Yearly Traffic Safety Analysis

48 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Ringgold County, total vehicle crashes increased from 37 in 2017 to 48 in 2018, a 29.7% rise. While the overall number of crashes and injuries rose, the number of fatalities decreased from two in the prior year to one in the current year. The most notable year-over-year shift was a doubling in the number of crashes attributed to both 'Lost Control' and collisions with an 'Animal'.

48

▲ 29.7%was 37

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

22

▲ 22.2%was 18

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 Ringgold County showed an upward trend, increasing by 29.7% from 37 incidents in 2017 to 48 in 2018. This increase was accompanied by a 22.2% rise in total injuries, from 18 to 22. Conversely, fatalities saw a decrease, falling from two in 2017 to one in 2018.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 2↓-50.0%

22

Motorists Injured

Prior: 17↑29.4%

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, Friday was the peak day for crashes with 13 incidents, a change from 2017 when Monday was the peak day with 12 incidents. The peak hour for collisions was 5 p.m. in 2018 (6 crashes), slightly later than the 3 p.m. peak in 2017 (7 crashes). Crashes occurring on weekends (Saturday and Sunday) saw a notable increase, rising from 5 in 2017 to 14 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

While total crashes increased, the fatal crash rate decreased from 5.4% in 2017 to 2.1% in 2018, with fatal crashes dropping from two to one. The proportion of crashes resulting in any injury also declined, from 45.9% in 2017 to 37.5% in 2018. However, the number of serious injury crashes increased from one in the prior period to three in the current period, representing a rise from 2.7% to 6.3% of all crashes.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.1%
↓-50.0%prior 2
Serious Injury3serious injury crashes6.3%
↑200.0%prior 1
Minor Injury6minor injury crashes12.5%
↑50.0%prior 4
Possible Injury8possible injury crashes16.7%
↓-20.0%prior 10
No Injury30no injury crashes62.5%
↑50.0%prior 20

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 changed year-over-year. In 2018, 'Lost Control' and 'Animal' were the top-ranked factors, each accounting for 8 crashes. This represents a significant increase from 2017, when 'Lost Control' was cited in 4 crashes and 'Animal' in only 2. The factor 'FTYROW: From stop sign' also saw an increase, rising from 1 crash in 2017 to 4 in 2018.

Officer-Reported Primary Contributing Cause

Lost Control8 (16.7%)
Animal8 (16.7%)
FTYROW: From stop sign4 (8.3%)
Ran off road - left3 (6.3%)
Other (explain in narrative): Other3 (6.3%)↓-62.5%prior 8
Driving too fast for conditions3 (6.3%)
Ran Stop Sign2 (4.2%)
Crossed centerline (undivided)2 (4.2%)
FTYROW: Making left turn2 (4.2%)
Improper Backing2 (4.2%)

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

Road & Environmental Conditions

While clear weather and daylight conditions were predominant in both years, there was a notable shift in crashes related to road surface conditions. The proportion of crashes on dry roads decreased from 83.8% of all crashes in 2017 to 60.4% in 2018. Concurrently, crashes on adverse surfaces increased; incidents on icy or frosty roads rose from zero in 2017 to 6 in 2018, and crashes on wet roads increased from 2 to 5.

Weather

Clear39 (83.0%)
↑30.0%prior 30
Rain4 (8.5%)
Cloudy2 (4.3%)
↓-60.0%prior 5
Freezing rain/drizzle1 (2.1%)
Snow1 (2.1%)

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

Lighting

Daylight33 (70.2%)
↑32.0%prior 25
Dark - roadway not lighted9 (19.1%)
→0.0%prior 9
Dusk3 (6.4%)
Dark - unknown roadway lighting1 (2.1%)
Dawn1 (2.1%)

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

Road Surface

Dry29 (61.7%)
↓-6.5%prior 31
Ice/frost6 (12.8%)
Gravel5 (10.6%)
Wet5 (10.6%)
Sand1 (2.1%)
Snow1 (2.1%)

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

Vehicles & Demographics

A significant demographic shift occurred in the age of persons involved in crashes, with the 16-20 age group doubling from 12 individuals in 2017 to 24 in 2018. In terms of vehicle makes, Chevrolet-branded vehicles (26) were most frequently involved in crashes in 2018, surpassing Ford (7), which was the leading make in 2017 with 10 vehicles involved. The number of Dodge vehicles involved also increased from 7 to 10.

Top Vehicle Makes (73 vehicles)

1
CHEV21 (28.8%)
↑200.0%prior 7
2
FORD7 (9.6%)
↓-30.0%prior 10
3
DODG6 (8.2%)
↑20.0%prior 5
4
CHEVROLET5 (6.8%)
5
PONT4 (5.5%)
6
JEEP4 (5.5%)
7
DODGE4 (5.5%)
8
TOYOTA3 (4.1%)
9
KIA3 (4.1%)
10
GMC2 (2.7%)

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

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

Sex Distribution (61 persons with recorded sex)

Male34 (55.7%)
↑41.7%prior 24
Female27 (44.3%)
↑170.0%prior 10

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: 48
  • Total persons involved: 87
  • Total vehicles involved: 73

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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