Monthly Traffic Safety Analysis

4,569 CRASHES IN
IOWA, IA
MAY 2018

All metrics benchmarked againstMay 2017

In May 2018, Iowa recorded 4,569 traffic crashes, a 5.4% decrease from the 4,828 crashes in May 2017. While overall crashes and injuries declined, the number of fatal crashes increased from 20 to 22 year-over-year, and total fatalities remained unchanged at 23. A notable shift was a 15.4% decrease in DUI-involed crashes, which fell from 175 to 148.

4,569

▼ -5.4%was 4,828

Total Crash Events

23

Persons Killed

1,659

▼ -3.3%was 1,716

Persons Injured

22

▲ 10.0%was 20

Fatal Crash Events

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic incidents shows a modest decline year-over-year. Total crashes decreased by 5.4%, from 4,828 in May 2017 to 4,569 in May 2018. Similarly, the number of people injured fell by 3.3% from 1,716 to 1,659, while the number of fatalities was stable at 23 for both periods.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

1

Cyclists Killed

Prior: 0→%

21

Motorists Killed

Prior: 22↓-4.5%

0

Other Killed

Prior: 0→0.0%

23

Pedestrians Injured

Prior: 33↓-30.3%

40

Cyclists Injured

Prior: 32↑25.0%

1,591

Motorists Injured

Prior: 1,644↓-3.2%

5

Other Injured

Prior: 7↓-28.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes saw a shift in the peak day of the week. In May 2018, Thursday was the busiest day with 785 crashes, whereas in May 2017, Tuesday was the peak day with 838 crashes. The peak hour for collisions, however, remained consistent, occurring at 3 p.m. in both periods, with 421 crashes in 2018 and 412 in 2017.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the fatal crash rate rose from 0.41% in May 2017 to 0.48% in May 2018. The number of fatal crashes increased from 20 to 22. The proportion of crashes resulting in serious injuries decreased slightly from 2.6% to 2.5%, while the share of no-injury crashes increased from 69.8% to 70.3% of all incidents.

Severity is per crash event (most severe injury). 22 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal22fatal crashes0.5%
↑10.0%prior 20
Serious Injury114serious injury crashes2.5%
↓-9.5%prior 126
Minor Injury485minor injury crashes10.6%
↓-1.2%prior 491
Possible Injury734possible injury crashes16.1%
↓-10.6%prior 821
No Injury3,214no injury crashes70.3%
↓-4.6%prior 3,370

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors remained consistent between the two periods, with 'Animal' and 'Followed too close' ranking first and second respectively. However, the count of crashes involving animals increased by 8.7%, from 622 to 676. Conversely, crashes attributed to 'Followed too close' decreased by 8.1% in count, from 617 to 567. Crashes due to 'Lost Control' also saw a notable decrease of 13.4% in count, from 268 incidents to 232.

Officer-Reported Primary Contributing Cause

Animal676 (14.8%)↑8.7%prior 622
Followed too close567 (12.4%)↓-8.1%prior 617
Other (explain in narrative): Other300 (6.6%)↓-0.3%prior 301
FTYROW: From stop sign273 (6%)↓-1.1%prior 276
Ran off road - left242 (5.3%)↑3.0%prior 235
Lost Control232 (5.1%)↓-13.4%prior 268
FTYROW: Making left turn187 (4.1%)↓-19.4%prior 232
Ran Traffic Signal156 (3.4%)↑1.3%prior 154
Driver Distraction: Other interior distraction145 (3.2%)↑6.6%prior 136
Ran Stop Sign137 (3%)↓-13.3%prior 158

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a significant year-over-year shift in crash conditions, with fewer incidents occurring in adverse weather. Crashes in the rain decreased from 370 to 218, and collisions on wet road surfaces dropped from 645 to 400. Consequently, the proportion of crashes on dry roads increased from 73.9% in May 2017 to 76.8% in May 2018. Lighting conditions for crashes remained proportionally similar, with about 71-72% of crashes occurring in daylight in both periods.

Weather

Clear2,889 (71.8%)
↓-1.8%prior 2,941
Cloudy868 (21.6%)
↓-11.0%prior 975
Rain218 (5.4%)
↓-41.1%prior 370
Fog, smoke, smog26 (0.6%)
↑160.0%prior 10
Freezing rain/drizzle10 (0.2%)
↑100.0%prior 5
Severe Winds6 (0.1%)
↓-64.7%prior 17
Other (explain in narrative)2 (0.0%)
Blowing sand, soil, dirt1 (0.0%)
Sleet, hail1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Weather condition at time of crash

Lighting

Daylight3,256 (80.7%)
↓-6.8%prior 3,494
Dark - roadway lighted322 (8.0%)
↓-16.6%prior 386
Dark - roadway not lighted294 (7.3%)
↓-1.0%prior 297
Dusk88 (2.2%)
↑6.0%prior 83
Dawn58 (1.4%)
↓-13.4%prior 67
Dark - unknown roadway lighting18 (0.4%)
→0.0%prior 18

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Lighting condition field

Road Surface

Dry3,507 (87.1%)
↓-1.7%prior 3,566
Wet400 (9.9%)
↓-38.0%prior 645
Gravel108 (2.7%)
↑12.5%prior 96
Mud, dirt5 (0.1%)
↓-50.0%prior 10
Water (standing or moving)3 (0.1%)
Other (explain in narrative)1 (0.0%)
Sand1 (0.0%)
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, remained consistent across both periods, though their total counts decreased in May 2018. Analysis of persons involved in crashes shows a shift in age representation. The share of individuals aged 65 and older increased from 10.3% of all persons in May 2017 to 11.3% in May 2018. Conversely, the proportion of younger people, particularly in the 16-20 and 26-34 age groups, saw a slight decrease.

Top Vehicle Makes (7,974 vehicles)

1
FORD1,260 (15.8%)
↓-7.3%prior 1,359
2
CHEV1,108 (13.9%)
↑9.7%prior 1,010
3
CHEVROLET482 (6%)
↓-24.3%prior 637
4
TOYT389 (4.9%)
↓-2.8%prior 400
5
DODG354 (4.4%)
↑7.6%prior 329
6
HOND269 (3.4%)
↓-4.6%prior 282
7
JEEP247 (3.1%)
↓-2.4%prior 253
8
NISS218 (2.7%)
↑1.9%prior 214
9
GMC218 (2.7%)
↓-4.0%prior 227
10
NR194 (2.4%)
↑3.7%prior 187

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · Vehicle unit records

1,359 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (7,133 persons with recorded sex)

Male3,950 (55.4%)
↓-1.5%prior 4,010
Female3,183 (44.6%)
↓-4.7%prior 3,339

Source: Iowa Crash Data · ArcGIS Open Data · 2018-05-01 to 2018-05-31 · 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: 2018-05-01 through 2018-05-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-05-01 through 2018-05-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,569
  • Total persons involved: 10,763
  • Total vehicles involved: 7,974

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 2018." Published September 9, 2026. Reporting period: 2018-05-01 to 2018-05-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/may-2018-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

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