Yearly Traffic Safety Analysis

150 CRASHES IN
IOWA, IA
2015

In Palo Alto County during 2015, there were 150 total vehicle crashes, resulting in 0 fatalities and 54 injuries. A significant portion of these incidents, 26.7%, were attributed to collisions with animals, which was the leading contributing factor reported. The majority of crashes, 78%, resulted in no injuries.

150

Total Crash Events

0

Persons Killed

54

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, all 54 reported injuries and 0 fatalities involved motorists. There were no pedestrians or cyclists reported as killed or injured in any traffic crashes within the county during this period. The data indicates that crash impacts were confined to vehicle occupants.

0

Motorists Killed

54

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 Palo Alto County were most frequent on Mondays, which saw 31 incidents in 2015. The single busiest hour for crashes was 3 p.m., with 12 recorded events. Overall, a majority of crashes, 80 out of 150, occurred 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

The vast majority of crashes, 78% (117 incidents), resulted in no injuries. Injury-related crashes accounted for the remaining 22%, with 2 classified as serious injury, 20 as minor injury, and 11 as possible injury. There were no fatal crashes recorded in 2015, and consequently, no fatalities.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.3%
Minor Injury20minor injury crashes13.3%
Possible Injury11possible injury crashes7.3%
No Injury117no injury crashes78%

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 common contributing factor cited in crashes was 'Animal,' accounting for 40 incidents, or 26.7% of the total. Other significant factors included 'Failure to Yield Right of Way from a stop sign' with 12 crashes (8.0%) and 'Lost Control' with 11 crashes (7.3%). Various forms of driver distraction were noted in 8 crashes combined.

Officer-Reported Primary Contributing Cause

Animal40 (26.7%)
FTYROW: From stop sign12 (8%)
Lost Control11 (7.3%)
Ran off road - straight9 (6%)
Driving too fast for conditions8 (5.3%)
Ran Stop Sign7 (4.7%)
FTYROW: At uncontrolled intersection7 (4.7%)
Followed too close7 (4.7%)
Ran off road - left6 (4%)
Other (explain in narrative): Other5 (3.3%)

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 majority of crashes occurred in favorable conditions, with 80 incidents happening in daylight, 70 on dry road surfaces, and 54 in clear weather. Adverse conditions included 24 crashes on unlighted dark roadways, 15 on icy or frosty surfaces, and 8 during snowfall.

Weather

Clear54 (50.5%)
Cloudy34 (31.8%)
Snow8 (7.5%)
Rain6 (5.6%)
Freezing rain/drizzle3 (2.8%)
Fog, smoke, smog1 (0.9%)
Severe Winds1 (0.9%)

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

Lighting

Daylight80 (72.1%)
Dark - roadway not lighted24 (21.6%)
Dark - roadway lighted4 (3.6%)
Dawn2 (1.8%)
Dusk1 (0.9%)

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

Road Surface

Dry70 (63.6%)
Ice/frost15 (13.6%)
Wet9 (8.2%)
Snow8 (7.3%)
Gravel5 (4.5%)
Other (explain in narrative)2 (1.8%)
Slush1 (0.9%)

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

Vehicles & Demographics

Analysis of the 277 people involved in crashes shows the most represented age groups were 45-54 years old (45 people), 16-20 years old (44 people), and 26-34 years old (40 people). Among the 223 vehicles involved, Chevrolet was the most frequent make with 62 vehicles, followed by Ford with 37 and Dodge with 24.

Top Vehicle Makes (223 vehicles)

1
FORD37 (16.6%)
2
CHEV36 (16.1%)
3
CHEVROLET26 (11.7%)
4
DODGE12 (5.4%)
5
DODG12 (5.4%)
6
GMC8 (3.6%)
7
BUIC7 (3.1%)
8
CHRYSLER6 (2.7%)
9
BUICK6 (2.7%)
10
PONTIAC5 (2.2%)

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

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

Sex Distribution (205 persons with recorded sex)

Male118 (57.6%)
Female87 (42.4%)

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 40 incidents (26.7%). Failure to yield the right of way from a stop sign was the second most common cause, contributing to 12 crashes (8.0%). This was followed by losing control of the vehicle (11 crashes, 7.3%) and running off a straight road (9 crashes, 6.0%).

