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
1,080 CRASHES IN
IOWA, IA
2015
In 2015, Dallas County recorded 1,080 traffic crashes, resulting in 4 fatalities and 333 injuries. These incidents involved 1,872 vehicles and 2,216 people. A notable finding from the data is that collisions with animals were the single most common contributing factor, cited in 178 crashes, representing 16.5% of the total.
1,080
Total Crash Events
4
Persons Killed
333
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
Motorists comprised the vast majority of casualties, with 3 individuals killed and 322 injured in 2015. One pedestrian was killed and 5 others were injured. While no cyclists were killed, 6 sustained injuries. These figures highlight the risks faced by all road users, particularly vulnerable pedestrians and cyclists.
1
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
5
Pedestrians Injured
6
Cyclists Injured
322
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 frequency in Dallas County peaked on Wednesdays, which saw 181 incidents over the year. The most hazardous time of day was the 5 p.m. hour, with 125 crashes, indicating a strong correlation with the evening commute. Overall, a majority of crashes, 671 or 62.1%, 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, 835 incidents or 77.3%, resulted in no injuries. Injury-involved crashes accounted for 22.3% of the total, comprising 23 serious injury, 85 minor injury, and 133 possible injury crashes. Four separate crashes were fatal, leading to a total of 4 fatalities recorded for the year.
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 leading contributing factor identified in crashes was the presence of an animal on the roadway, accounting for 178 incidents (16.5%). Following this, driver behaviors such as following too closely (152 crashes, 14.1%) and driving too fast for conditions (85 crashes, 7.9%) were the next most common causes. Failure to yield the right-of-way from a stop sign was a factor in 64 crashes (5.9%).
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 favorable conditions, with 62.1% (671 crashes) happening in daylight, 61.8% (667 crashes) on dry road surfaces, and 51.9% (561 crashes) in clear weather. Adverse weather was a factor in a smaller share of incidents, with 79 crashes occurring during rain and 75 during snow. Wet road surfaces were present in 125 crashes, while snow or ice was a factor in 130 incidents.
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 persons involved in crashes, the 26-34 age group was the most represented, with 411 individuals, followed by the 35-44 age group with 362 individuals. Analysis of the 1,872 vehicles involved shows that Chevrolet (335 vehicles) and Ford (308 vehicles) were the most frequent makes. Toyota and Dodge vehicles were each involved in 130 crashes.
Top Vehicle Makes (1,872 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
100 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,714 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 reported cause for crashes in Dallas County was an animal in the roadway, cited in 178 incidents (16.5%). Driver error followed, with 'followed too close' listed in 152 crashes (14.1%) and 'driving too fast for conditions' in 85 crashes (7.9%). 'Failure to yield right-of-way from a stop sign' was the major cause in 64 crashes (5.9%).
Major Cause
Showing top 9 of 49 reported. 40 additional (305 total) not shown: Ran Traffic Signal, Driver Distraction: Other interior distraction, Operating vehicle in an reckless, erratic, careless, negligent manner, Swerving/Evasive Action, FTYROW: Other (explain in narrative), Improper or erratic lane changing, Ran Stop Sign, Driver Distraction: Inattentive/lost in thought, Other (explain in narrative): No improper action, FTYROW: From yield sign, Exceeded authorized speed, FTYROW: At uncontrolled intersection, Failed to keep in proper lane, Passing: Other passing (explain in narrative), Driver Distraction: Exterior distraction, Improper Backing, Made improper turn, FTYROW: From driveway, Other (explain in narrative): Vision obstructed, FTYROW: From parked position, Driver Distraction: Adjusting devices (radio, climate), Aggressive driving/road rage, Driver Distraction: Talking on a hand-held device, Driver Distraction: Passenger, Passing: Through/around barrier, Passing: Where prohibited by signs/markings, Other (explain in narrative): Illegal off-road driving, Failed to yield to emergency vehicle, Driver Distraction: Reaching for object(s)/fallen object(s), Illegally Parked/Unattended, Passing: With insufficient distance/inadequate visibility, Ran off road - right, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Unrestrained animal, Crossed centerline (undivided), Cargo/equipment loss or shift, FTYROW: To pedestrian, Failure to signal intentions, Equipment failure, Operator inexperience.
