Yearly Traffic Safety Analysis

219 CRASHES IN
IOWA, IA
2015

In 2015, Dickinson County recorded 219 traffic crashes, which resulted in 4 fatalities and 91 injuries. These incidents involved a total of 376 vehicles and 473 individuals. A notable finding from the data is that collisions with animals were the single most cited contributing factor, accounting for 30 separate crashes.

219

Total Crash Events

4

Persons Killed

91

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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, crashes resulted in 4 deaths and 91 injuries. Motorists represented the largest group of casualties, with 3 individuals killed and 85 injured. Among vulnerable road users, one cyclist was killed and three were injured, while two pedestrians sustained injuries.

0

Pedestrians Killed

1

Cyclists Killed

3

Motorists Killed

0

Other Killed

2

Pedestrians Injured

3

Cyclists Injured

85

Motorists Injured

1

Other 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 Dickinson County were most frequent on Tuesdays, with 43 incidents recorded, closely followed by Thursdays with 42. The afternoon hours showed the highest crash concentration, with a peak of 19 crashes in the 4 p.m. hour and 18 crashes in both the 12 p.m. and 5 p.m. hours. The majority of crashes, 148 out of 219, 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

Of the 219 total crashes, approximately two-thirds (66.7%) resulted in no injuries, involving only property damage. The remaining crashes involved injuries of varying degrees: 14 were classified as serious injury, 23 as minor injury, and 32 as possible injury. Four separate crashes were classified as fatal, resulting in a total of four fatalities.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.8%
Serious Injury14serious injury crashes6.4%
Minor Injury23minor injury crashes10.5%
Possible Injury32possible injury crashes14.6%
No Injury146no injury crashes66.7%

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 identified in crash reports was 'Animal,' accounting for 30 incidents, or 13.7% of the total. 'Followed too close' was the second most common factor, cited in 24 crashes (11.0%). 'Driving too fast for conditions' was listed as a factor in 15 crashes (6.8%).

Officer-Reported Primary Contributing Cause

Animal30 (13.7%)
Followed too close24 (11%)
Driving too fast for conditions15 (6.8%)
FTYROW: Making left turn13 (5.9%)
FTYROW: From stop sign12 (5.5%)
Ran off road - left12 (5.5%)
Lost Control10 (4.6%)
Driver Distraction: Other interior distraction8 (3.7%)
Improper or erratic lane changing7 (3.2%)
Other (explain in narrative): Other7 (3.2%)

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 majority of crashes occurred in favorable conditions, with 67.6% happening in daylight and 62.1% on dry road surfaces. Clear weather was reported for 120 of the 219 crashes. Adverse conditions were less frequent, with 15 crashes occurring during rain and 20 on snow-covered roads.

Weather

Clear120 (62.2%)
Cloudy34 (17.6%)
Rain15 (7.8%)
Snow13 (6.7%)
Freezing rain/drizzle4 (2.1%)
Fog, smoke, smog2 (1.0%)
Severe Winds2 (1.0%)
Blowing Snow2 (1.0%)
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

Daylight148 (76.3%)
Dark - roadway lighted22 (11.3%)
Dark - roadway not lighted17 (8.8%)
Dawn4 (2.1%)
Dusk3 (1.5%)

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

Road Surface

Dry136 (69.7%)
Wet23 (11.8%)
Snow20 (10.3%)
Ice/frost8 (4.1%)
Gravel6 (3.1%)
Slush2 (1.0%)

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

Vehicles & Demographics

Analysis of the 473 individuals involved in crashes shows the most represented age groups were 55-64 years old (70 people), 65 and older (68 people), and 45-54 (66 people). Among the 376 vehicles involved, the most frequent makes, after combining abbreviated names, were Chevrolet (110 vehicles), Ford (58 vehicles), and Dodge (30 vehicles).

Top Vehicle Makes (376 vehicles)

1
FORD58 (15.4%)
2
CHEVROLET57 (15.2%)
3
CHEV53 (14.1%)
4
DODG19 (5.1%)
5
CHRYSLER17 (4.5%)
6
TOYOTA13 (3.5%)
7
DODGE11 (2.9%)
8
BUICK11 (2.9%)
9
BUIC11 (2.9%)
10
HOND10 (2.7%)

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

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

Sex Distribution (336 persons with recorded sex)

Male183 (54.5%)
Female153 (45.5%)

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 frequently recorded major cause for crashes was 'Animal,' which was attributed to 30 incidents. 'Followed too close' was the second leading cause, contributing to 24 crashes. Other significant causes included 'Driving too fast for conditions' (15 crashes) and 'FTYROW: Making left turn' (13 crashes).

