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
180 CRASHES IN
IOWA, IA
2015
In 2015, Madison County recorded 180 traffic crashes, resulting in 4 fatalities and 52 injuries. The most common contributing factor cited in these incidents was the presence of an animal on the roadway, which was a factor in 50 crashes, representing 27.8% of the total.
180
Total Crash Events
4
Persons Killed
52
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, motorists accounted for all fatalities and the vast majority of injuries in Madison County crashes, with 4 motorists killed and 51 injured. Among vulnerable road users, one cyclist was reported injured. There were no pedestrian fatalities or injuries recorded during this period.
0
Cyclists Killed
4
Motorists Killed
1
Cyclists Injured
51
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 Madison County occurred most frequently on Fridays, which saw 37 incidents in 2015. The single busiest hour for crashes was 3 p.m., with 16 recorded events. Analysis of lighting conditions shows that 87 crashes happened during daylight, while 54 occurred in dark conditions and 6 took place during dawn or dusk.
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 180 total crashes, 134 (74.4%) resulted in no injuries, being classified as property-damage-only events. The remaining 46 crashes involved at least one injury or fatality. There were 4 fatal crashes recorded during this period, which resulted in a total of 4 fatalities.
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 frequently cited contributing factor in Madison County crashes was an animal on the roadway, which was noted in 50 incidents (27.8%). Following this, 'Lost Control' was a factor in 24 crashes (13.3%), and 'Driving too fast for conditions' was cited in 13 crashes (7.2%). Failure to yield the right of way from a stop sign contributed to 12 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 significant portion of crashes occurred in ideal environmental conditions, with 85 incidents (47.2%) happening in clear weather and 89 (49.4%) on dry road surfaces. Crashes during daylight hours accounted for 87 of the total 180 events. For comparison, 12 crashes occurred in snow and 13 on snowy road surfaces.
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
Among the 312 individuals involved in crashes, the 16-20 age group was the most represented with 55 people, followed by the 35-44 age group with 45 people. Analysis of the 255 vehicles involved shows Chevrolet (69 vehicles), Ford (43 vehicles), and Dodge (34 vehicles) were the most common makes recorded in crash reports.
Top Vehicle Makes (255 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
17 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (236 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 leading major cause identified in crash reports was 'Animal,' contributing to 50 incidents. 'Lost Control' was the second most common cause, cited in 24 crashes, followed by 'Driving too fast for conditions' with 13 crashes. Failure to yield the right-of-way from a stop sign was listed as the cause in 12 crashes.
Major Cause
Showing top 9 of 34 reported. 25 additional (48 total) not shown: FTYROW: From parked position, Other (explain in narrative): Other, Driver Distraction: Other interior distraction, FTYROW: From driveway, FTYROW: Making left turn, Ran Stop Sign, FTYROW: Other (explain in narrative), Failed to keep in proper lane, Passing: Where prohibited by signs/markings, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Adjusting devices (radio, climate), Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Reaching for object(s)/fallen object(s), Exceeded authorized speed, Followed too close, FTYROW: At uncontrolled intersection, Improper Backing, Driver Distraction: Other electronic device activity, Made improper turn, Passing: Other passing (explain in narrative), Passing: Through/around barrier, Driver Distraction: Exterior distraction, Ran Traffic Signal, Traveling wrong way or on wrong side of road, Equipment failure.
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 events were collisions with another vehicle in traffic (51 incidents) and collisions with an animal (50 incidents). A notable number of crashes involved a single vehicle leaving the roadway, including 19 collisions with a ditch and 16 overturns or rollovers. Collisions with parked vehicles were the first harmful event in 13 incidents.
First Harmful Event
Showing top 9 of 23 reported. 14 additional (16 total) not shown: Collision with fixed object: Mailbox, Other (explain in narrative), Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Fire hydrant, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Building, Collision with: Work zone maintenance equipment, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with: Re-entering roadway, Collision with fixed object: Traffic sign support, Collision with fixed object: Fence, Collision with: Non-motorist (see non-motorist section - NOT a unit).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
The majority of crashes, 99 in total, occurred at non-junction segments of the roadway. In contrast, 33 crashes took place at intersections, with four-way intersections being the most common type, accounting for 18 of these incidents. An additional 11 crashes were related to driveway access points.
