Yearly Traffic Safety Analysis

204 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Carroll County recorded 204 total crashes, a 7.7% decrease from the 221 crashes reported in 2022. During this period, total injuries saw a significant decline of 24.4%, falling from 86 to 65. The number of fatalities also decreased from 4 in 2022 to 3 in 2023.

204

▼ -7.7%was 221

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

65

▼ -24.4%was 86

Persons Injured

3

▼ -25.0%was 4

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Carroll County showed improvement from 2022 to 2023. Total crashes decreased by 7.7%, from 221 to 204 incidents. This downward trend was also reflected in crash outcomes, with total injuries declining by 24.4% and fatalities falling from 4 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 4↓-25.0%

2

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 1↑100.0%

61

Motorists Injured

Prior: 85↓-28.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Carroll County remained relatively consistent year-over-year. In 2023, Wednesday was the peak day for crashes with 41 incidents, similar to 2022 where Wednesday and Friday were tied as the peak days with 40 crashes each. The peak hour for collisions shifted slightly from 2 p.m. in 2022 (22 crashes) to 3 p.m. in 2023 (20 crashes), keeping the afternoon as the highest-risk time period.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity improved from 2022 to 2023. The number of fatal crashes decreased from 4 to 3, with the corresponding share of total crashes dropping from 1.8% to 1.5%. The proportion of crashes involving any injury (serious, minor, or possible) also declined from 32.1% in 2022 to 24.5% in 2023, while crashes resulting in no injuries increased their share from 66.1% to 74.0% of all incidents.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.5%
↓-25.0%prior 4
Serious Injury8serious injury crashes3.9%
→0.0%prior 8
Minor Injury22minor injury crashes10.8%
↓-21.4%prior 28
Possible Injury20possible injury crashes9.8%
↓-42.9%prior 35
No Injury151no injury crashes74%
↑3.4%prior 146

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between 2022 and 2023. In 2023, "Followed too close" was the most common factor with 16 crashes, an increase from 14 in the prior year. "FTYROW: From stop sign," which was the top factor in 2022 with 22 crashes, saw a 36.4% decrease in count to 14 crashes in 2023, moving it to the third-ranked factor.

Officer-Reported Primary Contributing Cause

Followed too close16 (7.8%)↑14.3%prior 14
Other (explain in narrative): Other15 (7.4%)↓-11.8%prior 17
FTYROW: From stop sign14 (6.9%)↓-36.4%prior 22
Ran off road - left13 (6.4%)↓-13.3%prior 15
Driving too fast for conditions13 (6.4%)↑30.0%prior 10
Lost Control13 (6.4%)↑30.0%prior 10
Animal11 (5.4%)→0.0%prior 11
Driver Distraction: Other interior distraction11 (5.4%)↑57.1%prior 7
Ran Stop Sign9 (4.4%)→0.0%prior 9
FTYROW: Making left turn9 (4.4%)↑12.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The environmental conditions for crashes were broadly similar year-over-year, with the majority of incidents in both periods occurring in daylight on dry roads. In 2023, 73.5% of crashes happened on dry surfaces, a slight increase from 69.7% in 2022. Crashes during adverse weather conditions like rain or snow constituted a slightly smaller share of the total in 2023 (8.8%) compared to 2022 (10.8%). The proportion of crashes occurring in dark conditions increased slightly from 20.8% to 22.5%.

Weather

Clear144 (71.6%)
↓-13.8%prior 167
Cloudy36 (17.9%)
↑63.6%prior 22
Rain8 (4.0%)
↑33.3%prior 6
Snow6 (3.0%)
↓-33.3%prior 9
Fog, smoke, smog3 (1.5%)
Freezing rain/drizzle3 (1.5%)
↓-50.0%prior 6
Other (explain in narrative)1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight142 (70.6%)
↓-12.3%prior 162
Dark - roadway not lighted30 (14.9%)
↑15.4%prior 26
Dark - roadway lighted14 (7.0%)
↓-30.0%prior 20
Dusk11 (5.5%)
Dawn2 (1.0%)
Dark - unknown roadway lighting2 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry150 (74.3%)
↓-2.6%prior 154
Wet19 (9.4%)
↓-13.6%prior 22
Ice/frost15 (7.4%)
↑15.4%prior 13
Gravel11 (5.4%)
↓-15.4%prior 13
Snow7 (3.5%)
↓-22.2%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes showed some consistency, with CHEV (84 vehicles) and FORD (57 vehicles) leading in 2023, similar to 2022. The demographic profile of persons involved in crashes shifted, with a notable increase in the share of individuals aged 26-34, from 12.5% in 2022 to 17.2% in 2023. Conversely, the proportion of persons in the 16-20 age group decreased from 16.3% to 12.7% over the same period.

Top Vehicle Makes (349 vehicles)

1
CHEV84 (24.1%)
→0.0%prior 84
2
FORD57 (16.3%)
↑7.5%prior 53
3
GMC20 (5.7%)
↑81.8%prior 11
4
CHEVROLET18 (5.2%)
↓-37.9%prior 29
5
TOYT15 (4.3%)
↓-11.8%prior 17
6
JEEP13 (3.7%)
↓-23.5%prior 17
7
NISS11 (3.2%)
↓-21.4%prior 14
8
BUIC10 (2.9%)
↓-16.7%prior 12
9
TOYO10 (2.9%)
↓-23.1%prior 13
10
NR9 (2.6%)
↑12.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (319 persons with recorded sex)

Male173 (54.2%)
↓-11.3%prior 195
Female146 (45.8%)
↓-8.2%prior 159

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 204
  • Total persons involved: 441
  • Total vehicles involved: 349

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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