Yearly Traffic Safety Analysis

41 CRASHES IN
IOWA, IA
2015

In 2015, Pocahontas County recorded 41 traffic crashes, resulting in 0 fatalities and 17 injuries. A significant portion of these incidents, nearly 44%, involved only a single vehicle. No fatal crashes occurred during this period.

41

Total Crash Events

0

Persons Killed

17

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 17 reported injuries in Pocahontas County involved motorists, and there were no fatalities. There were no pedestrians or cyclists reported as killed or injured in traffic crashes during this period. The data indicates that all casualties were vehicle occupants.

0

Motorists Killed

17

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 Pocahontas County occurred most frequently on Wednesdays, which saw 8 incidents in 2015. The peak time for crashes was the 4 p.m. hour, with 4 separate events recorded. The majority of collisions, 28 out of 41, 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

In 2015, approximately 65.9% of crashes (27 incidents) in Pocahontas County were property-damage-only events with no injuries. The remaining 14 crashes involved injuries, including 2 with serious injuries, 7 with minor injuries, and 5 with possible injuries. There were no fatal crashes recorded during this period.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.9%
Minor Injury7minor injury crashes17.1%
Possible Injury5possible injury crashes12.2%
No Injury27no injury crashes65.9%

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 Pocahontas County crashes was 'Lost Control,' cited in 5 incidents, or 12.2% of the total. Other significant factors included 'Operating vehicle in a reckless, erratic, careless, negligent manner,' 'Failure to yield right of way from a stop sign,' and 'Ran off road - straight,' each accounting for 4 crashes (9.8%).

Officer-Reported Primary Contributing Cause

Lost Control5 (12.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (9.8%)
FTYROW: From stop sign4 (9.8%)
Ran off road - straight4 (9.8%)
Ran off road - left2 (4.9%)
FTYROW: At uncontrolled intersection2 (4.9%)
Failed to keep in proper lane2 (4.9%)
Swerving/Evasive Action2 (4.9%)
Driving too fast for conditions2 (4.9%)
Other (explain in narrative): Other2 (4.9%)

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 in 2015 occurred in ideal driving conditions, with 75.6% of incidents happening in clear weather and 73.2% on dry road surfaces. Over two-thirds of crashes (68.3%) occurred during daylight. Crashes in adverse conditions included 4 on icy or frosty roads and 3 during rain.

Weather

Clear31 (75.6%)
Cloudy5 (12.2%)
Rain3 (7.3%)
Blowing sand, soil, dirt1 (2.4%)
Blowing Snow1 (2.4%)

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

Lighting

Daylight28 (68.3%)
Dark - roadway not lighted7 (17.1%)
Dark - roadway lighted5 (12.2%)
Dawn1 (2.4%)

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

Road Surface

Dry30 (75.0%)
Ice/frost4 (10.0%)
Wet3 (7.5%)
Slush1 (2.5%)
Gravel1 (2.5%)
Snow1 (2.5%)

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

Vehicles & Demographics

Analysis of the 83 people involved in crashes shows the 35-44 and 45-54 age groups were most represented, each with 13 individuals. Among the 66 vehicles involved, Ford and Chevrolet were the most frequent makes with 15 vehicles each, followed by Dodge with 10 vehicles.

Top Vehicle Makes (66 vehicles)

1
FORD15 (22.7%)
2
CHEVROLET10 (15.2%)
3
DODGE8 (12.1%)
4
CHEV5 (7.6%)
5
PONTIAC4 (6.1%)
6
PETERBILT4 (6.1%)
7
FREIGHTLINER3 (4.5%)
8
GMC2 (3%)
9
DODG2 (3%)
10
TOYOTA1 (1.5%)

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

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

Sex Distribution (55 persons with recorded sex)

Male34 (61.8%)
Female21 (38.2%)

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

Major Cause

The primary major cause of crashes was 'Lost Control,' which was attributed to 5 incidents (12.2%). This was followed by three other causes, each accounting for 4 crashes (9.8%): 'Operating vehicle in a reckless, erratic, careless, negligent manner,' 'Failure to yield right of way from a stop sign,' and 'Ran off road - straight.'

Major Cause

1
Lost Control5 (12.5%)
2
Operating vehicle in an reckless, erratic, careless, negligent manner4 (10%)
3
FTYROW: From stop sign4 (10%)
4
Ran off road - straight4 (10%)
5
Ran off road - left2 (5%)
6
FTYROW: At uncontrolled intersection2 (5%)
7
Failed to keep in proper lane2 (5%)
8
Swerving/Evasive Action2 (5%)
9
Driving too fast for conditions2 (5%)

Showing top 9 of 20 reported. 11 additional (13 total) not shown: Other (explain in narrative): Other, Animal, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Reaching for object(s)/fallen object(s), FTYROW: From parked position, Improper Backing, Made improper turn, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed, Ran Stop Sign, Traveling wrong way or on wrong side of road.

