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CRASH INTELLIGENCE REPORT · IOWA, IA · 2015
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2015-annual-report
Yearly Traffic Safety Analysis
184 CRASHES IN
IOWA, IA
2015
In 2015, Grundy County recorded 184 traffic crashes, resulting in 0 fatalities and 65 injuries. A significant portion of these incidents were attributed to a single cause, with collisions involving animals accounting for nearly 40% of all crashes.
184
Total Crash Events
0
Persons Killed
65
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, there were no fatalities among motorists, pedestrians, or cyclists. All 65 reported injuries were sustained by motorists involved in crashes. No pedestrians or cyclists were recorded as being killed or injured during this period.
0
Motorists Killed
65
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 Grundy County peaked on Thursdays, with 34 incidents, and during the 5 p.m. hour, which saw 21 crashes. A notable seasonal trend was observed, with a sharp increase in crashes during November, which recorded 42 incidents, more than double the monthly average. While 78 crashes occurred in daylight, 36 took place in dark or dusk conditions.
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
There were no fatal crashes recorded in 2015. The majority of incidents, 138 crashes or 75%, resulted in no injuries and were classified as property-damage-only. The remaining 46 crashes (25%) involved injuries, including 4 serious injury crashes, 20 minor injury crashes, and 22 possible injury crashes.
Outcome by Severity (Crash Events)
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 significant contributing factor to crashes was animals on the roadway, cited in 73 incidents, which is 39.7% of all crashes. Other leading factors included drivers losing control (26 crashes, 14.1%), running off a straight road (13 crashes, 7.1%), and failure to yield the right-of-way from a stop sign (11 crashes, 6%).
Officer-Reported Primary Contributing Cause
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 total of 78 crashes occurred in daylight on dry road surfaces, and 74 took place in clear weather. Adverse conditions were also a factor in some incidents, with 18 crashes occurring on snow-covered roads and 12 during snowy weather. Additionally, 24 crashes happened on dark, unlighted roadways.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes, after consolidating abbreviated names, were Chevrolet (46), Ford (36), and Toyota (19). Analysis of person demographics shows the 26-34 age group was most frequently involved in crashes (56 people), followed closely by the 16-20 age group (49 people).
Top Vehicle Makes (241 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (222 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Major Cause
Collisions involving an animal were the leading major cause of crashes, cited in 73 incidents. The next most common causes were drivers losing control, which accounted for 26 crashes, and running off a straight portion of the road, which was cited in 13 crashes.
Major Cause
Showing top 9 of 27 reported. 18 additional (30 total) not shown: Driver Distraction: Inattentive/lost in thought, Driver Distraction: Talking on a hand-held device, Ran off road - right, Driver Distraction: Exterior distraction, FTYROW: Making left turn, Swerving/Evasive Action, Driver Distraction: Passenger, Ran Stop Sign, FTYROW: Other (explain in narrative), Driver Distraction: Other interior distraction, Driving less than the posted speed limit, Failed to keep in proper lane, Followed too close, FTYROW: At uncontrolled intersection, Illegally Parked/Unattended, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed, Passing: With insufficient distance/inadequate visibility.
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 an animal, which initiated 73 crashes. A collision with another vehicle in traffic was the second most common event, occurring in 46 incidents, followed by non-collision rollovers, which accounted for 20 crashes.
First Harmful Event
Showing top 9 of 22 reported. 13 additional (14 total) not shown: Collision with: Parked motor vehicle, Miscellaneous events: Hit and run, Non-collision events: Jackknife, Non-collision events: Vehicle went airborne, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Building, Collision with fixed object: Guardrail - face, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Tree, Collision with fixed object: Utility pole/light support, Collision with fixed object: Wall, Collision with: Re-entering roadway.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
The majority of crashes, 68 incidents, occurred at non-junction locations rather than at intersections. Of the 37 crashes that did happen at intersections, most (23) were at four-way intersections, while 11 occurred at T-intersections.
