Yearly Traffic Safety Analysis

128 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Lyon County recorded 128 total vehicle crashes, a 12.9% decrease from the 147 crashes reported in 2017. This year-over-year decline was accompanied by a reduction in fatalities, from two in the prior period to one in the current period. The most significant contributing factor in both years was collisions with animals, though the count for this factor also decreased from 38 in 2017 to 32 in 2018.

128

▼ -12.9%was 147

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

53

▼ -5.4%was 56

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Lyon County showed a downward trend from 2017 to 2018. The total number of crashes fell by 19, from 147 to 128. Similarly, the number of fatalities decreased from two to one, and total injuries saw a slight reduction from 56 to 53 year-over-year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 2↓-50.0%

53

Motorists Injured

Prior: 55↓-3.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. In 2018, the peak day for crashes was Wednesday with 25 incidents, a change from 2017 when Sunday was the peak day with 25 incidents. The peak hour also moved earlier in the day, from 8 p.m. (14 crashes) in 2017 to 3 p.m. (12 crashes) in 2018. The month with the highest crash volume shifted from October (24 crashes) in 2017 to November (26 crashes) in 2018.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a mixed change year-over-year. The number of fatal crashes decreased from two in 2017 to one in 2018, with the fatal crash rate dropping from 1.4% to 0.8% of all crashes. While the count of serious injury crashes remained stable at three for both years, the combined proportion of all injury-related crashes (serious, minor, and possible) increased from 29.2% of total crashes in 2017 to 33.5% in 2018.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
↓-50.0%prior 2
Serious Injury3serious injury crashes2.3%
→0.0%prior 3
Minor Injury21minor injury crashes16.4%
↓-4.5%prior 22
Possible Injury19possible injury crashes14.8%
↑5.6%prior 18
No Injury84no injury crashes65.6%
↓-17.6%prior 102

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, though the count decreased from 38 incidents in 2017 to 32 in 2018. 'Lost Control' was the second-ranked factor in both years, with its count also falling from 14 to 11. Conversely, crashes attributed to 'Driving too fast for conditions' increased from 8 in 2017 to 11 in 2018, becoming the third most common factor in the current period, up from fourth in the prior year.

Officer-Reported Primary Contributing Cause

Animal32 (25%)↓-15.8%prior 38
Driving too fast for conditions11 (8.6%)↑37.5%prior 8
Lost Control11 (8.6%)↓-21.4%prior 14
Other (explain in narrative): Other9 (7%)
Ran Stop Sign8 (6.3%)↑60.0%prior 5
Followed too close8 (6.3%)↓-20.0%prior 10
FTYROW: From stop sign7 (5.5%)→0.0%prior 7
Ran off road - straight5 (3.9%)→0.0%prior 5
FTYROW: At uncontrolled intersection4 (3.1%)
Ran off road - left3 (2.3%)↓-50.0%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. In 2018, a smaller share of crashes happened in clear weather (53.1%) compared to 2017 (66.0%). Correspondingly, the proportion of crashes on adverse road surfaces like snow, ice, or wet pavement increased from 18.4% in 2017 to 36.7% in 2018. Crashes in dark, unlighted conditions decreased, accounting for 17.2% of incidents in 2018, down from 23.1% in the previous year.

Weather

Clear68 (64.2%)
↓-29.9%prior 97
Cloudy14 (13.2%)
↓-22.2%prior 18
Snow8 (7.5%)
Freezing rain/drizzle7 (6.6%)
Rain5 (4.7%)
Fog, smoke, smog2 (1.9%)
Blowing Snow1 (0.9%)
Blowing sand, soil, dirt1 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight70 (66.7%)
↓-9.1%prior 77
Dark - roadway not lighted22 (21.0%)
↓-35.3%prior 34
Dark - roadway lighted9 (8.6%)
↑28.6%prior 7
Dawn2 (1.9%)
Dusk2 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry59 (55.7%)
↓-39.8%prior 98
Snow18 (17.0%)
Ice/frost11 (10.4%)
↑83.3%prior 6
Wet9 (8.5%)
Gravel7 (6.6%)
↓-41.7%prior 12
Water (standing or moving)2 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, and Dodge leading in both years. However, the number of Chevrolet-branded vehicles in crashes decreased from 52 to 41, and Dodge vehicles fell from 22 to 18, while Ford's involvement was unchanged at 34. An analysis of persons involved shows a demographic shift; the share of individuals in the 26-34 age group grew from 13.4% in 2017 to 17.5% in 2018, and the 65+ age group's share increased from 9.5% to 12.8%.

Top Vehicle Makes (191 vehicles)

1
FORD34 (17.8%)
→0.0%prior 34
2
CHEV22 (11.5%)
↓-8.3%prior 24
3
CHEVROLET19 (9.9%)
↓-32.1%prior 28
4
DODGE10 (5.2%)
↓-16.7%prior 12
5
GMC8 (4.2%)
↓-27.3%prior 11
6
DODG8 (4.2%)
↓-20.0%prior 10
7
TOYOTA7 (3.7%)
8
TOYT6 (3.1%)
9
NR5 (2.6%)
10
KIA5 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

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

Sex Distribution (130 persons with recorded sex)

Male78 (60.0%)
↓-18.8%prior 96
Female52 (40.0%)
↓-7.1%prior 56

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 128
  • Total persons involved: 234
  • Total vehicles involved: 191

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: 2018." Published September 9, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2018-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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