Roadway Junction / Feature
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 105 units recorded. Light trucks and pickups were the second most frequent with 64 vehicles, followed by sport utility vehicles with 51. The data also includes 6 motorcycles and 4 tractor-trailers involved in crashes during this period.
Vehicle Type
"Other" combines 6 smaller categories (9 records): Single-unit truck (>= 3 axles) (3), Maintenance/construction vehicle (2), Other small bus (seats 9-15) (1), School bus (seats > 15) (1), Other (explain in narrative) (1), Farm tractor (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
A substantial majority of crashes, 171 in total, occurred in areas with no traffic controls present. In locations with traffic controls, stop signs were the most common device, associated with 23 crashes. An additional 12 crashes occurred where 'No Passing Zone' markings were present.
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 44 vehicles sustaining damage to the front and 31 to the front-driver side corner. Side impacts were also frequent, with 15 vehicles damaged on the driver's side middle and 12 on the passenger's side middle. Rollovers or other events resulted in top damage for 21 vehicles.
Most Damaged Area
"Other" combines 9 smaller categories (58 records): Rear - driver side corner (11), Passenger side - rear (10), Driver side - front (9), Passenger side - front (8), Rear (7), Rear - passenger side corner (6), Undercarriage (3), Other (explain in narrative) (2), Non-collision/no damage (2).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Crashes by City
Crash reports identified the location of incidents within several municipalities, with Winterset having the highest volume at 46 crashes. Following Winterset, the town of Earlham recorded 7 crashes. Other locations noted include Saint Charles and Truro, each with 3 crashes, and a portion of West Des Moines with 2 crashes.
Crashes by City
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Paved vs Unpaved Road
Analysis of the road surface type shows that 144 crashes occurred on paved roads. A notable portion, 35 crashes or approximately 19.5% of those with a recorded surface type, took place on unpaved surfaces such as gravel or dirt roads.
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 a minority of crashes, specific roadway factors were identified as contributors. The most common factor was the road surface condition, such as being wet or icy, which was cited in 29 incidents. Other noted factors included a slippery or worn surface in 2 crashes, and debris or shoulder issues in one crash each.
Roadway Contributing Factor
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
Officer-estimated property damage was most frequently assessed in the $1,500 to $7,500 range, which applied to 133 crashes. A smaller number of incidents, 41, resulted in damages estimated between $7,500 and $25,000. Three crashes were estimated to have caused property 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 crashes were the predominant manner of collision, accounting for 92 incidents, or 51.1% of the total. Among multi-vehicle crashes, broadside collisions were the most common type with 23 occurrences (12.8%). Rear-end collisions were recorded in 11 crashes, representing 6.1% of the total.
Manner of Collision
"Other" combines 2 smaller categories (6 records): Other (explain in narrative) (3), Angle, oncoming left turn (3).
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,' recorded for 146 vehicles. Other frequent actions included turning left (12 vehicles), turning right (10 vehicles), and backing (10 vehicles). Additionally, 13 vehicles were legally parked when they were struck.
Pre-Crash Driver Action
Showing top 9 of 16 reported. 7 additional (11 total) not shown: Slowing/stopping (deceleration), Making U-turn, Entering a parked position, Leaving traffic lane, Entering traffic lane (merging), Illegally Parked/Unattended, Leaving a parked position.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 312 people involved in crashes, the vast majority, 301 individuals (96.5%), were drivers. The remaining persons included 10 passengers and one bicyclist. No pedestrians were recorded as being involved in any crash 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
Among all persons involved in crashes, there were 4 fatalities recorded. An additional 52 individuals sustained injuries, which were categorized as serious (11), minor (15), or possible (26).
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 subset of participants for whom safety equipment use was recorded, 34 were noted as using a shoulder and lap belt. Ten individuals were reported as not using any safety equipment. The data also captured the use of two forward-facing child safety seats and two helmets.
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 common incident type, accounting for 108 of the 180 total crashes (60%). Two-vehicle collisions made up the next largest group with 70 incidents (38.9%). There were also two crashes involving more than two vehicles, one with three and one with four 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: 180
- Total persons involved: 312
- Total vehicles involved: 255
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