ThatCarHitMe.com
An Injuria.ai Company
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
978 CRASHES IN
IOWA, IA
2015
In 2015, Cerro Gordo County recorded 978 motor vehicle crashes, resulting in 7 fatalities and 265 injuries. A significant portion of these incidents were single-vehicle crashes, accounting for 25.3% of all collisions. The most frequently cited contributing factor was collisions with animals, which were noted in 154 crashes, representing 15.7% of the total.
978
Total Crash Events
7
Persons Killed
265
Persons Injured
6
Fatal Crash Events
Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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
Motor vehicle occupants represented all 7 fatalities and the vast majority of injuries, with 254 motorists injured in 2015. While there were no fatalities among vulnerable road users, 4 pedestrians and 7 cyclists sustained injuries. These incidents highlight the risks faced by all road users in the county.
0
Pedestrians Killed
0
Cyclists Killed
7
Motorists Killed
4
Pedestrians Injured
7
Cyclists Injured
254
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 Cerro Gordo County peaked on Fridays, which saw 200 incidents in 2015. The most common time for crashes was the 4 p.m. hour, with 92 events, followed closely by the 5 p.m. hour with 87 events, indicating a strong correlation with the evening commute. Analysis of lighting conditions shows that a majority of crashes, 614 in total, 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, 771 out of 978 (78.8%), resulted in no injuries. Crashes involving injuries accounted for 20.6% of the total, with severities ranging from possible (126 crashes) to serious (12 crashes). There were 6 fatal crashes recorded, which resulted in a total of 7 fatalities, underscoring that a single crash event can lead to multiple deaths.
Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.
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
Collisions involving an animal were the leading contributing factor in crashes, accounting for 154 incidents or 15.7% of the total. Other significant factors included following too closely (75 crashes), failure to yield the right-of-way from a stop sign (68 crashes), and driving too fast for conditions (66 crashes). Driver distraction was also a notable contributor, with 'inattentive/lost in thought' and 'other interior distraction' combining for 59 crashes.
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 majority of crashes occurred in ideal driving conditions, with 62.8% (614 crashes) happening in daylight and 58.0% (567 crashes) on dry road surfaces. Clear weather was reported for 506 incidents. Adverse conditions still played a role, with 113 crashes on wet roads and 139 crashes on roads affected by snow, ice, or slush.
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 analysis of persons involved in crashes shows the highest representation among older age groups, with the 55-64 age bracket accounting for 302 individuals and the 65+ bracket for 297. Among the 1,720 vehicles involved, Ford was the most frequent make with 319 vehicles. Chevrolet (including 'CHEV' and 'CHEVROLET' variants) was also prominent, with a combined total of 391 vehicles, followed by Dodge with 125 vehicles.
Top Vehicle Makes (1,720 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
153 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,528 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
The primary causes of crashes, as coded by the Iowa DOT, point to specific driver behaviors and environmental factors. Collisions with animals were the single largest cause, cited in 154 incidents. Driver errors followed, including 'Followed too close' (75 crashes), 'Failure to Yield from a stop sign' (68 crashes), and 'Driving too fast for conditions' (66 crashes).
Major Cause
Showing top 9 of 49 reported. 40 additional (331 total) not shown: Driver Distraction: Other interior distraction, Lost Control, Driver Distraction: Inattentive/lost in thought, Ran Stop Sign, Ran off road - straight, FTYROW: From driveway, FTYROW: From yield sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Improper or erratic lane changing, FTYROW: At uncontrolled intersection, Improper Backing, Failed to keep in proper lane, Other (explain in narrative): No improper action, FTYROW: Other (explain in narrative), Driver Distraction: Exterior distraction, Driver Distraction: Reaching for object(s)/fallen object(s), Crossed centerline (undivided), Passing: Other passing (explain in narrative), Swerving/Evasive Action, Traveling wrong way or on wrong side of road, Driver Distraction: Manual operation of an electronic communication device, Ran off road - right, FTYROW: From parked position, Exceeded authorized speed, Other (explain in narrative): Vision obstructed, Other (explain in narrative): Disregarded signs/road markings, FTYROW: Making right turn on red signal, Driver Distraction: Adjusting devices (radio, climate), Improper Starting, Driver Distraction: Passenger, FTYROW: To pedestrian, Passing: Through/around barrier, Cargo/equipment loss or shift, Driver Distraction: Talking on a hands free device, Illegally Parked/Unattended, Aggressive driving/road rage, Operator inexperience, Passing: With insufficient distance/inadequate visibility, Disregarded RR Signal, Separation of units.
