Yearly Traffic Safety Analysis

163 CRASHES IN
IOWA, IA
2015

In 2015, Emmet County recorded 163 traffic crashes, resulting in 1 fatality and 44 injuries. A significant portion of these incidents, nearly 23%, were attributed to collisions involving animals. These events represent the single most frequent contributing factor cited in crash reports for the year.

163

Total Crash Events

1

Persons Killed

44

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

In 2015, crash casualties primarily involved motor vehicle occupants, with 1 motorist killed and 43 injured. One pedestrian was also injured in a crash during this period. There were no reported fatalities or injuries involving cyclists.

0

Pedestrians Killed

1

Motorists Killed

1

Pedestrians Injured

43

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

Crash occurrences in Emmet County were highest on Mondays and Fridays, each accounting for 28 incidents. The most frequent time for crashes was the 3 p.m. hour, with 15 events recorded. A majority of crashes, 89 out of 163, 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, 124 out of 163 or 76.1%, resulted in no injuries. Injury-related crashes, including those with possible, minor, or serious injuries, accounted for 38 incidents. One crash was fatal, resulting in one death; a single crash can result in multiple fatalities, though that was not the case here.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury3serious injury crashes1.8%
Minor Injury17minor injury crashes10.4%
Possible Injury18possible injury crashes11%
No Injury124no injury crashes76.1%

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 prominent contributing factor to crashes was the presence of an animal, cited in 37 incidents, or 22.7% of the total. Following this, driving too fast for conditions was noted in 15 crashes (9.2%), and loss of control was a factor in 12 crashes (7.4%). Other frequently cited factors included reckless or careless operation (11 crashes) and following too closely (11 crashes).

Officer-Reported Primary Contributing Cause

Animal37 (22.7%)
Driving too fast for conditions15 (9.2%)
Lost Control12 (7.4%)
Other (explain in narrative): Other12 (7.4%)
Operating vehicle in an reckless, erratic, careless, negligent manner11 (6.7%)
Followed too close11 (6.7%)
FTYROW: From stop sign8 (4.9%)
Driver Distraction: Other interior distraction7 (4.3%)
Ran off road - straight5 (3.1%)
FTYROW: From driveway4 (2.5%)

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

Road & Environmental Conditions

More than half of all crashes (54.6%) occurred in daylight, with 50.3% in clear weather and 59.5% on dry road surfaces, indicating most incidents happened in ideal driving conditions. Adverse conditions were also present in a number of crashes, with 11 incidents occurring during snowfall and 32 taking place on unlighted dark roadways.

Weather

Clear82 (59.9%)
Cloudy29 (21.2%)
Snow11 (8.0%)
Rain6 (4.4%)
Severe Winds4 (2.9%)
Fog, smoke, smog2 (1.5%)
Blowing Snow2 (1.5%)
Freezing rain/drizzle1 (0.7%)

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

Lighting

Daylight89 (64.5%)
Dark - roadway not lighted32 (23.2%)
Dark - roadway lighted17 (12.3%)

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

Road Surface

Dry97 (69.8%)
Snow16 (11.5%)
Ice/frost11 (7.9%)
Wet9 (6.5%)
Gravel5 (3.6%)
Other (explain in narrative)1 (0.7%)

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

Vehicles & Demographics

The 16-20 age group was the most frequently involved in crashes, accounting for 57 of the 300 individuals recorded. Among vehicle makes involved in incidents, Ford was listed 34 times, while Chevrolet appeared as 'CHEV' (31 times) and 'CHEVROLET' (27 times). GMC vehicles were involved in 18 crashes, and Pontiac models ('PONT' and 'PONTIAC') were noted in a combined 25 instances.

Top Vehicle Makes (253 vehicles)

1
FORD34 (13.4%)
2
CHEV31 (12.3%)
3
CHEVROLET27 (10.7%)
4
GMC18 (7.1%)
5
PONT14 (5.5%)
6
DODGE12 (4.7%)
7
PONTIAC11 (4.3%)
8
BUIC10 (4%)
9
CHRY9 (3.6%)
10
DODG9 (3.6%)

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

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

Sex Distribution (210 persons with recorded sex)

Male108 (51.4%)
Female102 (48.6%)

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 in Emmet County was an animal on the roadway, accounting for 37 incidents. Driver-related actions followed, with 'Driving too fast for conditions' cited in 15 crashes and 'Lost Control' in 12 crashes. Following too closely and reckless or erratic driving were each cited as the major cause in 11 crashes.