Major Cause

1
Animal30 (15%)
2
Followed too close24 (12%)
3
Driving too fast for conditions15 (7.5%)
4
FTYROW: Making left turn13 (6.5%)
5
FTYROW: From stop sign12 (6%)
6
Ran off road - left12 (6%)
7
Lost Control10 (5%)
8
Driver Distraction: Other interior distraction8 (4%)
9
Improper or erratic lane changing7 (3.5%)

Showing top 9 of 34 reported. 25 additional (69 total) not shown: Other (explain in narrative): Other, Ran Stop Sign, Ran Traffic Signal, FTYROW: From driveway, Made improper turn, Other (explain in narrative): No improper action, Driver Distraction: Reaching for object(s)/fallen object(s), Ran off road - straight, Swerving/Evasive Action, Improper Backing, Exceeded authorized speed, Operating vehicle in an reckless, erratic, careless, negligent manner, Cargo/equipment loss or shift, FTYROW: At uncontrolled intersection, FTYROW: From parked position, Ran off road - right, Passing: Other passing (explain in narrative), FTYROW: Making right turn on red signal, Driver Distraction: Exterior distraction, Crossed centerline (undivided), Failed to keep in proper lane, Driver Distraction: Talking on a hand-held device, Driver Distraction: Inattentive/lost in thought, Traveling wrong way or on wrong side of road, Illegally Parked/Unattended.

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 127 crashes. The second most frequent event was a collision with an animal, accounting for 27 incidents. Non-collision events like overturns (9 incidents) and collisions with fixed objects like ditches (10 incidents) were also notable.

First Harmful Event

1
Collision with: Vehicle in traffic127 (59.1%)
2
Collision with: Animal27 (12.6%)
3
Collision with: Parked motor vehicle10 (4.7%)
4
Collision with fixed object: Ditch10 (4.7%)
5
Non-collision events: Overturn/rollover9 (4.2%)
6
Collision with: Re-entering roadway5 (2.3%)
7
Collision with fixed object: Utility pole/light support5 (2.3%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)5 (2.3%)
9
Other (explain in narrative)3 (1.4%)

Showing top 9 of 19 reported. 10 additional (14 total) not shown: Collision with fixed object: Traffic sign support, Collision with: Thrown or falling object, Collision with fixed object: Mailbox, Non-collision events: Vehicle went airborne, Miscellaneous events: Hit and run, Collision with fixed object: Snow bank, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Other non-fixed object (explain in narrative), Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Building.

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

Roadway Junction / Feature

Crashes occurred more frequently at non-junction locations, which accounted for 93 incidents. Intersections were the site of 84 crashes, with four-way intersections being the most common type, hosting 58 of these incidents. An additional 10 crashes were related to driveway access.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature93 (47.7%)
2
Intersection: Four-way intersection58 (29.7%)
3
Intersection: T-intersection21 (10.8%)
4
Non-intersection: Driveway access (related, not in)10 (5.1%)
5
Non-intersection: Driveway access (within)4 (2.1%)
6
Intersection: Other intersection (explain in narrative)4 (2.1%)
7
Non-intersection: Other non-intersection (explain in narrative)3 (1.5%)
8
Intersection: L-intersection1 (0.5%)
9
Non-intersection: Alley1 (0.5%)

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 173 vehicles recorded. Four-tire light trucks (77 vehicles) and sport utility vehicles (66 vehicles) were also frequently involved. The data also includes 10 tractor/semi-trailers and 9 motorcycles among the vehicles in collisions.

Vehicle Type

"Other" combines 5 smaller categories (6 records): Cargo/panel van (2), Farm equipment (explain in narrative) (1), Truck/trailer (1), Moped (1), Single unit truck (2-axle, 6-tire) (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 at locations with no traffic controls present, a situation noted in 227 instances. Where traffic controls were a factor, crashes occurred most often at locations with traffic signals (63 instances) and stop signs (51 instances).

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 frequently damaged area, recorded in 81 cases, with an additional 80 vehicles sustaining damage to a front corner. Rear-end collisions are suggested by the 46 vehicles with primary damage to the rear. Side impacts were also common, with 69 vehicles damaged on the driver or passenger side.

Most Damaged Area

"Other" combines 9 smaller categories (82 records): Passenger side - middle (16), Rear - driver side corner (12), Rear - passenger side corner (11), Driver side - rear (10), Other (explain in narrative) (9), Top (9), Passenger side - rear (7), Non-collision/no damage (6), Cargo loss (2).