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 606 of the 978 crashes. The second most frequent event was a collision with an animal, accounting for 150 incidents. Run-off-road events were also common, with crashes involving a ditch (29), a utility pole (9), or a traffic sign support (7) as the first harmful event.
First Harmful Event
Showing top 9 of 32 reported. 23 additional (69 total) not shown: Collision with fixed object: Traffic sign support, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Guardrail - face, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Tree, Non-collision events: Other non-collision (explain in narrative), Non-collision events: Jackknife, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fence, Collision with fixed object: Fire hydrant, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Traffic signal support, Collision with fixed object: Cable barrier, Collision with fixed object: Building, Collision with: Work zone maintenance equipment, Other (explain in narrative), Non-collision events: Fell/jumped from vehicle, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Railway vehicle/train, Collision with fixed object: Embankment, Non-collision events: Vehicle went airborne, Collision with fixed object: Bridge overhead structure.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
Crashes were most likely to occur on non-intersection road segments, which accounted for 417 incidents. Four-way intersections were the second most common location, with 265 crashes recorded. Driveway-related incidents, both within and near driveways, contributed to a combined 50 crashes, while T-intersections were the site of 45 crashes.
Roadway Junction / Feature
Showing top 9 of 18 reported. 9 additional (20 total) not shown: Non-intersection: Railroad grade crossing, Interchange-related: Off-ramp, Interchange-related: On-ramp merge area, Intersection: Y-intersection, Interchange-related: Other interchange (explain in narrative), Interchange-related: Mainline, between ramps, Non-intersection: Crossover-related, Intersection: Five points or more, Interchange-related: Off-ramp, diverge area.
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 826 of the 1,720 total vehicles. Sport utility vehicles (338) and four-tire light trucks or pickups (277) were also frequently involved. Commercial vehicles like tractor/semi-trailers were involved in 44 crashes, while motorcycles were involved in 11.
Vehicle Type
"Other" combines 15 smaller categories (48 records): Motorcycle (11), Single unit truck (2-axle, 6-tire) (11), Passenger van (seats 9-15) (5), Truck/trailer (4), Moped (3), Other bus (seats > 15) (2), School bus (seats > 15) (2), Farm tractor (2), Farm equipment (explain in narrative) (2), Other (explain in narrative) (1), Maintenance/construction vehicle (1), Motor home/recreational vehicle (1), Small school bus (seats 9-15) (1), Train (1), Other light truck (<=10000 lbs) (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
Analysis of traffic controls present at crash locations shows that for a majority of vehicles involved, no controls were present (872 of 1,720 vehicles). Where traffic controls were a factor, traffic signals were most common, being present for 425 vehicles. Stop signs were the next most frequent control device, present for 213 vehicles involved in collisions.
Traffic Control Device
"Other" combines 4 smaller categories (5 records): Flashing traffic control signal (2), No Passing Zone (marked) (1), Warning sign (1), Work zone sign (1).
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 impact, recorded in 431 instances. This aligns with the high number of rear-end collisions, which is further supported by the 220 vehicles damaged in the rear. Side impacts were also significant, with 114 vehicles sustaining damage to the driver-side middle and 89 to the passenger-side middle.
Most Damaged Area
"Other" combines 9 smaller categories (341 records): Passenger side - front (81), Driver side - rear (63), Rear - driver side corner (54), Passenger side - rear (50), Rear - passenger side corner (38), Top (22), Other (explain in narrative) (21), Non-collision/no damage (8), Undercarriage (4).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Impairment (Alcohol / Drugs)
Impairment was suspected in a subset of crashes, with alcohol being the factor in 22 instances and drugs in 3. These incidents correspond to 19 crashes officially coded as DUI-related, representing 1.9% of all crashes in the county. It is important to note that impairment is often under-reported, so these figures should be considered a minimum.