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 634 crashes, or 58.7% of the total. The second most frequent event was a collision with an animal, accounting for 175 incidents (16.2%). Collisions with fixed objects like cable barriers (45 crashes), ditches (35 crashes), and utility poles (18 crashes) were also significant.
First Harmful Event
Showing top 9 of 37 reported. 28 additional (86 total) not shown: Collision with fixed object: Traffic sign support, Other (explain in narrative), Collision with fixed object: Tree, Collision with: Other non-fixed object (explain in narrative), Non-collision events: Jackknife, Collision with fixed object: Bridge/bridge rail parapet, Non-collision events: Other non-collision (explain in narrative), Collision with: Work zone maintenance equipment, Collision with fixed object: Guardrail - face, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Embankment, Collision with fixed object: Fire hydrant, Collision with fixed object: Mailbox, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Re-entering roadway, Collision with: Thrown or falling object, Collision with fixed object: Bridge pier or support, Miscellaneous events: Hit and run, Non-collision events: Vehicle went airborne, Miscellaneous events: Vehicle out of gear/rolled, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Snow bank, Collision with fixed object: Fence, Collision with fixed object: Ground, Non-collision events: Fell/jumped from vehicle.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
Nearly half of all crashes, 527 incidents or 48.8%, occurred at non-junction locations along a roadway. Four-way intersections were the most common type of junction for crashes, accounting for 239 incidents (22.1%). T-intersections were the site of 64 crashes, representing 5.9% of the total.
Roadway Junction / Feature
Showing top 9 of 23 reported. 14 additional (39 total) not shown: Intersection: Intersection with ramp, Interchange-related: On-ramp merge area, Non-intersection: Alley, Non-intersection: Driveway access (within), Interchange-related: Off-ramp, diverge area, Intersection: Five points or more, Intersection: Roundabout, Interchange-related: On-ramp, Intersection: Y-intersection, Non-intersection: Railroad grade crossing, Interchange-related: Other interchange (explain in narrative), Non-intersection: Bike lanes, Intersection: Shared use path or trail, Intersection: Traffic circle.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Vehicle Type
Of the 1,872 vehicles involved in crashes, passenger cars were the most common type, accounting for 909 vehicles (48.6%). Sport utility vehicles were the next most frequent with 440 vehicles (23.5%), followed by four-tire light trucks and pickups at 267 vehicles (14.3%). Tractor-trailers were involved in 57 crashes (3.0%) and motorcycles in 15 crashes (0.8%).
Vehicle Type
"Other" combines 12 smaller categories (39 records): Single-unit truck (>= 3 axles) (15), Single unit truck (2-axle, 6-tire) (9), School bus (seats > 15) (5), Other small bus (seats 9-15) (2), Passenger van (seats 9-15) (1), Motor home/recreational vehicle (1), Other (explain in narrative) (1), Farm tractor (1), Farm equipment (explain in narrative) (1), Truck tractor (bobtail) (1), Maintenance/construction vehicle (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
For vehicles involved in crashes, the majority (56.1% or 1,050 vehicles) were in areas with no traffic controls present. Where controls were present, traffic signals were the most common, governing 434 vehicles (23.2%). Stop signs were a factor for 166 vehicles (8.9%) involved in collisions.
Traffic Control Device
"Other" combines 6 smaller categories (12 records): No Passing Zone (marked) (4), Railway crossing device (2), Inoperative (not functioning properly) (2), School zone signs (2), Traffic sign missing (1), Warning sign (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Most Damaged Area
Analysis of vehicle damage points shows that frontal impacts were the most common, with the primary damage area being the front for 521 vehicles and front corners for another 266 vehicles. Rear impacts were the next most frequent, with 319 vehicles sustaining primary damage to the rear, which is consistent with the high number of reported rear-end collisions.
Most Damaged Area
"Other" combines 10 smaller categories (340 records): Passenger side - rear (65), Passenger side - front (58), Rear - passenger side corner (55), Driver side - rear (55), Rear - driver side corner (42), Top (36), Other (explain in narrative) (13), Undercarriage (8), Non-collision/no damage (7), Cargo loss (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Impairment (Alcohol / Drugs)
Impairment was a factor in 28 crashes, representing 2.6% of all incidents in 2015. Among the 23 drivers specifically identified as impaired, alcohol was the sole factor for 21 individuals. One driver was impaired by drugs, and another by a combination of alcohol and drugs.
