ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · 2017
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/2017-annual-report
Yearly Traffic Safety Analysis
443 CRASHES IN
IOWA, IA
2017
In 2017, Sioux County recorded 443 total crashes, a 5.7% decrease from the 470 crashes reported in 2016. Despite the overall drop in collisions, the number of crashes resulting in serious injuries increased significantly, rising from 13 in 2016 to 24 in 2017. Total fatalities remained stable at 3 for both years.
443
▼ -5.7%was 470
Total Crash Events
3
Persons Killed
224
▲ 5.2%was 213
Persons Injured
3
Fatal Crash Events
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash totals in Sioux County saw a modest year-over-year decline, falling from 470 in 2016 to 443 in 2017, a decrease of 5.7%. While the number of crashes went down, the number of people injured in these incidents increased by 5.2%, from 213 to 224. The number of fatalities remained unchanged at 3 for both years.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
4
Pedestrians Injured
2
Cyclists Injured
217
Motorists Injured
1
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2017 (76 crashes) and 2016 (88 crashes). The peak hour for collisions shifted slightly, moving from the 4 p.m. hour in 2016 (40 crashes) to the 3 p.m. hour in 2017 (45 crashes). Weekdays continued to account for the majority of crashes in both periods.
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes decreased, the severity of those crashes increased from 2016 to 2017. The number of fatal crashes remained stable at 3, but the fatal crash rate rose slightly from 0.64% to 0.68%. More notably, crashes resulting in serious injuries increased from 13 in 2016 to 24 in 2017, and their share of all crashes grew from 2.8% to 5.4%. Consequently, the proportion of crashes with no injuries decreased from 68.1% to 63.4%.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record
Top Contributing Factors
In 2017, the top contributing factors were collisions with an animal (67 crashes), following too closely (64 crashes), and failure to yield from a stop sign (31 crashes). While "Animal" remained a leading factor, its count decreased from 71 in 2016. Crashes attributed to "Followed too close" increased by 12 incidents, from 52 to 64. Notably, incidents of "Ran Stop Sign" more than doubled, jumping from 8 crashes in 2016 to 18 in 2017, a 125% increase in count.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained broadly stable between 2016 and 2017. The majority of collisions in both years occurred in daylight (61.2% in 2017 vs. 59.8% in 2016) and on dry roads (55.1% in 2017 vs. 57.0% in 2016). One notable change was a decrease in crashes on roads with ice or frost, which accounted for 5.9% of crashes in 2017, down from 10.0% in the prior year.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were consistent year-over-year, with Chevrolet, Ford, and Dodge remaining the most common. There was a notable shift in the age demographics of persons involved in collisions. The 16-20 age group saw its involvement increase from 148 individuals in 2016 to 178 in 2017, representing a rise from 16.7% to 20.6% of all persons involved. The sex distribution also changed, with a higher number of males (357 vs. 339) and a lower number of females (201 vs. 241) involved in crashes in 2017 compared to the prior year.
Top Vehicle Makes (718 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records
39 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (558 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Person-level records linked to crash events
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: 2017-01-01 through 2017-12-31
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2017-01-01 through 2017-12-31 (365 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 443
- Total persons involved: 865
- Total vehicles involved: 718
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: 2017." Published September 9, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2017-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: 2017-01-01 – 2017-12-31
Generated: September 9, 2026 · All rights reserved