Crashes by City
Within Cerro Gordo County, Mason City recorded the highest number of incidents with 608 crashes, followed by Clear Lake with 121. Other municipalities such as Ventura and Rockwell reported 12 and 7 crashes respectively. Notably, 221 crashes occurred in unincorporated areas of the county, outside of any city's jurisdiction.
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 overwhelming majority of crashes, 949 in total, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt roads accounted for 25 incidents, representing approximately 2.6% of crashes where the road surface type was specified. This reflects the prevalence of paved infrastructure where most traffic volume is concentrated.
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 identified as a contributor, poor surface condition (such as wet or icy roads) was the leading issue, cited in 119 crashes. Work zones were a contributing factor in 7 crashes, as was a slippery, loose, or worn road surface. Debris in the roadway and traffic backups each contributed to 3 crashes.
Roadway Contributing Factor
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Driver Condition
While most drivers were recorded as 'apparently normal,' several other conditions were noted as potential factors. Driving under the influence of alcohol was the most cited condition with 25 drivers, followed by 16 drivers who were noted as asleep or fatigued. An emotional state, such as being depressed or angry, was recorded for 11 drivers involved in crashes.
Driver Condition
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 to $7,500 range, which applied to 739 incidents. A smaller but significant number of crashes, 193, resulted in damages estimated between $7,500 and $25,000. High-damage crashes, with costs exceeding $25,000, accounted for 19 incidents, or approximately 1.9% of the total.
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 frequent type of crash, accounting for 247 incidents (25.3%). Rear-end collisions were a close second, with 231 crashes (23.6%). Broadside, or front-to-side, collisions were the third most common manner of collision, occurring in 181 cases (18.5%).
Manner of Collision
"Other" combines 3 smaller categories (44 records): Head-on (front to front) (23), Sideswipe, opposite direction (17), Rear to rear (4).
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 moving essentially straight, which was the case for 939 of the 1,720 vehicles involved. Turning left was the second most frequent action, recorded for 178 vehicles. Additionally, 118 vehicles were stopped in traffic at the time of the collision.
Pre-Crash Driver Action
Showing top 9 of 19 reported. 10 additional (48 total) not shown: Starting in road, Entering traffic lane (merging), Leaving traffic lane, Negotiating a curve, Overtaking/passing, Leaving a parked position, Entering a parked position, Accelerating in road, Illegally Parked/Unattended, Making U-turn.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Pedestrian/Cyclist Action
For the 11 pedestrians and cyclists involved in crashes, the most common action was entering or crossing the roadway, which was recorded in 6 instances. Three individuals were moving along the roadway with the flow of traffic. One was moving along the roadway against traffic.
Pedestrian/Cyclist Action
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Non-motorist records linked to crash events
Person Type
Of the 2,001 individuals involved in crashes, the vast majority were drivers, accounting for 1,927 people or 96.3% of the total. Passengers made up a smaller portion with 63 individuals. Vulnerable road users included 7 bicyclists and 4 pedestrians.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Across all 2,001 people involved in crashes, 7 individuals sustained fatal injuries and 265 sustained non-fatal injuries. The majority of injuries were classified as 'Possible' (173 people) or 'Minor' (78 people), while 14 people suffered serious injuries. In total, 13.6% of all persons involved in crashes were either injured or killed.
Person Injury Severity
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
Among the limited sample where safety equipment use was recorded, 170 individuals were noted as using a shoulder and lap belt. Fifteen individuals were recorded as using no safety equipment. While the data is not comprehensive for all participants, of those with a recorded status, 7.9% were not using any form of restraint.
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
The most common type of crash involved two vehicles, accounting for 632 incidents. Single-vehicle crashes were also frequent, with 298 incidents representing 30.5% of the total. While most multi-vehicle crashes involved three vehicles (42 incidents), a few larger pile-ups were recorded, including two crashes involving six vehicles and one involving seven 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: 978
- Total persons involved: 2,001
- Total vehicles involved: 1,720
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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2015-01-01 – 2015-12-31
Generated: September 9, 2026 · All rights reserved