Yearly Traffic Safety Analysis

296 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Dickinson County recorded 296 total crashes, a 5.0% increase from the 282 crashes reported in 2021. Despite the rise in total incidents, the outcomes were less severe, with total fatalities decreasing from three to one and the number of people injured falling from 107 to 92. A notable trend was the decrease in crashes involving a driver under the influence, which fell from 28 in 2021 to 17 in 2022.

296

▲ 5.0%was 282

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

92

▼ -14.0%was 107

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 Dickinson County increased by 5.0% in 2022 compared to the prior year, rising from 282 to 296 incidents. However, the severity of these crashes lessened, with total fatalities declining from three to one and the number of people injured decreasing by 14.0% from 107 to 92.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

3

Pedestrians Injured

Prior: 1↑200.0%

1

Cyclists Injured

Prior: 0→%

88

Motorists Injured

Prior: 105↓-16.2%

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 peak hour for crashes remained consistent year-over-year, with the 3 p.m. hour seeing the most incidents in both 2022 (29 crashes) and 2021 (25 crashes). The peak day of the week for crashes shifted, moving from Saturday (51 crashes) in 2021 to Monday (52 crashes) in 2022.

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 proportion of crashes resulting in no injuries increased from 69.1% in 2021 to 73.3% in 2022. Correspondingly, the share of crashes involving any level of injury (Serious, Minor, or Possible) decreased from 30.5% of all crashes in 2021 to 26.4% in 2022. While both years recorded one fatal crash event, the total number of fatalities fell from three in 2021 to one in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
→0.0%prior 1
Serious Injury14serious injury crashes4.7%
↑16.7%prior 12
Minor Injury24minor injury crashes8.1%
↓-25.0%prior 32
Possible Injury40possible injury crashes13.5%
↓-4.8%prior 42
No Injury217no injury crashes73.3%
↑11.3%prior 195

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

"Followed too close" was the leading contributing factor in both periods, though its count decreased from 49 incidents in 2021 to 41 in 2022. Crashes attributed to "Driving too fast for conditions" saw a notable increase in count, rising from 14 incidents to 22, which moved it to the second-highest rank in 2022. Conversely, collisions where an "Animal" was a factor decreased from 24 in 2021 to 14 in 2022.

Officer-Reported Primary Contributing Cause

Followed too close41 (13.9%)↓-16.3%prior 49
Driving too fast for conditions22 (7.4%)↑57.1%prior 14
Lost Control20 (6.8%)↑33.3%prior 15
FTYROW: From stop sign19 (6.4%)↓-26.9%prior 26
FTYROW: Making left turn18 (6.1%)↓-14.3%prior 21
Ran off road - left16 (5.4%)↑33.3%prior 12
Other (explain in narrative): Other15 (5.1%)↑114.3%prior 7
Animal14 (4.7%)↓-41.7%prior 24
Ran Stop Sign13 (4.4%)↑30.0%prior 10
Driver Distraction: Other interior distraction11 (3.7%)

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

Road & Environmental Conditions

The majority of crashes in both years occurred in clear weather and on dry roads. However, there was a notable increase in crashes during adverse winter conditions in 2022. Crashes occurring in snow or blowing snow more than doubled, from 13 incidents in 2021 to 33 in 2022. Similarly, collisions on roads with snow, ice, or slush increased from 31 to 57 year-over-year.

Weather

Clear186 (65.7%)
↑8.8%prior 171
Cloudy53 (18.7%)
↑15.2%prior 46
Snow26 (9.2%)
↑225.0%prior 8
Blowing Snow7 (2.5%)
↑40.0%prior 5
Rain6 (2.1%)
↓-68.4%prior 19
Severe Winds2 (0.7%)
Fog, smoke, smog2 (0.7%)
Freezing rain/drizzle1 (0.4%)
↓-87.5%prior 8

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

Lighting

Daylight217 (77.0%)
↑8.5%prior 200
Dark - roadway lighted30 (10.6%)
↑36.4%prior 22
Dark - roadway not lighted27 (9.6%)
↓-6.9%prior 29
Dawn4 (1.4%)
Dusk3 (1.1%)
Dark - unknown roadway lighting1 (0.4%)
↓-83.3%prior 6

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

Road Surface

Dry205 (72.2%)
↑5.7%prior 194
Snow43 (15.1%)
↑168.8%prior 16
Wet17 (6.0%)
↓-50.0%prior 34
Ice/frost14 (4.9%)
↑27.3%prior 11
Gravel5 (1.8%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes for both years, with Ford's involvement decreasing from 83 to 79 vehicles and Chevrolet's combined count falling from 120 to 111. A significant demographic shift occurred among persons involved in crashes; the 16-20 age group saw its involvement increase from 77 individuals in 2021 to 129 in 2022. Conversely, the number of persons aged 65 and older involved in crashes decreased from 100 to 90.

Top Vehicle Makes (527 vehicles)

1
FORD79 (15%)
↓-4.8%prior 83
2
CHEV75 (14.2%)
↑19.0%prior 63
3
TOYT38 (7.2%)
↑90.0%prior 20
4
CHEVROLET36 (6.8%)
↓-36.8%prior 57
5
JEEP29 (5.5%)
↑16.0%prior 25
6
DODG23 (4.4%)
↑130.0%prior 10
7
GMC20 (3.8%)
↓-25.9%prior 27
8
BUIC18 (3.4%)
↑100.0%prior 9
9
CHRY13 (2.5%)
↓-31.6%prior 19
10
TOYO12 (2.3%)
↑100.0%prior 6

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

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

Sex Distribution (477 persons with recorded sex)

Male275 (57.7%)
↑22.2%prior 225
Female202 (42.3%)
↑6.9%prior 189

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: 296
  • Total persons involved: 674
  • Total vehicles involved: 527

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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