Major Cause

1
Animal40 (27.8%)
2
FTYROW: From stop sign12 (8.3%)
3
Lost Control11 (7.6%)
4
Ran off road - straight9 (6.3%)
5
Driving too fast for conditions8 (5.6%)
6
Ran Stop Sign7 (4.9%)
7
FTYROW: At uncontrolled intersection7 (4.9%)
8
Followed too close7 (4.9%)
9
Ran off road - left6 (4.2%)

Showing top 9 of 28 reported. 19 additional (37 total) not shown: Other (explain in narrative): Other, FTYROW: From driveway, Driver Distraction: Other interior distraction, Other (explain in narrative): No improper action, Equipment failure, FTYROW: Making left turn, FTYROW: Other (explain in narrative), Driver Distraction: Exterior distraction, Operator inexperience, Driver Distraction: Other electronic device activity, Driver Distraction: Passenger, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Cargo/equipment loss or shift, Failure to signal intentions, Crossed centerline (undivided), Swerving/Evasive Action, Traveling wrong way or on wrong side of road, Made improper turn.

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, which occurred in 59 crashes. The second most common event was a collision with an animal, recorded in 40 incidents. Collisions with fixed objects were also prevalent, with hitting a ditch being the most common of these with 11 occurrences, followed by rollovers in 10 non-collision events.

First Harmful Event

1
Collision with: Vehicle in traffic59 (39.9%)
2
Collision with: Animal40 (27%)
3
Collision with fixed object: Ditch11 (7.4%)
4
Non-collision events: Overturn/rollover10 (6.8%)
5
Other (explain in narrative)4 (2.7%)
6
Collision with fixed object: Embankment4 (2.7%)
7
Collision with fixed object: Tree4 (2.7%)
8
Collision with fixed object: Utility pole/light support2 (1.4%)
9
Collision with fixed object: Bridge/bridge rail parapet2 (1.4%)

Showing top 9 of 19 reported. 10 additional (12 total) not shown: Collision with: Other non-fixed object (explain in narrative), Collision with: Parked motor vehicle, Collision with fixed object: Bridge pier or support, Collision with: Re-entering roadway, Collision with fixed object: Guardrail - face, Miscellaneous events: Hit and run, Miscellaneous events: Vehicle out of gear/rolled, Collision with fixed object: Building, Collision with fixed object: Traffic sign support, Collision with fixed object: Other fixed object (explain in narrative).

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

Roadway Junction / Feature

A majority of crashes, 60 incidents, occurred at non-junction locations along a road segment, with an additional 10 crashes related to driveways. In contrast, 40 crashes happened at intersections, with four-way intersections being the most common type, accounting for 28 of these incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature60 (54.5%)
2
Intersection: Four-way intersection28 (25.5%)
3
Intersection: T-intersection11 (10%)
4
Non-intersection: Driveway access (related, not in)9 (8.2%)
5
Non-intersection: Driveway access (within)1 (0.9%)
6
Intersection: Other intersection (explain in narrative)1 (0.9%)

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 76 units recorded. Light trucks and pickups were the second most frequent with 58 vehicles, followed by sport utility vehicles at 49. Crashes also involved 12 tractor/semi-trailers and 2 motorcycles.

Vehicle Type

"Other" combines 6 smaller categories (8 records): Farm tractor (2), Single unit truck (2-axle, 6-tire) (2), Maintenance/construction vehicle (1), Motor home/recreational vehicle (1), School bus (seats > 15) (1), All-terrain vehicle (ATV) (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 occurred where no traffic controls were present, with 147 such instances reported. Stop signs were the most common form of traffic control involved in crashes, noted in 28 cases. Traffic signals were a factor in 4 incidents.

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 in 48 cases. Side impacts were also frequent, with 19 instances of damage to the driver's side middle area and 14 to the passenger's side middle area. Damage to the rear of the vehicle was noted in 8 crashes.

