Yearly Traffic Safety Analysis

2,069 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Pottawattamie County, total traffic crashes decreased by 3.2% from 2,138 in 2021 to 2,069 in 2022. Despite this overall reduction, the number of people injured increased by 5.0% from 694 to 729. The most notable year-over-year shift was a 22.9% increase in the number of serious injury crashes, which rose from 35 to 43, even as the number of fatal crashes remained unchanged at 10.

2,069

▼ -3.2%was 2,138

Total Crash Events

10

Persons Killed

729

▲ 5.0%was 694

Persons Injured

10

Fatal Crash Events

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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

The overall trend in Pottawattamie County shows a decrease in the total volume of crashes, which fell from 2,138 in 2021 to 2,069 in 2022. In contrast to the drop in total incidents, the number of resulting injuries rose by 5.0% from 694 to 729. The number of fatalities remained stable at 10 for both years.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 0→%

9

Motorists Killed

Prior: 10↓-10.0%

0

Other Killed

Prior: 0→0.0%

23

Pedestrians Injured

Prior: 17↑35.3%

17

Cyclists Injured

Prior: 6↑183.3%

688

Motorists Injured

Prior: 670↑2.7%

1

Other Injured

Prior: 1→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 primary temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both 2022 (350 crashes) and 2021 (431 crashes), though the volume on Fridays decreased. The 4 p.m. hour was the peak hour in both periods, with a slight increase in incidents from 169 in 2021 to 177 in 2022. No significant shifts in the daily or hourly distribution of crashes were observed.

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

While the number of fatal crashes (10) and the fatal crash rate (0.5%) were identical in 2022 and 2021, the severity of non-fatal crashes worsened. The count of serious injury crashes increased from 35 to 43, raising their share of all crashes from 1.6% to 2.1%. Overall, the proportion of crashes resulting in any level of injury—possible, minor, serious, or fatal—increased from 30.0% in 2021 to 31.7% in 2022.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.5%
→0.0%prior 10
Serious Injury43serious injury crashes2.1%
↑22.9%prior 35
Minor Injury184minor injury crashes8.9%
↑5.1%prior 175
Possible Injury418possible injury crashes20.2%
↓-0.7%prior 421
No Injury1,414no injury crashes68.3%
↓-5.5%prior 1,497

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 saw some shifts between 2021 and 2022. "Followed too close" remained the top factor, with a stable count of 291 in 2021 and 294 in 2022. The count of crashes attributed to "Lost Control" increased by 16.0%, from 119 to 138 incidents, moving it from the fourth to the third-ranked cause. Crashes involving "Ran Traffic Signal" also increased notably, rising 14.6% from 89 to 102 incidents and entering the top five factors in 2022.

Officer-Reported Primary Contributing Cause

Followed too close294 (14.2%)↑1.0%prior 291
Ran off road - left172 (8.3%)↓-9.5%prior 190
Lost Control138 (6.7%)↑16.0%prior 119
Animal127 (6.1%)↓-11.2%prior 143
Ran Traffic Signal102 (4.9%)↑14.6%prior 89
FTYROW: From stop sign99 (4.8%)↓-2.0%prior 101
Other (explain in narrative): Other84 (4.1%)↑20.0%prior 70
Ran off road - straight77 (3.7%)↓-21.4%prior 98
Ran Stop Sign77 (3.7%)↓-15.4%prior 91
FTYROW: Making left turn76 (3.7%)↑5.6%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 were largely consistent year-over-year, with the majority of incidents in both periods occurring in clear weather and on dry roads. The proportion of crashes on dry surfaces increased slightly from 74.9% in 2021 to 76.1% in 2022. A notable shift occurred in lighting conditions, as crashes in dark, unlighted areas increased by 12.4%, from 178 incidents in 2021 to 200 in 2022.

Weather

Clear1,495 (76.3%)
→0.0%prior 1,495
Cloudy243 (12.4%)
↓-12.6%prior 278
Rain76 (3.9%)
↓-16.5%prior 91
Snow74 (3.8%)
↓-2.6%prior 76
Freezing rain/drizzle31 (1.6%)
↑3.3%prior 30
Blowing Snow18 (0.9%)
↓-18.2%prior 22
Severe Winds12 (0.6%)
↑33.3%prior 9
Fog, smoke, smog7 (0.4%)
↑40.0%prior 5
Other (explain in narrative)3 (0.2%)
Sleet, hail1 (0.1%)

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

Lighting

Daylight1,307 (66.5%)
↓-3.3%prior 1,352
Dark - roadway lighted364 (18.5%)
↓-2.2%prior 372
Dark - roadway not lighted200 (10.2%)
↑12.4%prior 178
Dusk44 (2.2%)
↓-41.3%prior 75
Dawn40 (2.0%)
↑8.1%prior 37
Dark - unknown roadway lighting11 (0.6%)
↓-8.3%prior 12

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

Road Surface

Dry1,574 (80.3%)
↓-1.7%prior 1,601
Wet177 (9.0%)
↓-8.3%prior 193
Ice/frost87 (4.4%)
↓-15.5%prior 103
Snow85 (4.3%)
↓-2.3%prior 87
Gravel29 (1.5%)
↑61.1%prior 18
Slush5 (0.3%)
→0.0%prior 5
Mud, dirt2 (0.1%)
Sand1 (0.1%)
Other (explain in narrative)1 (0.1%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, remained the same in both 2022 and 2021, though both makes saw a decrease in their total number of crashes. Analysis of persons involved in crashes reveals a significant demographic shift; the number of individuals in the 35-44 age group increased by 18.0% from 604 to 713. Conversely, involvement for the 16-20 age group decreased from 548 persons in 2021 to 505 in 2022.

Top Vehicle Makes (3,644 vehicles)

1
FORD512 (14.1%)
↓-9.5%prior 566
2
CHEV327 (9%)
↑16.4%prior 281
3
CHEVROLET286 (7.8%)
↓-22.1%prior 367
4
KIA144 (4%)
↑5.9%prior 136
5
NR141 (3.9%)
↓-18.0%prior 172
6
JEEP136 (3.7%)
↓-13.4%prior 157
7
TOYOTA124 (3.4%)
↑1.6%prior 122
8
NISS123 (3.4%)
↑23.0%prior 100
9
GMC114 (3.1%)
↑18.8%prior 96
10
NISSAN112 (3.1%)
↓-24.3%prior 148

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

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

Sex Distribution (3,121 persons with recorded sex)

Male1,849 (59.2%)
↑6.9%prior 1,730
Female1,272 (40.8%)
↑4.5%prior 1,217

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: 2,069
  • Total persons involved: 4,882
  • Total vehicles involved: 3,644

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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