Yearly Traffic Safety Analysis

151 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In O'Brien County, total traffic crashes decreased by 13.2%, from 174 in 2017 to 151 in 2018. Despite the overall reduction in collisions, the most significant year-over-year change was the emergence of traffic fatalities, with two fatal crashes resulting in two deaths in 2018, compared to zero in the prior year.

151

▼ -13.2%was 174

Total Crash Events

2

Persons Killed

67

▼ -6.9%was 72

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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

Overall, traffic crashes in O'Brien County showed a downward trend, decreasing from 174 in 2017 to 151 in 2018. The number of people injured also saw a slight decline from 72 to 67. However, this positive trend was contrasted by a negative development in crash severity, as the county recorded two fatalities in 2018 after having none in 2017.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 1→0.0%

65

Motorists Injured

Prior: 71↓-8.5%

1

Other Injured

Prior: 0→%

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

The temporal patterns of crashes shifted between the two periods. In 2018, Tuesday was the peak day for crashes with 32 incidents, a change from 2017 when Wednesday saw the most crashes at 34. The peak hour for collisions also changed significantly, moving from the 4 p.m. hour in 2017 (24 crashes) to the 12 p.m. hour in 2018 (14 crashes).

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

While total crashes decreased, their severity worsened year-over-year. The county experienced two fatal crashes in 2018, up from zero in 2017. The number of serious injury crashes also increased from 7 to 9. Consequently, the proportion of crashes resulting in any injury (fatal, serious, minor, or possible) rose from 28.2% of all crashes in 2017 to 35.8% in 2018.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.3%
Serious Injury9serious injury crashes6%
↑28.6%prior 7
Minor Injury16minor injury crashes10.6%
↑6.7%prior 15
Possible Injury27possible injury crashes17.9%
→0.0%prior 27
No Injury97no injury crashes64.2%
↓-22.4%prior 125

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

The leading contributing factors for crashes showed some changes between 2017 and 2018. Collisions involving an 'Animal' remained a top cause but decreased in count from 21 to 17. Incidents attributed to 'Lost Control' increased from 9 to 14, and crashes due to 'FTYROW: From stop sign' also rose from 11 to 14. 'Driving too fast for conditions' was a factor in 12 crashes in both years, while 'Ran off road - left' incidents were also stable at 14.

Officer-Reported Primary Contributing Cause

Animal17 (11.3%)↓-19.0%prior 21
FTYROW: From stop sign14 (9.3%)↑27.3%prior 11
Lost Control14 (9.3%)↑55.6%prior 9
Driving too fast for conditions12 (7.9%)→0.0%prior 12
Followed too close11 (7.3%)↑22.2%prior 9
Ran off road - left11 (7.3%)↓-21.4%prior 14
Improper Backing7 (4.6%)
Ran off road - straight6 (4%)→0.0%prior 6
Ran Stop Sign6 (4%)↓-33.3%prior 9
FTYROW: At uncontrolled intersection5 (3.3%)→0.0%prior 5

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

Road & Environmental Conditions

Crash conditions saw a notable shift toward more incidents on adverse road surfaces. While crashes on dry roads decreased from 107 to 79, collisions on snowy surfaces more than doubled, increasing from 10 in 2017 to 24 in 2018. Correspondingly, crashes during snowy weather also increased from 7 to 13. The distribution of crashes by lighting conditions remained relatively stable, with daylight crashes being the most common in both periods.

Weather

Clear85 (62.0%)
↓-5.6%prior 90
Cloudy22 (16.1%)
↓-53.2%prior 47
Snow13 (9.5%)
↑85.7%prior 7
Rain7 (5.1%)
→0.0%prior 7
Fog, smoke, smog5 (3.6%)
Severe Winds2 (1.5%)
Freezing rain/drizzle2 (1.5%)
Blowing Snow1 (0.7%)

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

Lighting

Daylight104 (74.8%)
↓-11.9%prior 118
Dark - roadway not lighted20 (14.4%)
↓-4.8%prior 21
Dark - roadway lighted8 (5.8%)
→0.0%prior 8
Dusk3 (2.2%)
↓-62.5%prior 8
Dawn2 (1.4%)
Dark - unknown roadway lighting2 (1.4%)

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

Road Surface

Dry79 (56.8%)
↓-26.2%prior 107
Snow24 (17.3%)
↑140.0%prior 10
Ice/frost15 (10.8%)
↓-6.3%prior 16
Wet13 (9.4%)
↓-23.5%prior 17
Gravel5 (3.6%)
Slush3 (2.2%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained broadly consistent, with Chevrolet and Ford being the most common in both years. In 2018, Chevrolet was the most frequent make with 53 vehicles involved, followed by Ford with 42. This represents a shift from 2017, when Ford led with 60 vehicles involved compared to Chevrolet's 59. The age and sex distribution of persons involved in crashes did not show significant changes year-over-year.

Top Vehicle Makes (248 vehicles)

1
FORD42 (16.9%)
↓-30.0%prior 60
2
CHEV37 (14.9%)
↓-15.9%prior 44
3
CHEVROLET16 (6.5%)
↑6.7%prior 15
4
GMC15 (6%)
↓-6.3%prior 16
5
BUIC13 (5.2%)
↑18.2%prior 11
6
DODG12 (4.8%)
↑33.3%prior 9
7
PONT11 (4.4%)
↑10.0%prior 10
8
CHRY10 (4%)
↓-16.7%prior 12
9
DODGE9 (3.6%)
↓-18.2%prior 11
10
JEEP7 (2.8%)
→0.0%prior 7

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

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

Sex Distribution (194 persons with recorded sex)

Male118 (60.8%)
↓-4.8%prior 124
Female76 (39.2%)
↓-7.3%prior 82

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: 151
  • Total persons involved: 302
  • Total vehicles involved: 248

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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