Crashes by City
Crash distribution within the county was concentrated in its larger municipalities. West Des Moines recorded the highest volume with 277 crashes, followed by Waukee with 193. Other cities with significant crash counts include Perry (74), Adel (54), and Clive (47).
Crashes by City
Showing top 9 of 15 reported. 6 additional (31 total) not shown: DALLAS CENTER, GRIMES, VAN METER, REDFIELD, DEXTER, DAWSON.
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, 1,021 incidents, occurred on paved roadways. A smaller but notable number of crashes, 53 incidents or 4.9% of the total where surface type was recorded, 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
Among crashes where a roadway factor was cited, adverse surface conditions such as wet or icy roads were the leading contributor, noted in 116 incidents. Work zones were identified as a roadway-related factor in 15 crashes. Other less frequent factors included debris on the roadway (3 crashes) and slippery or worn surfaces (6 crashes).
Roadway Contributing Factor
Showing top 9 of 11 reported. 2 additional (2 total) not shown: Traffic backup, regular congestion, Traffic control obscured.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Driver Condition
In cases where a driver's condition was noted as other than 'apparently normal,' being under the influence of alcohol was the most frequent, recorded for 31 drivers. Emotional state, such as anger or depression, was noted for 14 drivers, while fatigue or falling asleep was a factor for 12 drivers. A medical condition was cited for 10 drivers.
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 most crashes fell into the $1,500 to $7,500 range, which accounted for 756 incidents (70.0%). A smaller number of crashes resulted in higher damage, with 277 (25.6%) estimated between $7,500 and $25,000, and 21 crashes (1.9%) exceeding $25,000 in damages.
Property Damage
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Manner of Collision
The most frequent crash types were non-collision single-vehicle incidents, such as running off the road, which accounted for 333 crashes (30.8%), and rear-end collisions, which numbered 314 (29.1%). Broadside collisions were the third most common manner of collision, occurring in 155 incidents (14.4%).
Manner of Collision
"Other" combines 3 smaller categories (30 records): Head-on (front to front) (14), Sideswipe, opposite direction (11), Rear to rear (5).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Pre-Crash Driver Action
Of the 1,872 vehicles involved in crashes, a majority (1,081 vehicles or 57.7%) were moving straight ahead just prior to the collision. Other common pre-crash actions included slowing or stopping (144 vehicles), turning left (140 vehicles), and being stopped in traffic (128 vehicles).
Pre-Crash Driver Action
Showing top 9 of 18 reported. 9 additional (59 total) not shown: Overtaking/passing, Negotiating a curve, Illegally Parked/Unattended, Entering traffic lane (merging), Accelerating in road, Making U-turn, Leaving a parked position, Starting in road, Leaving traffic lane.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Pedestrian/Cyclist Action
Among the 12 pedestrians and cyclists involved in crashes, the most common action at the time of the collision was entering or crossing the roadway, which was reported for 7 individuals. Two individuals were moving along the roadway with traffic when the crash occurred.
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 2,216 people involved in crashes, the overwhelming majority were drivers, accounting for 2,133 individuals (96.3%). Passengers made up 71 of the total persons involved. A small fraction consisted of vulnerable road users, with 6 pedestrians and 6 cyclists involved in incidents.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Among all 2,216 people involved in crashes, 337 individuals sustained some level of injury or were killed, representing 15.2% of the total. This includes 4 fatalities, 25 serious injuries, 120 minor injuries, and 188 possible injuries. The data also indicates 7 non-fatal injuries were recorded as 'None', suggesting they were evaluated and found to be uninjured.
Person Injury Severity
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
Data on safety equipment use was recorded for a subset of 242 vehicle occupants. Within this group, 220 individuals were reported as using a shoulder and lap belt. However, 16 occupants, or 6.6% of this recorded group, were not using any safety restraints 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
Two-vehicle collisions were the most common scenario, accounting for 604 crashes or 55.9% of the total. Single-vehicle crashes were also frequent, with 390 incidents representing 36.1% of all crashes. Multi-vehicle pileups involving three or more vehicles were less common, with 74 crashes involving three vehicles and 12 crashes involving four or more.
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: 1,080
- Total persons involved: 2,216
- Total vehicles involved: 1,872
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