Major Cause

1
Animal37 (23.4%)
2
Driving too fast for conditions15 (9.5%)
3
Lost Control12 (7.6%)
4
Other (explain in narrative): Other12 (7.6%)
5
Operating vehicle in an reckless, erratic, careless, negligent manner11 (7%)
6
Followed too close11 (7%)
7
FTYROW: From stop sign8 (5.1%)
8
Driver Distraction: Other interior distraction7 (4.4%)
9
Ran off road - straight5 (3.2%)

Showing top 9 of 30 reported. 21 additional (40 total) not shown: FTYROW: From driveway, Ran Stop Sign, Improper Backing, Driver Distraction: Adjusting devices (radio, climate), Driver Distraction: Exterior distraction, FTYROW: At uncontrolled intersection, Driver Distraction: Inattentive/lost in thought, FTYROW: From parked position, Driver Distraction: Passenger, FTYROW: Other (explain in narrative), Crossed centerline (undivided), Driver Distraction: Talking on a hand-held device, Failed to yield to emergency vehicle, Driver Distraction: Manual operation of an electronic communication device, FTYROW: To pedestrian, Operator inexperience, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed, Ran off road - right, Ran Traffic Signal, Exceeded authorized speed.

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 another vehicle in traffic, which occurred in 66 crashes (40.5%). The second most frequent event was a collision with an animal, accounting for 36 crashes (22.1%). Events indicating a run-off-road crash, such as striking a ditch (14 crashes) or an overturn/rollover (12 crashes), were also significant.

First Harmful Event

1
Collision with: Vehicle in traffic66 (40.7%)
2
Collision with: Animal36 (22.2%)
3
Collision with fixed object: Ditch14 (8.6%)
4
Non-collision events: Overturn/rollover12 (7.4%)
5
Collision with: Parked motor vehicle10 (6.2%)
6
Collision with: Re-entering roadway5 (3.1%)
7
Collision with fixed object: Tree3 (1.9%)
8
Non-collision events: Other non-collision (explain in narrative)2 (1.2%)
9
Collision with fixed object: Other post/pole/support (explain in narrative)2 (1.2%)

Showing top 9 of 21 reported. 12 additional (12 total) not shown: Miscellaneous events: Hit and run, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Vehicle went airborne, Other (explain in narrative), Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Fence, Collision with fixed object: Guardrail - face, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Utility pole/light support, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Other non-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, 89 out of 163 (54.6%), occurred at non-intersection locations. Crashes at intersections were less frequent, with four-way intersections being the most common type, accounting for 30 incidents. An additional 10 crashes were related to driveway access points.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature89 (63.6%)
2
Intersection: Four-way intersection30 (21.4%)
3
Non-intersection: Driveway access (related, not in)10 (7.1%)
4
Intersection: Y-intersection3 (2.1%)
5
Intersection: T-intersection3 (2.1%)
6
Non-intersection: Alley1 (0.7%)
7
Interchange-related: Other interchange (explain in narrative)1 (0.7%)
8
Non-intersection: Driveway access (within)1 (0.7%)
9
Intersection: Other intersection (explain in narrative)1 (0.7%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Intersection: Intersection with ramp.

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, accounting for 118 of the 253 vehicles. Sport utility vehicles (50 vehicles) and four-tire light trucks or pickups (51 vehicles) were also frequently involved, collectively representing about 40% of all vehicles. Tractor/semi-trailers were involved in 6 crashes, and motorcycles were involved in 2.

Vehicle Type

"Other" combines 4 smaller categories (5 records): Moped (2), Other heavy truck (> 10000 lbs) (cannot classify) (1), Farm tractor (1), Cargo/panel van (1).

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

Traffic Control Device

The majority of vehicles involved in crashes were in areas with no traffic controls present, as this was noted for 160 of the 253 vehicles. For crashes where traffic controls were a factor, traffic signals and stop signs were the most common, associated with 29 and 28 vehicles respectively.

Traffic Control Device

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

Most Damaged Area

Frontal impacts were the most common area of damage, recorded for 64 vehicles. This suggests a high number of head-on or frontal collisions with objects. Rear impacts, indicative of rear-end collisions, were the second most frequent damage area, noted on 31 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (49 records): Driver side - rear (11), Rear - passenger side corner (8), Driver side - middle (8), Passenger side - rear (8), Driver side - front (7), Passenger side - front (2), Other (explain in narrative) (2), Undercarriage (2), Non-collision/no damage (1).

