Yearly Traffic Safety Analysis

2,311 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Woodbury County, total crashes increased from 2,258 in 2022 to 2,311 in 2023, a 2.4% rise. The most significant year-over-year change was in crash lethality, with the number of fatal crashes doubling from 4 to 8 and total fatalities increasing from 5 to 9.

2,311

▲ 2.3%was 2,258

Total Crash Events

9

▲ 80.0%was 5

Persons Killed

782

▲ 0.1%was 781

Persons Injured

8

▲ 100.0%was 4

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 crash volume in Woodbury County showed a slight increase year-over-year. Total crashes rose by 2.4%, from 2,258 in 2022 to 2,311 in 2023. While the number of total injuries remained stable with a change of just one person (from 781 to 782), total fatalities increased by 80% from 5 to 9.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

9

Motorists Killed

Prior: 3↑200.0%

31

Pedestrians Injured

Prior: 22↑40.9%

11

Cyclists Injured

Prior: 15↓-26.7%

740

Motorists Injured

Prior: 741↓-0.1%

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

Temporal crash patterns remained largely consistent between 2022 and 2023. The peak day for crashes in both periods was Friday, with 370 crashes in 2023 compared to 375 in 2022. Similarly, the 3 PM hour was the peak time for collisions in both years, recording 209 crashes in 2023 and 211 in the prior year.

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

The severity of crashes worsened in 2023 compared to the previous year. The number of fatal crashes doubled from 4 to 8, and crashes involving serious injuries increased by 65% from 20 to 33. Consequently, the fatal crash rate rose from 0.18% to 0.35%. Conversely, crashes resulting in minor injuries decreased from 233 in 2022 to 192 in 2023.

Severity is per crash event (most severe injury). 8 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.3%
↑100.0%prior 4
Serious Injury33serious injury crashes1.4%
↑65.0%prior 20
Minor Injury192minor injury crashes8.3%
↓-17.6%prior 233
Possible Injury513possible injury crashes22.2%
↓-0.4%prior 515
No Injury1,565no injury crashes67.7%
↑5.3%prior 1,486

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 were similar in both periods, with 'Followed too close' remaining the top factor, increasing in count from 240 to 254. While 'Ran off road - left' and 'FTYROW: From stop sign' remained in the top three, their counts decreased by 7.8% and 10.6%, respectively. Notably, crashes attributed to 'Ran Traffic Signal' increased by 13.6% from 140 to 159, while those involving 'Driving too fast for conditions' saw a 24.1% reduction in count, from 112 to 85.

Officer-Reported Primary Contributing Cause

Followed too close254 (11%)↑5.8%prior 240
Ran off road - left190 (8.2%)↓-7.8%prior 206
FTYROW: From stop sign178 (7.7%)↓-10.6%prior 199
Ran Traffic Signal159 (6.9%)↑13.6%prior 140
FTYROW: Making left turn134 (5.8%)↑15.5%prior 116
Other (explain in narrative): Other128 (5.5%)↓-7.9%prior 139
Animal107 (4.6%)↑10.3%prior 97
Made improper turn88 (3.8%)↑4.8%prior 84
Driving too fast for conditions85 (3.7%)↓-24.1%prior 112
Ran Stop Sign81 (3.5%)↑6.6%prior 76

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 majority of crashes in both 2023 and 2022 occurred in clear weather and daylight on dry roads. In 2023, 70.0% of crashes happened in clear weather, compared to 68.9% in 2022. There was a notable decrease in crashes on roads with ice or frost (from 133 to 93). Conversely, crashes on wet road surfaces increased from 196 in 2022 to 262 in 2023.

Weather

Clear1,617 (73.4%)
↑3.9%prior 1,556
Cloudy377 (17.1%)
↑8.3%prior 348
Rain83 (3.8%)
↑10.7%prior 75
Snow62 (2.8%)
↓-27.1%prior 85
Freezing rain/drizzle30 (1.4%)
↓-36.2%prior 47
Fog, smoke, smog14 (0.6%)
↑40.0%prior 10
Blowing Snow9 (0.4%)
↓-70.0%prior 30
Sleet, hail5 (0.2%)
Other (explain in narrative)3 (0.1%)
Blowing sand, soil, dirt2 (0.1%)

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

Lighting

Daylight1,578 (71.1%)
↑6.3%prior 1,485
Dark - roadway lighted423 (19.1%)
↓-3.2%prior 437
Dark - roadway not lighted123 (5.5%)
↓-12.8%prior 141
Dusk48 (2.2%)
↓-29.4%prior 68
Dawn40 (1.8%)
↑2.6%prior 39
Dark - unknown roadway lighting6 (0.3%)

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

Road Surface

Dry1,695 (76.5%)
↑0.5%prior 1,686
Wet262 (11.8%)
↑33.7%prior 196
Snow104 (4.7%)
↓-8.0%prior 113
Ice/frost93 (4.2%)
↓-30.1%prior 133
Slush43 (1.9%)
↑95.5%prior 22
Gravel13 (0.6%)
↓-27.8%prior 18
Other (explain in narrative)3 (0.1%)
Mud, dirt2 (0.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Ford and Chevrolet being the most common in both years. In 2023, 635 Fords and 824 Chevrolets (combining 'CHEV' and 'CHEVROLET' entries) were involved in collisions, compared to 625 Fords and 809 Chevrolets in 2022. Analysis of person data shows a notable increase in individuals aged 16-20 involved in crashes, rising from 600 in 2022 to 734 in 2023, while the 26-34 age group saw a decrease from 795 to 757.

Top Vehicle Makes (4,325 vehicles)

1
FORD635 (14.7%)
↑1.6%prior 625
2
CHEV545 (12.6%)
↑8.6%prior 502
3
CHEVROLET279 (6.5%)
↓-9.1%prior 307
4
JEEP215 (5%)
↑8.6%prior 198
5
GMC193 (4.5%)
↑5.5%prior 183
6
NR163 (3.8%)
↑7.2%prior 152
7
HOND158 (3.7%)
↑0.6%prior 157
8
KIA157 (3.6%)
↓-6.0%prior 167
9
DODG145 (3.4%)
↑4.3%prior 139
10
TOYT134 (3.1%)
↓-5.6%prior 142

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

1,182 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (3,653 persons with recorded sex)

Male2,080 (56.9%)
↑6.8%prior 1,947
Female1,573 (43.1%)
↑1.5%prior 1,549

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: 2,311
  • Total persons involved: 5,747
  • Total vehicles involved: 4,325

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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