Yearly Traffic Safety Analysis

55 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Audubon County recorded 55 total crashes, a 6.8% decrease from the 59 crashes reported in 2021. While overall crashes declined slightly, the number of crashes involving a driver under the influence of alcohol increased from 2 in 2021 to 5 in 2022.

55

▼ -6.8%was 59

Total Crash Events

2

Persons Killed

30

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 crashes in Audubon County saw a slight decrease in 2022, falling by 4 incidents from 59 in 2021 to 55. Despite this drop in total collisions, the number of resulting fatalities and injuries remained unchanged, with 2 fatalities and 30 injuries recorded in both periods.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

30

Motorists Injured

Prior: 30→0.0%

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 some shifts between the two years. While Saturday remained the day with the most crashes in both 2022 (11 crashes) and 2021 (16 crashes), the peak hour for collisions moved earlier in the day. In 2022, the most crashes occurred at 5 p.m. (7 crashes), a shift from the 9 p.m. peak observed in 2021 (8 crashes).

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

The number of fatal crashes remained constant at 2 in both 2022 and 2021, though the fatal crash rate per 100 crashes increased slightly from 3.39 to 3.64. The distribution of injury severity shifted; serious injury crashes decreased from 6 to 4, while minor injury crashes increased from 6 to 11. The proportion of crashes resulting in no injury was stable, accounting for 60% of crashes in 2022 compared to 59.3% in 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes3.6%
→0.0%prior 2
Serious Injury4serious injury crashes7.3%
↓-33.3%prior 6
Minor Injury11minor injury crashes20%
↑83.3%prior 6
Possible Injury5possible injury crashes9.1%
↓-50.0%prior 10
No Injury33no injury crashes60%
↓-5.7%prior 35

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

Collisions involving an animal remained the top contributing factor in both periods, though the count decreased from 15 crashes in 2021 to 12 in 2022. 'Lost Control' was the second most common factor, increasing slightly from 7 incidents to 8. Crashes attributed to 'Driving too fast for conditions' saw a notable decrease, falling from 5 incidents in 2021 to 3 in 2022.

Officer-Reported Primary Contributing Cause

Animal12 (21.8%)↓-20.0%prior 15
Lost Control8 (14.5%)↑14.3%prior 7
FTYROW: From stop sign3 (5.5%)
Driving too fast for conditions3 (5.5%)↓-40.0%prior 5
Crossed centerline (undivided)2 (3.6%)
Driver Distraction: Exterior distraction2 (3.6%)
FTYROW: From driveway2 (3.6%)
FTYROW: From parked position2 (3.6%)
Other (explain in narrative): Other2 (3.6%)
Ran off road - left2 (3.6%)

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

Road & Environmental Conditions

Crashes in 2022 occurred more frequently under favorable conditions compared to the prior year. Collisions during daylight hours increased from 27 to 34, and those on dry roads rose from 28 to 34. Correspondingly, crashes on road surfaces with snow decreased from 5 incidents in 2021 to 2 in 2022.

Weather

Clear38 (82.6%)
↑18.8%prior 32
Cloudy8 (17.4%)
→0.0%prior 8

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

Lighting

Daylight34 (73.9%)
↑25.9%prior 27
Dark - roadway not lighted8 (17.4%)
↓-20.0%prior 10
Dark - roadway lighted2 (4.3%)
↓-60.0%prior 5
Dusk2 (4.3%)

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

Road Surface

Dry34 (73.9%)
↑21.4%prior 28
Gravel7 (15.2%)
↑40.0%prior 5
Snow2 (4.3%)
↓-60.0%prior 5
Wet2 (4.3%)
Ice/frost1 (2.2%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most common makes involved in crashes in both periods, with Ford's involvement increasing from 13 vehicles in 2021 to 18 in 2022. The age demographics of persons involved in crashes shifted significantly. The number of persons in the 16-20 and 65+ age groups both increased, from 18 to 24 and 16 to 24, respectively. Meanwhile, the 35-44 age group saw a decrease in involvement from 22 persons in 2021 to 6 in 2022.

Top Vehicle Makes (77 vehicles)

1
FORD18 (23.4%)
↑38.5%prior 13
2
CHEV16 (20.8%)
↑60.0%prior 10
3
DODG6 (7.8%)
4
CHEVROLET4 (5.2%)
↓-33.3%prior 6
5
JEEP3 (3.9%)
6
DODGE3 (3.9%)
7
RAM2 (2.6%)
8
GMC2 (2.6%)
9
BUICK2 (2.6%)
10
BUIC2 (2.6%)

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

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

Sex Distribution (74 persons with recorded sex)

Male47 (63.5%)
↓-2.1%prior 48
Female27 (36.5%)
↑42.1%prior 19

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: 55
  • Total persons involved: 122
  • Total vehicles involved: 77

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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