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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
126 CRASHES IN
IOWA, IA
2015
In 2015, Fremont County recorded 126 total traffic crashes, resulting in 0 fatalities and 58 injuries. A significant portion of these incidents, 58.7%, were single-vehicle crashes not involving a collision with another vehicle. The most frequently cited contributing factor was drivers losing control, which was noted in 19% of all crashes.
126
Total Crash Events
0
Persons Killed
58
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 any road users in Fremont County. A total of 58 individuals were injured, with the vast majority being motorists (57 injuries). One cyclist was injured, and there were no recorded pedestrian injuries or fatalities.
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
57
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 Fremont County peaked on Mondays, which saw 28 incidents in 2015. The most frequent time for crashes was the afternoon, with a peak of 12 crashes during the 3 p.m. hour. While a majority of crashes (74) occurred during daylight hours, a notable number of incidents (39) happened in dark or low-light 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
Out of 126 total crashes, a majority (61.9%) resulted in no injuries, involving only property damage. The remaining 38.1% of crashes involved some level of injury, including 13 crashes with serious injuries and 18 with minor injuries. There were no fatal crashes recorded in Fremont County during this period.
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 for crashes in 2015 was 'Lost Control,' cited in 24 incidents, or 19% of the total. Collisions involving an 'Animal' were the second most common factor, accounting for 19 crashes (15.1%). Running off the road was also a significant factor, with 'Ran off road - straight' listed in 15 crashes (11.9%).
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
The majority of crashes occurred in ideal driving conditions, with 68.3% (86 crashes) happening on dry roads and 61.9% (78 crashes) in clear weather. Similarly, 58.7% of crashes (74) took place during daylight hours. Adverse road surface conditions such as wet, snow, or ice were present in a combined 21 crashes.
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
Analysis of persons involved in crashes shows the 45-54 age group was the most represented, with 43 individuals, followed by the 26-34 age group with 38 individuals. Among the 179 vehicles involved, Ford was the most frequent make, with 33 vehicles recorded. Chevrolet was recorded 23 times, with an additional 11 instances coded as 'CHEV'.
Top Vehicle Makes (179 vehicles)
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 (143 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 major cause identified in crashes was 'Lost Control,' accounting for 24 incidents, or 19.0% of all crashes. Collisions with animals were the second-leading cause, cited in 19 crashes (15.1%). 'Ran off road - straight' was the third most common cause, contributing to 15 crashes (11.9%).
Major Cause
Showing top 9 of 27 reported. 18 additional (31 total) not shown: Other (explain in narrative): No improper action, Other (explain in narrative): Other, Driver Distraction: Other interior distraction, Exceeded authorized speed, FTYROW: From stop sign, Made improper turn, Operating vehicle in an reckless, erratic, careless, negligent manner, FTYROW: At uncontrolled intersection, Improper or erratic lane changing, Failed to yield to emergency vehicle, Ran Traffic Signal, Operator inexperience, Passing: Other passing (explain in narrative), Passing: With insufficient distance/inadequate visibility, Driver Distraction: Exterior distraction, Driver Distraction: Adjusting devices (radio, climate), Cargo/equipment loss or shift, Driver Distraction: Reaching for object(s)/fallen object(s).
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: Vehicle in traffic,' which occurred in 42 crashes (33.3%). 'Collision with: Animal' and 'Non-collision events: Overturn/rollover' were the next most frequent events, each accounting for 18 crashes (14.3% each). Collisions with various fixed objects like ditches, embankments, and fences collectively represent another significant category of initial impacts.
First Harmful Event
Showing top 9 of 24 reported. 15 additional (21 total) not shown: Collision with fixed object: Traffic sign support, Collision with fixed object: Tree, Collision with fixed object: Utility pole/light support, Collision with: Other non-fixed object (explain in narrative), Collision with: Parked motor vehicle, Collision with: Re-entering roadway, Collision with fixed object: Cable barrier, Non-collision events: Vehicle went airborne, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Building, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Thrown or falling object, Collision with fixed object: Concrete traffic barrier (median or right side), Non-collision events: Other non-collision (explain in narrative), 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
A majority of crashes, 70 out of 126 (55.6%), occurred at non-intersection locations. Crashes at intersections were less frequent, with T-intersections and four-way intersections each accounting for 11 incidents. Interchange-related crashes, primarily on off-ramps, were noted in 10 cases.
Roadway Junction / Feature
Showing top 9 of 12 reported. 3 additional (3 total) not shown: Non-intersection: Driveway access (within), Non-intersection: Other non-intersection (explain in narrative), Non-intersection: Railroad grade crossing.