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

Crashes by City

Within Dickinson County, Spirit Lake had the highest number of crashes with 80 incidents. Milford recorded the second-highest number with 29 crashes, followed by Arnolds Park with 19. Several other municipalities, including Okoboji and Lake Park, reported crashes in the single or low double digits.

Crashes by City

1
SPIRIT LAKE80 (49.7%)
2
MILFORD29 (18%)
3
ARNOLDS PARK19 (11.8%)
4
OKOBOJI15 (9.3%)
5
LAKE PARK6 (3.7%)
6
WAHPETON5 (3.1%)
7
WEST OKOBOJI5 (3.1%)
8
SUPERIOR1 (0.6%)
9
TERRIL1 (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, 199 out of 210 for which road surface type was recorded, occurred on paved roads. Crashes on unpaved surfaces such as gravel or dirt accounted for 11 incidents, representing approximately 5.2% of that subset.

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 minority of crashes where a roadway factor was identified as a contributor, 'Surface condition (e.g. wet, icy)' was the most common, cited in 27 cases. Other factors were noted infrequently, with 'Slippery, loose or worn surface' listed in 2 cases and 'Ruts/holes/bumps' in 1 case.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)27 (77.1%)
2
Slippery, loose or worn surface2 (5.7%)
3
Ruts/holes/bumps1 (2.9%)
4
Shoulders (none, low, soft, high)1 (2.9%)
5
Traffic backup, prior crash1 (2.9%)
6
Non-highway work1 (2.9%)
7
Traffic backup, regular congestion1 (2.9%)
8
Obstruction in roadway1 (2.9%)

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

Driver Condition

Among driver conditions noted as a factor other than 'apparently normal,' being 'Under the influence of alcohol' was the most frequent, recorded in 11 instances. 'Emotional' states were cited in 5 cases, while single instances of 'Asleep/fatigued' and 'Medical condition' were also reported.

Driver Condition

1
Under the influence of alcohol11 (61.1%)
2
Emotional (e.g. depressed, angry)5 (27.8%)
3
Asleep/fatigued1 (5.6%)
4
Medical condition (seizure, reaction)1 (5.6%)

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 within the '$1,500 - $7,500' range, which applied to 150 incidents (68.5%). Fifty crashes (22.8%) resulted in damages between $7,500 and $25,000. Four crashes were estimated to have caused property damage in excess of $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 such as running off the road or overturning were the most common crash type, accounting for 68 incidents (31.1%). Rear-end collisions were the second most frequent manner of collision with 58 incidents (26.5%). Broadside crashes were also significant, occurring 32 times (14.6%).

Manner of Collision

"Other" combines 2 smaller categories (7 records): Head-on (front to front) (5), Sideswipe, opposite direction (2).

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 vehicle action was 'Movement essentially straight,' recorded in 209 instances. 'Turning left' was the second most frequent pre-crash action with 43 instances, followed by vehicles being 'Stopped in traffic' in 20 instances.

Pre-Crash Driver Action

1
Movement essentially straight209 (58.7%)
2
Turning left43 (12.1%)
3
Stopped in traffic20 (5.6%)
4
Turning right19 (5.3%)
5
Legally Parked16 (4.5%)
6
Slowing/stopping (deceleration)11 (3.1%)
7
Changing lanes8 (2.2%)
8
Backing7 (2%)
9
Other (explain in narrative)5 (1.4%)

Showing top 9 of 18 reported. 9 additional (18 total) not shown: Negotiating a curve, Leaving a parked position, Overtaking/passing, Making U-turn, Illegally Parked/Unattended, Entering a parked position, Accelerating in road, Starting in road, Entering traffic lane (merging).

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

Person Type

Of the 473 people involved in crashes, the vast majority, 447 individuals (94.5%), were drivers. The remaining individuals included 19 passengers, 4 bicyclists, and 2 pedestrians. A single 'other non-motorist' was also involved.

Person Type

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

Person Injury Severity

Among all persons involved in crashes, 4 sustained fatal injuries and 16 had serious injuries. An additional 29 people had minor injuries and 46 had possible injuries. The total number of injured persons across all crashes was 91.

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 the limited data available for safety equipment usage, 54 individuals were recorded as using a shoulder and lap belt. In 11 cases, it was noted that no safety equipment was used. Two individuals were recorded as wearing a DOT-compliant helmet.

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

Two-vehicle collisions were the most common scenario, accounting for 135 crashes, or 61.6% of the total. Single-vehicle crashes were also frequent, with 72 incidents (32.9%). Crashes involving three or more vehicles were less common, with 11 such incidents recorded in total.

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: 219
  • Total persons involved: 473
  • Total vehicles involved: 376

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

ThatCarHitMe.com · An Injuria.ai Company