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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · MAY 2026
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/may-2026-report
Monthly Traffic Safety Analysis
4,478 CRASHES IN
IOWA, IA
MAY 2026
In May 2026, there were 4,478 vehicle crashes statewide, a 1.4% increase from the 4,417 crashes recorded in May 2025. Fatalities also rose from 24 to 26 year-over-year. The most notable shift in contributing factors was a 10.4% increase in crashes involving animals, which rose from 636 incidents to 702.
4,478
▲ 1.4%was 4,417
Total Crash Events
26
▲ 8.3%was 24
Persons Killed
1,493
▲ 2.1%was 1,462
Persons Injured
26
▲ 8.3%was 24
Fatal Crash Events
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends show a slight increase in May 2026 compared to the same month in the prior year. Total crashes rose by 1.4% (from 4,417 to 4,478), while total injuries increased by 2.1% (from 1,462 to 1,493). The number of fatalities saw an 8.3% increase, rising from 24 to 26.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
24
Motorists Killed
0
Other Killed
37
Pedestrians Injured
56
Cyclists Injured
1,391
Motorists Injured
9
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · 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 May 2026 (867 crashes) and May 2025 (846 crashes). However, the peak hour shifted slightly earlier, from 4 p.m. in the prior period (395 crashes) to 3 p.m. in the current period (373 crashes). Notably, crashes on Thursdays decreased from 723 to 587, while Sunday crashes increased from 456 to 599.
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity distribution of crashes was stable between the two periods. The fatal crash rate saw a minor increase from 0.54 per 100 crashes in May 2025 to 0.58 in May 2026, corresponding to a rise from 24 to 26 fatal incidents. The proportions of crashes resulting in serious injury (2.7% vs. 2.6%), minor injury (10.3% in both periods), and possible injury (15.2% vs. 15.3%) remained virtually unchanged year-over-year.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes were consistent across both periods, with 'Animal' (702 crashes), 'Followed too close' (506), and 'FTYROW: From stop sign' (279) ranking as the top three in May 2026. The count of crashes attributed to animals increased by 10.4%, from 636 to 702, representing the most significant growth among top factors. Conversely, crashes where 'Driving too fast for conditions' was a factor decreased by 25%, from 100 incidents in the prior year to 75 in the current year.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions shifted notably between the two periods, primarily related to weather. Crashes in rainy conditions decreased by 52.9% (from 204 to 96), with a corresponding drop in crashes on wet road surfaces (from 372 to 163). Consequently, a higher proportion of crashes in May 2026 occurred in clear weather (70.9% vs. 66.8%) and on dry roads (80.5% vs. 76.7%) compared to May 2025. Lighting conditions at the time of crashes remained proportionally similar year-over-year.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Road surface condition field
Vehicles & Demographics
The demographics of vehicles and persons involved in crashes showed high stability year-over-year. Ford (1,154 vehicles) and Chevrolet (1,057) remained the top two vehicle makes involved in crashes in May 2026, consistent with the prior year's rankings and counts. The age distribution of individuals involved also saw little change; the 26-34 age group was the most represented in both periods, with an identical count of 1,185 persons.
Top Vehicle Makes (7,670 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · Vehicle unit records
910 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,903 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2026-05-01 to 2026-05-31 · 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: 2026-05-01 through 2026-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2026-05-01 through 2026-05-31 (31 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 4,478
- Total persons involved: 8,031
- Total vehicles involved: 7,670
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: May 2026." Published August 20, 2026. Reporting period: 2026-05-01 to 2026-05-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/may-2026-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: 2026-05-01 – 2026-05-31
Generated: August 20, 2026 · All rights reserved
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