Roadway Junction / Feature
Showing top 9 of 10 reported. 1 additional (1 total) not shown: Intersection: Other intersection (explain in narrative).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Vehicle Type
Passenger cars were the predominant vehicle type involved, accounting for 128 of the 241 vehicles in crashes. Sport utility vehicles (35 vehicles) and four-tire light trucks or pickups (34 vehicles) were the next most common types. Six tractor-trailers and two motorcycles were also involved in crashes.
Vehicle Type
"Other" combines 7 smaller categories (10 records): Cargo/panel van (2), Motorcycle (2), Farm tractor (2), Farm equipment (explain in narrative) (1), Maintenance/construction vehicle (1), Moped (1), Other bus (seats > 15) (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
A significant majority of crashes, 123 incidents, occurred in areas where no traffic controls were present. For crashes where a control was present, stop signs were the most common type, associated with 32 incidents.
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 type of vehicle damage, with the primary damage area being the front for 36 vehicles and the front corners for another 31 vehicles. Rear-end damage was the primary point of impact for 16 vehicles, while side damage was most prominent on 15 vehicles.
Most Damaged Area
"Other" combines 9 smaller categories (47 records): Rear - driver side corner (9), Driver side - front (8), Passenger side - rear (6), Driver side - rear (6), Passenger side - middle (6), Other (explain in narrative) (5), Rear - passenger side corner (4), 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
Within Grundy County, the highest number of crashes were reported in or near the city of Grundy Center, with 17 incidents. The city of Dike recorded the second-highest volume with 15 crashes, followed by Conrad and Reinbeck with 5 crashes each.
Crashes by City
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, 166 out of 184, occurred on paved roadways. Eighteen crashes, representing 9.8% of the total for the year, took place on unpaved gravel or dirt road surfaces.
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 a contributor, adverse surface conditions such as wet or icy pavement were the most common, cited in 16 crashes. Other factors, such as ruts or a work zone, were each cited in only one crash.
Roadway Contributing Factor
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, 6 were identified as asleep or fatigued. Additionally, 3 drivers were noted as being under the influence of alcohol, and 1 had a medical condition such as a seizure.
Driver Condition
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
The most common estimated cost of property damage fell within the $1,500 to $7,500 range, accounting for 133 crashes (72.3%). Forty-three crashes resulted in damage between $7,500 and $25,000, while 7 crashes involved 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
Single-vehicle, non-collision events were the dominant crash type, comprising 98 incidents or 53.3% of all crashes. Among multi-vehicle crashes, rear-end collisions were the most frequent with 21 incidents, followed by broadside collisions with 18 incidents.
Manner of Collision
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Pre-Crash Driver Action
The most common action of vehicles immediately prior to a crash was moving straight, which was the case for 127 vehicles. The next most frequent pre-crash maneuvers were turning left (14 vehicles) and being legally parked (11 vehicles).
Pre-Crash Driver Action
Showing top 9 of 15 reported. 6 additional (7 total) not shown: Other (explain in narrative), Leaving a parked position, Starting in road, Illegally Parked/Unattended, Changing lanes, Leaving traffic lane.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 306 individuals involved in crashes, the overwhelming majority, 295 people (96.4%), were drivers. The remaining 11 individuals (3.6%) were vehicle passengers. No other person types were recorded.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Across all 306 people involved in crashes, 65 individuals sustained an injury. This included 4 serious injuries, 23 minor injuries, and 38 possible injuries. No fatalities were recorded among any of the involved persons.
Person Injury Severity
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
In the limited sample of 61 vehicle occupants for whom safety equipment use was documented, 54 were reported to have used a shoulder and lap belt. Six occupants were recorded as having used no safety equipment at the time of the crash.
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 prevalent type, accounting for 129 of the 184 total incidents (70.1%). Crashes involving two vehicles numbered 53 (28.8%), and there were two crashes that 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 10, 2026
Data Coverage
- Reporting period: 2015-01-01 through 2015-12-31 (365 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 184
- Total persons involved: 306
- Total vehicles involved: 241
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 10, 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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2015-01-01 – 2015-12-31
Generated: September 10, 2026 · All rights reserved