY126 (78.3%)
2
NORA SPRINGS9 (5.6%)
3
ROCKFORD7 (4.3%)
4
FLOYD7 (4.3%)
5
RUDD6 (3.7%)
6
MARBLE ROCK5 (3.1%)
7
COLWELL1 (0.6%)

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

Paved vs Unpaved Road

The vast majority of crashes, 247, occurred on paved roads. Crashes on unpaved surfaces such as gravel or dirt accounted for 18 incidents, representing approximately 6.8% of crashes where the road surface type was specified.

Paved vs Unpaved Road

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

Roadway Contributing Factor

Among roadway-related contributing factors, 'Surface condition,' such as wet or icy roads, was the most cited factor, contributing to 43 crashes. Other factors were noted less frequently, with 'Debris,' 'Ruts/holes/bumps,' and 'Shoulders' each contributing to 2 crashes. One crash was related to a work zone.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)43 (82.7%)
2
Debris2 (3.8%)
3
Ruts/holes/bumps2 (3.8%)
4
Shoulders (none, low, soft, high)2 (3.8%)
5
Slippery, loose or worn surface2 (3.8%)
6
Work Zone (roadway-related)1 (1.9%)

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

Driver Condition

In cases where a driver's condition was noted as a factor, being 'Asleep/fatigued' was the most common, recorded for 8 drivers. An emotional state was cited for 4 drivers, while 3 were noted as being under the influence of alcohol. Medical conditions were a factor for 2 drivers.

Driver Condition

1
Asleep/fatigued8 (47.1%)
2
Emotional (e.g. depressed, angry)4 (23.5%)
3
Under the influence of alcohol3 (17.6%)
4
Medical condition (seizure, reaction)2 (11.8%)

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

Property Damage

The estimated property damage for the majority of crashes, 198 incidents, fell within the $1,500 to $7,500 range. A smaller number of crashes resulted in higher damage, with 58 incidents estimated between $7,500 and $25,000. Eight crashes, or 3.0% of the total, involved property 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

Nearly half of all incidents, 129 crashes or 48.3%, were single-vehicle, non-collision events. Among multi-vehicle crashes, the most common type was a broadside collision, accounting for 51 incidents (19.1%). Rear-end collisions were the next most frequent manner, with 23 crashes (8.6%).

Manner of Collision

"Other" combines 3 smaller categories (7 records): Other (explain in narrative) (3), Head-on (front to front) (3), Rear to rear (1).

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

Pre-Crash Driver Action

Prior to impact, the most common driver action was 'Movement essentially straight,' recorded for 246 vehicles. Turning maneuvers were also common pre-crash actions, with 33 vehicles turning left and 20 vehicles turning right. A total of 11 vehicles were stopped in traffic before being involved in a collision.

Pre-Crash Driver Action

1
Movement essentially straight246 (69.1%)
2
Turning left33 (9.3%)
3
Turning right20 (5.6%)
4
Backing12 (3.4%)
5
Stopped in traffic11 (3.1%)
6
Legally Parked10 (2.8%)
7
Other (explain in narrative)7 (2%)
8
Changing lanes6 (1.7%)
9
Slowing/stopping (deceleration)6 (1.7%)

Showing top 9 of 11 reported. 2 additional (5 total) not shown: Leaving traffic lane, Negotiating a curve.

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

Person Type

A total of 470 individuals were involved in crashes in 2015. The vast majority of these, 455 people or 96.8%, were drivers. The remaining individuals included 12 passengers and 3 pedestrians.

Person Type

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

Person Injury Severity

Across all 470 people involved in crashes, a total of 73 casualties were recorded. This included one fatality, 8 serious injuries, 21 minor injuries, and 43 possible injuries. The remaining 397 individuals were not injured.

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 67 vehicle occupants for whom safety equipment use was documented, 57 were using both a shoulder and lap belt. Nine individuals, representing 13.4% of this group, were recorded as using no safety equipment. One person used only a lap belt.

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

Slightly over half of all crashes, 145 incidents or 54.3%, involved a single vehicle. Two-vehicle collisions were also common, accounting for 114 crashes (42.7%). A small number of incidents, 8 crashes, involved three vehicles.

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: 267
  • Total persons involved: 470
  • Total vehicles involved: 397

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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