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 17 crashes, representing 41.5% of the total. Non-collision events like 'Overturn/rollover' accounted for 6 incidents. Collisions with animals were cited as the first harmful event in 2 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic17 (48.6%)
2
Non-collision events: Overturn/rollover6 (17.1%)
3
Collision with: Parked motor vehicle5 (14.3%)
4
Collision with: Animal2 (5.7%)
5
Collision with fixed object: Utility pole/light support1 (2.9%)
6
Collision with fixed object: Other post/pole/support (explain in narrative)1 (2.9%)
7
Collision with fixed object: Curb/island/raised median1 (2.9%)
8
Miscellaneous events: Fire/explosion1 (2.9%)
9
Collision with fixed object: Culvert/pipe opening1 (2.9%)

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 19 incidents (46.3%) happening on non-junction road segments. Four-way intersections were the most common junction type for collisions, accounting for 13 crashes (31.7%). An additional 3 crashes occurred at driveway access points.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature19 (46.3%)
2
Intersection: Four-way intersection13 (31.7%)
3
Non-intersection: Driveway access (within)3 (7.3%)
4
Non-intersection: Driveway access (related, not in)2 (4.9%)
5
Non-intersection: Alley1 (2.4%)
6
Intersection: L-intersection1 (2.4%)
7
Intersection: Y-intersection1 (2.4%)
8
Interchange-related: Other interchange (explain in narrative)1 (2.4%)

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

Vehicle Type

Light trucks, including pickups and panel trucks, were the most common vehicle type involved in crashes, accounting for 22 of the 66 vehicles (33.3%). Passenger cars were the second most frequent with 19 vehicles (28.8%). Notably, tractor/semi-trailers were involved in 12 instances, representing 18.2% of all vehicles in crashes.

Vehicle Type

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

Traffic Control Device

The data shows that for a large majority of vehicles involved in crashes, no traffic controls were present. This was the case for 55 out of 66 vehicles (83.3%). Stop signs were the most common form of traffic control noted, present for 7 of the vehicles involved in collisions.

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 vehicle damage, with 'Front - driver side corner' (11 vehicles) and 'Front' (9 vehicles) being the most cited locations. Side impacts were also frequent, with 'Driver side - middle' damage recorded for 8 vehicles. Damage to the 'Rear' of the vehicle was noted for 4 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (16 records): Passenger side - front (4), Driver side - front (2), Front - passenger side corner (2), Other (explain in narrative) (2), Rear - driver side corner (2), Undercarriage (1), Rear - passenger side corner (1), Non-collision/no damage (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 Pocahontas County, the city of Pocahontas had the highest crash volume with 8 incidents reported in 2015. The town of Laurens followed with 5 crashes, and Rolfe recorded 3 crashes. A significant number of the county's crashes occurred outside of any incorporated city limits.

Crashes by City

1
POCAHONTAS8 (50%)
2
LAURENS5 (31.3%)
3
ROLFE3 (18.8%)

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, 37 out of 41, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt roads accounted for 4 incidents, representing 9.8% 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 - $7,500' range, which applied to 25 crashes, or 61% of the total. High-damage crashes, with estimates of '$25,000 or more,' accounted for 6 incidents (14.6%). An additional 8 crashes fell into the '$7,500 - $25,000' damage category.

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 crash type, accounting for 18 incidents or 43.9% of all crashes in 2015. Among multi-vehicle collisions, broadside crashes were the most common, with 7 incidents (17.1%), followed by same-direction sideswipes with 6 incidents (14.6%).

Manner of Collision

"Other" combines 1 smaller categories (1 records): Sideswipe, opposite direction (1).

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

Pre-Crash Driver Action

The most common pre-crash action for vehicles was 'Movement essentially straight,' which was reported for 38 of the 66 vehicles involved (57.6%). The next most frequent actions were vehicles being 'Legally Parked' (7 vehicles) and 'Turning left' (6 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight38 (57.6%)
2
Legally Parked7 (10.6%)
3
Turning left6 (9.1%)
4
Turning right4 (6.1%)
5
Backing3 (4.5%)
6
Overtaking/passing3 (4.5%)
7
Stopped in traffic2 (3%)
8
Leaving traffic lane1 (1.5%)
9
Negotiating a curve1 (1.5%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Other (explain in narrative).

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

Person Type

Of the 83 individuals involved in crashes, the vast majority were drivers, accounting for 80 people or 96.4% of the total. Passengers made up the remaining 3 individuals. No pedestrians or cyclists were recorded in any crash reports for the year.

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 17 people sustained injuries in crashes, representing 20.5% of all individuals involved. Of those injured, 2 suffered serious injuries, 7 had minor injuries, and 8 had possible injuries. No fatalities were recorded among the 83 people 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

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 23 of the 41 crashes (56.1%). Single-vehicle crashes were also frequent, with 17 incidents representing 41.5% of the total. One crash 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: 41
  • Total persons involved: 83
  • Total vehicles involved: 66

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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