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 70 of the 179 vehicles. Light trucks, including pickups, were the second most frequent with 42 vehicles, followed by Sport Utility Vehicles with 24. Notably, large commercial vehicles (Tractor/semi-trailer) were involved in 20 instances, and motorcycles were involved in 4 crashes.
Vehicle Type
"Other" combines 4 smaller categories (5 records): Farm tractor (2), Tractor/doubles (1), Other light truck (<=10000 lbs) (1), Truck/trailer (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
Data indicates that the vast majority of vehicles involved in crashes were in areas with no traffic controls present, accounting for 133 instances. Stop signs were the most common form of traffic control noted, present in 18 cases. Traffic signals were present for 6 of the vehicles involved in crashes.
Traffic Control Device
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 initial damage, with 44 vehicles sustaining a direct frontal impact. Including corner impacts, frontal damage was recorded in a total of 69 instances. Side impacts were also frequent, with 12 vehicles damaged on the driver's side middle area, while rear-end damage was noted for 9 vehicles.
Most Damaged Area
"Other" combines 10 smaller categories (47 records): Top (8), Driver side - rear (8), Driver side - front (7), Rear - driver side corner (6), Rear - passenger side corner (5), Other (explain in narrative) (4), Cargo loss (3), Passenger side - rear (3), 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 Fremont County, the highest volume of crashes occurred in Hamburg, which recorded 10 incidents in 2015. The city of Sidney had the second-highest number with 8 crashes. Shenandoah and Thurman followed with 4 and 3 crashes, respectively.
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, 116 out of 126, occurred on paved roadways. Crashes on unpaved surfaces, such as gravel or dirt roads, accounted for 10 incidents, representing 7.9% 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
Roadway Contributing Factor
For the small number of crashes where a roadway factor was cited as a contributor, 'Surface condition' was the most common, noted in 12 cases. This includes factors like wet or icy roads. Other factors such as ruts or shoulder issues 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 crashes where a driver condition other than 'apparently normal' was recorded, being 'Under the influence of alcohol' and 'Asleep/fatigued' were the most frequent, each cited for 5 drivers. Medical issues, including seizures or fainting, were noted for 4 drivers, while influence of drugs was recorded for 2 drivers.
Driver Condition
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
The estimated cost of property damage was most frequently in the '$1,500 - $7,500' range, which applied to 73 crashes. A significant number of crashes, 47, resulted in damages estimated between '$7,500 - $25,000'. High-damage crashes, with costs exceeding $25,000, accounted for 5 incidents, or 4.0% 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
The dominant manner of collision was 'Non-collision (single vehicle),' which includes incidents like run-offs and rollovers, accounting for 74 crashes or 58.7% of the total. Among multi-vehicle crashes, rear-end collisions were the most common type, occurring in 20 incidents (15.9%). Broadside and same-direction sideswipe crashes each accounted for 9 incidents (7.1%).
Manner of Collision
"Other" combines 1 smaller categories (1 records): Rear to side (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 involved was 'Movement essentially straight,' recorded for 116 vehicles. 'Turning left' was the next most frequent action, noted for 15 vehicles prior to their involvement in a crash. An additional 7 vehicles were 'Stopped in traffic' immediately before the collision.
Pre-Crash Driver Action
Showing top 9 of 14 reported. 5 additional (8 total) not shown: Slowing/stopping (deceleration), Changing lanes, Leaving traffic lane, Entering traffic lane (merging), Illegally Parked/Unattended.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 238 individuals involved in crashes, the vast majority were drivers, accounting for 223 people or 93.7% of the total. Passengers made up a smaller portion with 14 individuals (5.9%). One bicyclist was involved in a 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
Across all 238 people involved in crashes, 58 individuals sustained some level of injury. This included 13 serious injuries, 23 minor injuries, and 22 possible injuries. There were no fatalities recorded among any persons involved in crashes.
Person Injury Severity
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
Based on available data for safety equipment usage, 33 occupants were recorded as using a shoulder and lap belt. In 9 instances, it was noted that no safety equipment was used by the participant. Helmet use was recorded for 3 individuals.
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
A majority of crashes, 78 out of 126 (61.9%), involved only a single vehicle. Two-vehicle collisions were the next most common, with 44 incidents. There were a small number of multi-vehicle pile-ups, including 3 crashes involving three vehicles and one crash involving 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: 126
- Total persons involved: 238
- Total vehicles involved: 179
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