Yearly Traffic Safety Analysis

361 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In 2017, there were 361 total crashes, a 3.5% decrease from the 374 crashes recorded in 2016. While the number of fatalities remained unchanged at 8 for both years, the total number of injuries saw a significant year-over-year reduction. The count of injured persons fell by 40.9%, from 132 in 2016 to 78 in 2017.

361

▼ -3.5%was 374

Total Crash Events

8

Persons Killed

78

▼ -40.9%was 132

Persons Injured

6

▲ 20.0%was 5

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

Overall, traffic crashes showed a slight downward trend in 2017 compared to the prior year, with total incidents decreasing by 3.5% from 374 to 361. This decline was primarily driven by a substantial 40.9% drop in total injuries, which fell from 132 to 78. The number of fatalities held steady at 8 for both periods.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

7

Motorists Killed

Prior: 8↓-12.5%

1

Pedestrians Injured

Prior: 1→0.0%

77

Motorists Injured

Prior: 131↓-41.2%

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 showed some shifts between 2016 and 2017. Saturday remained a peak day for crashes in both years, with its count increasing from 62 to 67 incidents. The 6 p.m. hour continued to be a high-frequency time for collisions, though the count dropped from 36 to 27. In 2017, the 3 p.m. hour also emerged as a peak time, matching the 6 p.m. hour with 27 crashes.

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

The severity of crashes shifted year-over-year. While total crashes decreased, the number of fatal crashes increased from 5 to 6, raising the fatal crash rate from 1.34% to 1.66% of all crashes. Conversely, the proportion of crashes resulting in any level of injury declined from 23.3% of all incidents in 2016 to 17.7% in 2017. This was most evident in the 'Possible Injury' category, which decreased from 48 to 31 crashes.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 8 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1.7%
↑20.0%prior 5
Serious Injury7serious injury crashes1.9%
↓-12.5%prior 8
Minor Injury26minor injury crashes7.2%
↓-16.1%prior 31
Possible Injury31possible injury crashes8.6%
↓-35.4%prior 48
No Injury291no injury crashes80.6%
↑3.2%prior 282

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

Collisions with an 'Animal' remained the leading contributing factor in both years, with the count increasing from 119 in 2016 to 129 in 2017. 'Lost Control' and 'Ran off road - straight' were the next most common factors, with 'Lost Control' incidents decreasing from 49 to 38 and 'Ran off road - straight' incidents increasing from 30 to 40. A notable decrease was observed in crashes attributed to 'Driving too fast for conditions,' which fell from 29 incidents in 2016 to 11 in 2017.

Officer-Reported Primary Contributing Cause

Animal129 (35.7%)↑8.4%prior 119
Ran off road - straight40 (11.1%)↑33.3%prior 30
Lost Control38 (10.5%)↓-22.4%prior 49
Followed too close25 (6.9%)↑8.7%prior 23
FTYROW: From stop sign15 (4.2%)↑15.4%prior 13
Driving too fast for conditions11 (3%)↓-62.1%prior 29
Ran off road - left10 (2.8%)↓-9.1%prior 11
Other (explain in narrative): Other9 (2.5%)↓-18.2%prior 11
FTYROW: Making left turn7 (1.9%)
Exceeded authorized speed6 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A significant shift was observed in crash conditions, largely tied to weather. Crashes in snowy conditions dropped from 31 in 2016 to 6 in 2017, and incidents on roads with snow, ice, or slush decreased from 50 to 14. While crashes in clear weather remained stable (137 vs. 136), incidents during daylight hours fell from 165 to 137. The number of crashes on dry road surfaces was comparable across both years, at 178 in 2017 versus 186 in 2016.

Weather

Clear137 (57.8%)
↑0.7%prior 136
Cloudy70 (29.5%)
↓-12.5%prior 80
Rain15 (6.3%)
↑114.3%prior 7
Snow6 (2.5%)
↓-80.6%prior 31
Fog, smoke, smog5 (2.1%)
Freezing rain/drizzle2 (0.8%)
Severe Winds1 (0.4%)
Blowing Snow1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight137 (57.8%)
↓-17.0%prior 165
Dark - roadway not lighted72 (30.4%)
↑2.9%prior 70
Dawn11 (4.6%)
↓-15.4%prior 13
Dark - roadway lighted9 (3.8%)
↓-25.0%prior 12
Dusk5 (2.1%)
Dark - unknown roadway lighting3 (1.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry178 (74.8%)
↓-4.3%prior 186
Wet30 (12.6%)
↑87.5%prior 16
Gravel16 (6.7%)
↑23.1%prior 13
Snow10 (4.2%)
↓-64.3%prior 28
Ice/frost4 (1.7%)
↓-75.0%prior 16

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field

Vehicles & Demographics

The distribution of vehicle makes involved in crashes showed some changes. When combining abbreviations, Chevrolet-branded vehicles remained the most common but saw their count decrease from 120 to 106. The count of Ford vehicles increased from 68 to 87. In terms of driver demographics, the representation of persons aged 55-64 involved in crashes increased, accounting for 16.6% of all persons in 2017 compared to 12.7% in 2016. Conversely, the share of persons in the 26-34 age group decreased from 18.0% to 16.8%.

Top Vehicle Makes (499 vehicles)

1
FORD87 (17.4%)
↑27.9%prior 68
2
CHEV61 (12.2%)
↑29.8%prior 47
3
CHEVROLET45 (9%)
↓-38.4%prior 73
4
GMC25 (5%)
↑38.9%prior 18
5
JEEP16 (3.2%)
↑60.0%prior 10
6
DODG15 (3%)
↑7.1%prior 14
7
TOYO14 (2.8%)
↑27.3%prior 11
8
FREIGHTLINER14 (2.8%)
↓-36.4%prior 22
9
CHRY12 (2.4%)
↑71.4%prior 7
10
PONT12 (2.4%)
↑71.4%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records

30 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (366 persons with recorded sex)

Male232 (63.4%)
↓-4.1%prior 242
Female134 (36.6%)
↓-11.3%prior 151

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: 361
  • Total persons involved: 559
  • Total vehicles involved: 499

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

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