Yearly Traffic Safety Analysis

245 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Washington County recorded 245 total crashes, a 6.1% decrease from the 261 crashes reported in 2017. The most significant year-over-year change was a reduction in traffic fatalities, which fell from 3 in 2017 to 1 in 2018, with fatal crashes decreasing from 3 to 1.

245

▼ -6.1%was 261

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

101

▼ -5.6%was 107

Persons Injured

1

▼ -66.7%was 3

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

Overall, traffic crashes in Washington County showed a downward trend from 2017 to 2018. Total crashes decreased by 6.1%, from 261 to 245. Correspondingly, total injuries saw a slight decline from 107 to 101, and fatalities decreased from 3 to 1.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

1

Pedestrians Injured

Prior: 1→0.0%

3

Cyclists Injured

Prior: 3→0.0%

97

Motorists Injured

Prior: 102↓-4.9%

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 showed some shifts between 2017 and 2018. While Friday remained a peak day for crashes in both years (42 in 2017, 44 in 2018), the peak hour for collisions moved from 2 p.m. in 2017 (29 crashes) to a dual peak at 12 p.m. and 5 p.m. in 2018 (21 crashes each). Monday also emerged as a high-frequency day in 2018 with 42 crashes, compared to 31 in the prior year.

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

Crash severity decreased notably from 2017 to 2018, with the number of fatal crashes dropping from 3 to 1. This resulted in a lower fatal crash rate, which fell from 1.15% to 0.41%. While the proportion of minor injury crashes remained stable at approximately 11%, there was a slight increase in the share of crashes resulting in serious injuries (from 3.4% to 4.1%) and possible injuries (from 16.5% to 18.4%).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-66.7%prior 3
Serious Injury10serious injury crashes4.1%
↑11.1%prior 9
Minor Injury27minor injury crashes11%
↓-6.9%prior 29
Possible Injury45possible injury crashes18.4%
↑4.7%prior 43
No Injury162no injury crashes66.1%
↓-8.5%prior 177

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 remained consistent between 2017 and 2018, though their frequency changed. Collisions involving an 'Animal' remained the top factor but decreased in count from 45 to 39. 'Failure to yield right of way from a stop sign' saw a significant reduction in count, falling from 30 incidents in 2017 to 19 in 2018. Conversely, crashes attributed to 'Driving too fast for conditions' more than doubled in count, increasing from 6 to 13 incidents.

Officer-Reported Primary Contributing Cause

Animal39 (15.9%)↓-13.3%prior 45
Followed too close21 (8.6%)↓-4.5%prior 22
FTYROW: From stop sign19 (7.8%)↓-36.7%prior 30
Other (explain in narrative): Other16 (6.5%)↑33.3%prior 12
Ran off road - straight14 (5.7%)↑27.3%prior 11
Lost Control13 (5.3%)↓-23.5%prior 17
Driving too fast for conditions13 (5.3%)↑116.7%prior 6
Ran Stop Sign12 (4.9%)↑9.1%prior 11
Ran off road - left10 (4.1%)↓-37.5%prior 16
Driver Distraction: Other interior distraction9 (3.7%)

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

Road & Environmental Conditions

In both 2017 and 2018, the majority of crashes occurred in clear weather and during daylight hours. However, there was a notable shift in road surface conditions, as the proportion of crashes on dry roads decreased from 73.9% in 2017 to 66.5% in 2018. Concurrently, collisions on adverse road surfaces like wet, snow, ice, or slush increased from 40 incidents in 2017 to 64 in 2018. Crashes in dark, unlighted conditions also rose from 41 to 52.

Weather

Clear160 (66.7%)
↓-8.0%prior 174
Cloudy39 (16.3%)
↓-2.5%prior 40
Snow12 (5.0%)
↓-7.7%prior 13
Rain10 (4.2%)
↓-23.1%prior 13
Freezing rain/drizzle7 (2.9%)
Fog, smoke, smog6 (2.5%)
Blowing Snow3 (1.3%)
Sleet, hail3 (1.3%)

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

Lighting

Daylight154 (64.2%)
↓-8.9%prior 169
Dark - roadway not lighted52 (21.7%)
↑26.8%prior 41
Dark - roadway lighted19 (7.9%)
↑11.8%prior 17
Dawn7 (2.9%)
→0.0%prior 7
Dusk5 (2.1%)
↓-44.4%prior 9
Dark - unknown roadway lighting3 (1.3%)

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

Road Surface

Dry163 (67.9%)
↓-15.5%prior 193
Wet28 (11.7%)
↑16.7%prior 24
Snow18 (7.5%)
↑38.5%prior 13
Gravel12 (5.0%)
→0.0%prior 12
Ice/frost10 (4.2%)
Slush8 (3.3%)
Mud, dirt1 (0.4%)

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

Vehicles & Demographics

Vehicle and person demographics showed notable shifts between the two years. Combining variations of make names, Chevrolet became the most frequent vehicle make in 2018 crashes with 98 vehicles, surpassing Ford, which decreased from 83 vehicles in 2017 to 55 in 2018. Regarding persons involved in crashes, the 16-20 age group saw a significant decrease in representation, dropping from 93 individuals in 2017 to 63 in 2018. Conversely, the 65+ age group saw an increase in involvement, rising from 74 individuals to 84.

Top Vehicle Makes (394 vehicles)

1
CHEV63 (16%)
↑26.0%prior 50
2
FORD55 (14%)
↓-33.7%prior 83
3
CHEVROLET35 (8.9%)
↑12.9%prior 31
4
DODG19 (4.8%)
↓-9.5%prior 21
5
GMC15 (3.8%)
↓-16.7%prior 18
6
TOYT14 (3.6%)
↑75.0%prior 8
7
CHRY11 (2.8%)
↓-8.3%prior 12
8
PONT10 (2.5%)
↓-28.6%prior 14
9
DODGE10 (2.5%)
↓-33.3%prior 15
10
HOND9 (2.3%)
↓-10.0%prior 10

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

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

Sex Distribution (321 persons with recorded sex)

Male168 (52.3%)
↓-13.4%prior 194
Female153 (47.7%)
↓-3.2%prior 158

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: 245
  • Total persons involved: 483
  • Total vehicles involved: 394

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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