Yearly Traffic Safety Analysis

2,258 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Woodbury County, a total of 2,258 vehicle crashes were recorded in 2022, a nearly identical figure to the 2,255 crashes reported in 2021. Despite the stable number of total incidents, the most notable year-over-year change was a significant decrease in traffic fatalities, which fell from 8 in 2021 to 5 in 2022. Correspondingly, the number of fatal crashes dropped from 8 to 4 during the same period.

2,258

▲ 0.1%was 2,255

Total Crash Events

5

▼ -37.5%was 8

Persons Killed

781

▲ 3.6%was 754

Persons Injured

4

▼ -50.0%was 8

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Woodbury County remained stable year-over-year, with total incidents increasing by just 3, from 2,255 in 2021 to 2,258 in 2022. While total crashes were flat, the outcomes shifted, with total injuries rising by 3.6% from 754 to 781, and total fatalities decreasing by 37.5% from 8 to 5.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 7↓-57.1%

1

Other Killed

Prior: 0→%

22

Pedestrians Injured

Prior: 15↑46.7%

15

Cyclists Injured

Prior: 13↑15.4%

741

Motorists Injured

Prior: 726↑2.1%

3

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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 strong consistency between 2022 and 2021. Friday was the peak day for crashes in both years, with 375 incidents in 2022 and 373 in 2021. Similarly, the 3 p.m. hour remained the single hour with the most crashes in both periods, accounting for 211 crashes in 2022 and 196 in 2021. The overall distribution of crashes by day of the week and hour of the day did not change significantly.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

A positive shift was observed in crash severity, with the most severe outcomes decreasing from 2021 to 2022. The fatal crash count was halved, dropping from 8 crashes in 2021 to 4 in 2022, while serious injury crashes fell from 28 to 20. Conversely, crashes resulting in minor injuries increased from 200 to 233, and those with possible injuries rose from 494 to 515. The proportion of crashes with no injuries decreased slightly from 67.6% to 65.8%.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.2%
↓-50.0%prior 8
Serious Injury20serious injury crashes0.9%
↓-28.6%prior 28
Minor Injury233minor injury crashes10.3%
↑16.5%prior 200
Possible Injury515possible injury crashes22.8%
↑4.3%prior 494
No Injury1,486no injury crashes65.8%
↓-2.6%prior 1,525

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes showed some notable shifts between 2021 and 2022. "Followed too close" remained the top-ranked cause in both periods, though its count decreased from 274 to 240. The count of crashes attributed to "FTYROW: From stop sign" grew by 38.2%, from 144 incidents in 2021 to 199 in 2022, moving it from the fifth to the third most common factor. In contrast, crashes involving an "Animal" saw a significant count decrease of 34.9%, falling from 149 in 2021 to 97 in 2022 and dropping out of the top five factors.

Officer-Reported Primary Contributing Cause

Followed too close240 (10.6%)↓-12.4%prior 274
Ran off road - left206 (9.1%)↑10.8%prior 186
FTYROW: From stop sign199 (8.8%)↑38.2%prior 144
Ran Traffic Signal140 (6.2%)↑27.3%prior 110
Other (explain in narrative): Other139 (6.2%)↓-12.6%prior 159
FTYROW: Making left turn116 (5.1%)↓-2.5%prior 119
Driving too fast for conditions112 (5%)↑17.9%prior 95
Lost Control101 (4.5%)↓-9.0%prior 111
Animal97 (4.3%)↓-34.9%prior 149
Made improper turn84 (3.7%)↑16.7%prior 72

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year, with the majority of incidents in both periods occurring under ideal circumstances. In 2022, 68.9% of crashes happened in clear weather, 65.8% in daylight, and 74.7% on dry road surfaces. These proportions are nearly identical to 2021, which saw 67.8% of crashes in clear weather, 64.4% in daylight, and 74.5% on dry roads, indicating no significant shift in the role of adverse conditions.

Weather

Clear1,556 (71.9%)
↑1.8%prior 1,528
Cloudy348 (16.1%)
↓-11.0%prior 391
Snow85 (3.9%)
↓-16.7%prior 102
Rain75 (3.5%)
↓-1.3%prior 76
Freezing rain/drizzle47 (2.2%)
↑235.7%prior 14
Blowing Snow30 (1.4%)
↑76.5%prior 17
Severe Winds11 (0.5%)
Fog, smoke, smog10 (0.5%)
↓-9.1%prior 11
Other (explain in narrative)2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight1,485 (68.3%)
↑2.2%prior 1,453
Dark - roadway lighted437 (20.1%)
↑1.4%prior 431
Dark - roadway not lighted141 (6.5%)
↓-2.8%prior 145
Dusk68 (3.1%)
↑25.9%prior 54
Dawn39 (1.8%)
↓-22.0%prior 50
Dark - unknown roadway lighting3 (0.1%)
↓-72.7%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry1,686 (77.6%)
↑0.3%prior 1,681
Wet196 (9.0%)
↓-8.4%prior 214
Ice/frost133 (6.1%)
↑101.5%prior 66
Snow113 (5.2%)
↓-16.9%prior 136
Slush22 (1.0%)
↓-24.1%prior 29
Gravel18 (0.8%)
↑80.0%prior 10
Mud, dirt3 (0.1%)
Other (explain in narrative)2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained stable between 2021 and 2022. Ford and Chevrolet were the most frequently involved makes in both years, with counts remaining very similar (e.g., Ford-involved vehicles numbered 625 in 2022 vs. 614 in 2021). The age distribution of persons involved in crashes also showed no significant changes, with all age brackets representing a consistent share of the total individuals involved across both periods.

Top Vehicle Makes (4,223 vehicles)

1
FORD625 (14.8%)
↑1.8%prior 614
2
CHEV502 (11.9%)
↑41.4%prior 355
3
CHEVROLET307 (7.3%)
↓-18.6%prior 377
4
JEEP198 (4.7%)
↑3.1%prior 192
5
GMC183 (4.3%)
↑1.1%prior 181
6
KIA167 (4%)
↑21.9%prior 137
7
HOND157 (3.7%)
↑44.0%prior 109
8
NR152 (3.6%)
↓-9.5%prior 168
9
TOYT142 (3.4%)
↑1.4%prior 140
10
DODG139 (3.3%)
↑27.5%prior 109

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

1,275 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (3,496 persons with recorded sex)

Male1,947 (55.7%)
↑10.0%prior 1,770
Female1,549 (44.3%)
↑7.1%prior 1,446

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,258
  • Total persons involved: 5,665
  • Total vehicles involved: 4,223

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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