Most Damaged Area

"Other" combines 10 smaller categories (53 records): Driver side - rear (9), Rear (8), Front - passenger side corner (7), Passenger side - front (7), Rear - passenger side corner (6), Rear - driver side corner (5), Other (explain in narrative) (4), Undercarriage (3), Non-collision/no damage (3), Cargo loss (1).

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

Crashes by City

Crash distribution across municipalities shows Emmetsburg with the highest volume, recording 40 crashes. West Bend had the second-highest number of incidents with 8, followed closely by Graettinger with 7. The remaining crashes were spread across Ruthven (2), Ayrshire (1), and Cylinder (1).

Crashes by City

1
EMMETSBURG40 (67.8%)
2
WEST BEND8 (13.6%)
3
GRAETTINGER7 (11.9%)
4
RUTHVEN2 (3.4%)
5
AYRSHIRE1 (1.7%)
6
CYLINDER1 (1.7%)

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

Paved vs Unpaved Road

The data indicates that 128 crashes occurred on paved roads. A notable portion, 20 crashes or approximately 13.5% of the reported total, took place on unpaved surfaces such as gravel or dirt roads.

Paved vs Unpaved Road

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

Roadway Contributing Factor

For the small number of crashes where a roadway factor was cited, surface condition was the leading contributor, noted in 17 incidents. Other factors such as ruts, holes, or worn surfaces were each cited in a single crash. In most incidents, no specific roadway factor was identified as a contributor.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)17 (89.5%)
2
Ruts/holes/bumps1 (5.3%)
3
Slippery, loose or worn surface1 (5.3%)

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 100 crashes. Forty crashes resulted in damages between $7,500 and $25,000. Nine crashes were estimated to have damage costs 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 common manner of crash, accounting for 65 incidents or 43.3% of the total. Among multi-vehicle crashes, broadside collisions were most frequent, with 26 occurrences (17.3%). Rear-end collisions were reported in 13 crashes, representing 8.7% of the total.

Manner of Collision

"Other" combines 3 smaller categories (5 records): Angle, oncoming left turn (2), Head-on (front to front) (2), 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

The vast majority of vehicles, 133, were moving essentially straight prior to the crash. The next most common pre-crash actions were turning left, reported for 13 vehicles, and being legally parked, reported for 12 vehicles. Other actions like backing and slowing were less frequent.

Pre-Crash Driver Action

1
Movement essentially straight133 (68.9%)
2
Turning left13 (6.7%)
3
Legally Parked12 (6.2%)
4
Backing11 (5.7%)
5
Slowing/stopping (deceleration)6 (3.1%)
6
Turning right6 (3.1%)
7
Overtaking/passing3 (1.6%)
8
Other (explain in narrative)2 (1%)
9
Negotiating a curve1 (0.5%)

Showing top 9 of 15 reported. 6 additional (6 total) not shown: Changing lanes, Entering a parked position, Entering traffic lane (merging), Leaving traffic lane, Accelerating in road, Stopped in traffic.

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

Person Type

Of the 277 individuals involved in crashes, the overwhelming majority, 262 people, were drivers. Passengers accounted for the remaining 15 individuals. No other person types, such as pedestrians or cyclists, were recorded in the crash data.

Person Type

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

Person Injury Severity

A total of 54 individuals sustained injuries in crashes. Among these, 30 were classified as minor injuries, 21 as possible injuries, and 3 as serious injuries. No fatalities were 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

Based on available data for 43 occupants, 33 were reported as using a shoulder and lap belt. Seven individuals were recorded as not using any safety equipment. The data also noted the use of a booster seat, a lap belt only, and a forward-facing child seat in one instance each.

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 80 incidents, making up 53.3% of the total. Two-vehicle collisions were also frequent, accounting for 68 crashes (45.3%). There were two multi-vehicle incidents reported, one involving three vehicles and another involving four.

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: 150
  • Total persons involved: 277
  • Total vehicles involved: 223

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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