Monthly Traffic Safety Analysis

4,738 CRASHES IN
IOWA, IA
JUNE 2017

All metrics benchmarked againstJune 2016

In June 2017, there were 4,738 total crashes, representing a 3.1% increase from the 4,597 crashes recorded in June 2016. Despite the rise in total incidents, the most notable year-over-year shift was a significant decrease in roadway fatalities. The number of people killed in crashes fell by 25%, from 40 in the prior year to 30 in the current period.

4,738

▲ 3.1%was 4,597

Total Crash Events

30

▼ -25.0%was 40

Persons Killed

1,830

▼ -0.1%was 1,831

Persons Injured

28

▼ -22.2%was 36

Fatal Crash Events

Note: "Persons Killed" (30) counts individual fatalities across all crash events. "Fatal" in the severity table below (28) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight increase in total crash volume, which rose by 141 incidents from 4,597 in June 2016 to 4,738 in June 2017. However, the severity of these crashes lessened, as total fatalities decreased by 25% from 40 to 30. The number of injuries remained stable, changing by only one person from 1,831 to 1,830.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 2→0.0%

0

Cyclists Killed

Prior: 3↓-100.0%

28

Motorists Killed

Prior: 35↓-20.0%

0

Other Killed

Prior: 0→0.0%

34

Pedestrians Injured

Prior: 31↑9.7%

50

Cyclists Injured

Prior: 60↓-16.7%

1,741

Motorists Injured

Prior: 1,737↑0.2%

5

Other Injured

Prior: 3↑66.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes saw a shift in the peak day of the week between the two periods. In June 2017, Friday was the busiest day with 971 crashes, a change from Thursday in the prior year which saw 804 crashes. The peak hour for collisions, however, remained the 5 p.m. hour in both periods, with counts of 376 in 2016 and 400 in 2017.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes improved in June 2017 compared to the same month in 2016. The number of fatal crashes decreased from 36 to 28, and their share of all crashes fell from 0.8% to 0.6%. While the number of crashes involving any injury rose from 1,417 to 1,464, the proportion of crashes resulting in an injury remained stable at approximately 31% year-over-year. Consequently, the share of no-injury crashes also held steady at around 68.5%.

Severity is per crash event (most severe injury). 28 fatal crash events resulted in 30 persons killed.

Outcome by Severity (Crash Events)

Fatal28fatal crashes0.6%
↓-22.2%prior 36
Serious Injury129serious injury crashes2.7%
↓-0.8%prior 130
Minor Injury505minor injury crashes10.7%
↓-5.6%prior 535
Possible Injury830possible injury crashes17.5%
↑10.4%prior 752
No Injury3,246no injury crashes68.5%
↑3.2%prior 3,144

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors for crashes were consistent across both periods, with 'Animal' (703 incidents) and 'Followed too close' (575 incidents) remaining the top two causes. Both factors saw an increase in crash counts, rising from 650 and 525 respectively. Crashes attributed to 'Lost Control' decreased from 282 to 258, dropping its rank from third to fifth. Notably, incidents involving 'Improper or erratic lane changing' increased from 79 to 107.

Officer-Reported Primary Contributing Cause

Animal703 (14.8%)↑8.2%prior 650
Followed too close575 (12.1%)↑9.5%prior 525
Other (explain in narrative): Other314 (6.6%)↑47.4%prior 213
FTYROW: From stop sign266 (5.6%)↑3.5%prior 257
Lost Control258 (5.4%)↓-8.5%prior 282
Ran off road - left243 (5.1%)↑3.4%prior 235
FTYROW: Making left turn242 (5.1%)↑1.7%prior 238
Ran off road - straight165 (3.5%)↑7.1%prior 154
Ran Traffic Signal153 (3.2%)↓-8.4%prior 167
Ran Stop Sign151 (3.2%)↑20.8%prior 125

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions during crashes were largely unchanged year-over-year. The majority of incidents in both June 2016 and June 2017 occurred in daylight (approximately 71% of all crashes) and on dry road surfaces (approximately 80%). There was a minor shift in reported weather, with the share of crashes in clear conditions decreasing from 74.7% to 71.6%, while the share in cloudy conditions increased from 9.6% to 12.7%.

Weather

Clear3,392 (81.5%)
↓-1.2%prior 3,432
Cloudy602 (14.5%)
↑35.9%prior 443
Rain158 (3.8%)
↑4.6%prior 151
Severe Winds6 (0.1%)
↓-33.3%prior 9
Other (explain in narrative)2 (0.0%)
Blowing sand, soil, dirt1 (0.0%)
Fog, smoke, smog1 (0.0%)
Freezing rain/drizzle1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Weather condition at time of crash

Lighting

Daylight3,395 (81.2%)
↑4.1%prior 3,262
Dark - roadway lighted328 (7.8%)
↓-7.3%prior 354
Dark - roadway not lighted302 (7.2%)
↑3.1%prior 293
Dusk90 (2.2%)
↑4.7%prior 86
Dawn56 (1.3%)
↑12.0%prior 50
Dark - unknown roadway lighting12 (0.3%)
↓-14.3%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Lighting condition field

Road Surface

Dry3,775 (90.7%)
↑2.2%prior 3,694
Wet269 (6.5%)
↑15.9%prior 232
Gravel112 (2.7%)
↓-3.4%prior 116
Other (explain in narrative)2 (0.0%)
Mud, dirt2 (0.0%)
Oil2 (0.0%)
Sand1 (0.0%)
Water (standing or moving)1 (0.0%)
↓-80.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained stable, with Chevrolet, Ford, Toyota, Dodge, and Honda being the most frequent in both periods with similar counts. The age demographics of persons involved in crashes also showed little change. The proportion of individuals from the 16-20 age group decreased slightly from 13.7% in June 2016 to 12.9% in June 2017, while the 26-34 age group's share dropped from 15.8% to 14.9%.

Top Vehicle Makes (8,120 vehicles)

1
FORD1,294 (15.9%)
↓-0.7%prior 1,303
2
CHEV950 (11.7%)
↑34.4%prior 707
3
CHEVROLET606 (7.5%)
↓-25.6%prior 815
4
TOYT348 (4.3%)
↑32.8%prior 262
5
DODG319 (3.9%)
↑38.1%prior 231
6
HOND260 (3.2%)
↑26.2%prior 206
7
JEEP249 (3.1%)
↑10.2%prior 226
8
TOYOTA246 (3%)
↓-22.9%prior 319
9
DODGE219 (2.7%)
↓-23.2%prior 285
10
GMC210 (2.6%)
↓-4.5%prior 220

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · Vehicle unit records

1,203 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,182 persons with recorded sex)

Male3,428 (55.5%)
↑0.1%prior 3,423
Female2,754 (44.5%)
↑0.7%prior 2,736

Source: Iowa Crash Data · ArcGIS Open Data · 2017-06-01 to 2017-06-30 · 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: 2017-06-01 through 2017-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2017-06-01 through 2017-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,738
  • Total persons involved: 9,678
  • Total vehicles involved: 8,120

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: June 2017." Published September 9, 2026. Reporting period: 2017-06-01 to 2017-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2017-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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