Yearly Traffic Safety Analysis

232 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Carroll County, total crashes decreased by 12.5% from 265 in 2017 to 232 in 2018. This overall decline in collisions was accompanied by a reduction in both fatalities, which dropped from 3 to 1, and total injuries, which fell from 96 to 76. One of the most significant shifts was a 66.7% decrease in crashes involving a driver under the influence, which fell from 9 incidents in 2017 to 3 in 2018.

232

▼ -12.5%was 265

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

76

▼ -20.8%was 96

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 safety metrics in Carroll County showed a positive trend from 2017 to 2018. The total number of crashes fell by 12.5%, from 265 to 232. This improvement extended to crash outcomes, as the number of people injured decreased by 20.8% from 96 to 76, and the number of fatalities was reduced 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%

2

Pedestrians Injured

Prior: 1↑100.0%

2

Cyclists Injured

Prior: 1↑100.0%

72

Motorists Injured

Prior: 94↓-23.4%

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 showed some shifts between the two years. The peak day for collisions moved from Tuesday, with 50 crashes in 2017, to Wednesday, with 47 crashes in 2018. However, the peak hour for crashes remained consistent at 5 p.m. in both periods, though the volume of crashes during that hour decreased from 26 to 22.

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 generally decreased in 2018 compared to the prior year. The number of fatal crashes fell from 3 to 1, causing the fatal crash rate to drop from 1.13% to 0.43% of all collisions. The proportion of crashes resulting in minor injuries also decreased from a 13.2% share to a 9.9% share. In contrast, the share of crashes involving possible injuries increased slightly from 12.8% in 2017 to 15.9% in 2018.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-66.7%prior 3
Serious Injury6serious injury crashes2.6%
↓-25.0%prior 8
Minor Injury23minor injury crashes9.9%
↓-34.3%prior 35
Possible Injury37possible injury crashes15.9%
↑8.8%prior 34
No Injury165no injury crashes71.1%
↓-10.8%prior 185

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 shifted between 2017 and 2018. While 'Failure to Yield Right of Way from a stop sign' was a top cause in both years, its count decreased from 29 incidents in 2017 to 21 in 2018. Crashes attributed to 'Driving too fast for conditions' saw a significant increase, rising from 4 to 14 incidents. Conversely, crashes caused by 'Followed too close' dropped from a count of 24 to 13.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign21 (9.1%)↓-27.6%prior 29
Lost Control19 (8.2%)↑18.8%prior 16
Other (explain in narrative): Other18 (7.8%)↓-5.3%prior 19
Ran off road - left17 (7.3%)↓-22.7%prior 22
Driving too fast for conditions14 (6%)
Followed too close13 (5.6%)↓-45.8%prior 24
Other (explain in narrative): No improper action11 (4.7%)↑83.3%prior 6
Driver Distraction: Other interior distraction10 (4.3%)↑42.9%prior 7
Ran Traffic Signal10 (4.3%)
Ran off road - straight9 (3.9%)↑12.5%prior 8

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

Road & Environmental Conditions

The conditions under which crashes occurred changed, with a higher proportion of incidents happening on non-dry surfaces in 2018. The share of crashes on dry roads decreased from 75.1% in 2017 to 59.9% in 2018. Correspondingly, collisions on wet, icy, or snow-covered surfaces accounted for a larger portion of the total, rising from 15.8% of crashes in the prior period to 35.8% in the current period. Lighting conditions remained largely consistent, with daylight crashes making up approximately 70% of the total in both years.

Weather

Clear143 (63.0%)
↓-21.4%prior 182
Cloudy40 (17.6%)
↓-14.9%prior 47
Freezing rain/drizzle16 (7.0%)
↑128.6%prior 7
Snow13 (5.7%)
↑116.7%prior 6
Rain7 (3.1%)
→0.0%prior 7
Blowing Snow3 (1.3%)
Fog, smoke, smog3 (1.3%)
Severe Winds1 (0.4%)
Other (explain in narrative)1 (0.4%)

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

Lighting

Daylight163 (71.5%)
↓-9.9%prior 181
Dark - roadway not lighted33 (14.5%)
↑3.1%prior 32
Dark - roadway lighted23 (10.1%)
↓-14.8%prior 27
Dawn3 (1.3%)
↓-40.0%prior 5
Dark - unknown roadway lighting3 (1.3%)
Dusk3 (1.3%)
↓-70.0%prior 10

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

Road Surface

Dry139 (61.2%)
↓-30.2%prior 199
Wet29 (12.8%)
↑52.6%prior 19
Ice/frost26 (11.5%)
↑100.0%prior 13
Snow24 (10.6%)
↑200.0%prior 8
Gravel5 (2.2%)
↓-68.8%prior 16
Slush4 (1.8%)

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

Vehicles & Demographics

Vehicle and person demographics involved in crashes showed some changes between 2017 and 2018. The top vehicle makes involved in collisions were consistent, with Chevrolet and Ford vehicles accounting for the highest numbers in both years. Among persons involved, the 16-20 age group saw its representation decrease from 88 individuals in 2017 to 56 in 2018. Conversely, the 45-54 age group's involvement increased, rising from 52 individuals in the prior year to 72 in the current year.

Top Vehicle Makes (408 vehicles)

1
CHEV89 (21.8%)
↑20.3%prior 74
2
FORD62 (15.2%)
↓-4.6%prior 65
3
CHEVROLET34 (8.3%)
↓-33.3%prior 51
4
DODG20 (4.9%)
↓-4.8%prior 21
5
PONT16 (3.9%)
↑60.0%prior 10
6
GMC15 (3.7%)
↓-16.7%prior 18
7
BUIC15 (3.7%)
↑15.4%prior 13
8
CHRY12 (2.9%)
↓-14.3%prior 14
9
TOYT11 (2.7%)
↓-42.1%prior 19
10
JEEP10 (2.5%)
↓-23.1%prior 13

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

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

Sex Distribution (324 persons with recorded sex)

Male180 (55.6%)
↓-9.1%prior 198
Female144 (44.4%)
↓-11.1%prior 162

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: 232
  • Total persons involved: 482
  • Total vehicles involved: 408

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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