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

Crashes by City

The city of Estherville was the site of the majority of municipal crashes, with 90 incidents recorded in 2015. Far fewer crashes occurred in other towns, including 5 in Armstrong and 4 in Wallingford. A significant number of crashes in the county occurred outside of any incorporated city limits.

Crashes by City

1
ESTHERVILLE90 (86.5%)
2
ARMSTRONG5 (4.8%)
3
WALLINGFORD4 (3.8%)
4
GRUVER2 (1.9%)
5
RINGSTED2 (1.9%)
6
DOLLIVER1 (1%)

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, 153 out of 162 with recorded road surface type, occurred on paved roads. Crashes on unpaved surfaces, such as gravel or dirt roads, accounted for 9 incidents, or approximately 5.6% of the total.

Paved vs Unpaved Road

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

Roadway Contributing Factor

In cases where a roadway factor was noted as contributing to a crash, adverse surface conditions such as wet or icy pavement were the most common, cited in 17 incidents. Work zones were identified as a contributing factor in one crash. In total, a roadway factor was cited in 22 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)17 (77.3%)
2
Slippery, loose or worn surface2 (9.1%)
3
Non-highway work1 (4.5%)
4
Traffic backup, regular congestion1 (4.5%)
5
Work Zone (roadway-related)1 (4.5%)

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, being under the influence of alcohol was the most frequent, noted for 9 individuals. Additionally, 2 drivers were reported as asleep or fatigued, a condition often associated with rural driving. Other noted conditions included emotional distress and medical events.

Driver Condition

1
Under the influence of alcohol9 (64.3%)
2
Asleep/fatigued2 (14.3%)
3
Emotional (e.g. depressed, angry)1 (7.1%)
4
Medical condition (seizure, reaction)1 (7.1%)
5
Paraplegic/wheelchair restricted1 (7.1%)

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 fell into the $1,500 to $7,500 range, which applied to 135 of the 163 incidents. Only one crash was estimated to have damage exceeding $25,000, while 26 crashes were in the $7,500 to $25,000 range.

Property Damage

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

Manner of Collision

Single-vehicle crashes, categorized as 'Non-collision', were the most frequent type of incident, accounting for 67 crashes or 41.1% of the total. Among multi-vehicle crashes, rear-end collisions were the most common, with 33 incidents (20.2%), followed by broadside collisions with 19 incidents (11.7%).

Manner of Collision

"Other" combines 3 smaller categories (4 records): Sideswipe, opposite direction (2), Angle, oncoming left turn (1), 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

Among the 253 vehicles involved in crashes, the most common pre-crash action was moving straight ahead, which was reported for 134 vehicles (53.0%). The next most frequent actions were backing (25 vehicles) and being legally parked (19 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight134 (57.3%)
2
Backing25 (10.7%)
3
Legally Parked19 (8.1%)
4
Stopped in traffic13 (5.6%)
5
Turning left13 (5.6%)
6
Turning right9 (3.8%)
7
Slowing/stopping (deceleration)8 (3.4%)
8
Negotiating a curve6 (2.6%)
9
Other (explain in narrative)4 (1.7%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Illegally Parked/Unattended, Leaving a parked position, Making U-turn.

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

Person Type

Of the 300 individuals involved in crashes, the overwhelming majority, 293 people (97.7%), were drivers. Passengers accounted for 6 individuals, and one person was a pedestrian. No cyclists were recorded as being involved in crashes during this period.

Person Type

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

Person Injury Severity

Across all 300 people involved in crashes, there was 1 fatality. A total of 44 individuals sustained injuries, with 3 classified as serious, 18 as minor, and 23 as possible injuries. The remaining individuals were not reported as injured.

Person Injury Severity

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

Occupant Safety Equipment

Data on safety equipment use was available for a small subset of 36 occupants. Within this group, 9 individuals (25%) were reported as not using any safety restraints. The majority, 26 occupants, were recorded as using a shoulder and 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

Crashes in Emmet County were almost evenly split between single-vehicle and two-vehicle incidents. Two-vehicle crashes were slightly more common, with 83 incidents (50.9%), while single-vehicle crashes accounted for 77 incidents (47.2%). Only 3 crashes involved more than two 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: 163
  • Total persons involved: 300
  • Total vehicles involved: 253

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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