Yearly Traffic Safety Analysis

2,395 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Johnson County recorded 2,395 total crashes, a 1.9% increase from the 2,351 crashes reported in 2021. Despite the rise in total incidents, the number of fatalities decreased significantly from 9 in the prior year to 5 in the current year. Overall injuries remained relatively stable, increasing from 615 to 622 year-over-year.

2,395

▲ 1.9%was 2,351

Total Crash Events

5

▼ -44.4%was 9

Persons Killed

622

▲ 1.1%was 615

Persons Injured

5

▼ -44.4%was 9

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 traffic crashes in Johnson County shows a slight increase year-over-year. Total crashes rose from 2,351 in 2021 to 2,395 in 2022, representing a 1.9% increase. While total crashes went up, fatalities saw a notable decrease of 44.4%, from 9 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 2↓-100.0%

0

Cyclists Killed

Prior: 1↓-100.0%

5

Motorists Killed

Prior: 6↓-16.7%

0

Other Killed

Prior: 0→0.0%

30

Pedestrians Injured

Prior: 17↑76.5%

26

Cyclists Injured

Prior: 19↑36.8%

565

Motorists Injured

Prior: 575↓-1.7%

1

Other Injured

Prior: 4↓-75.0%

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 remained largely consistent between 2021 and 2022. Friday continued to be the peak day for crashes in both periods, with incidents increasing from 400 to 438. Similarly, the 5 p.m. hour remained the peak time for collisions, rising from 216 incidents in 2021 to 240 in 2022. The afternoon commute, particularly from 3 p.m. to 5 p.m., consistently represented the most frequent time for crashes in both years.

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 overall severity of crashes in Johnson County lessened from 2021 to 2022. The number of fatal crashes decreased from 9 to 5, and their share of all crashes fell from 0.4% to 0.2%. Serious injury crashes also declined in count from 32 to 25. Conversely, the number of crashes resulting in no injuries increased from 1,802 to 1,846, making up 77.1% of all crashes in 2022 compared to 76.6% in the prior year.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.2%
↓-44.4%prior 9
Serious Injury25serious injury crashes1%
↓-21.9%prior 32
Minor Injury223minor injury crashes9.3%
↑8.3%prior 206
Possible Injury296possible injury crashes12.4%
↓-2.0%prior 302
No Injury1,846no injury crashes77.1%
↑2.4%prior 1,802

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

Following too closely was the leading contributing factor in both periods, though its count decreased from 399 incidents in 2021 to 347 in 2022. The second-most cited factor, 'Driving too fast for conditions,' saw an increase in count from 173 to 193. Crashes attributed to 'Ran off road - left' declined from 166 to 156, while incidents involving animals increased from 111 to 123.

Officer-Reported Primary Contributing Cause

Followed too close347 (14.5%)↓-13.0%prior 399
Driving too fast for conditions193 (8.1%)↑11.6%prior 173
Other (explain in narrative): Other162 (6.8%)↑11.7%prior 145
Ran off road - left156 (6.5%)↓-6.0%prior 166
Animal123 (5.1%)↑10.8%prior 111
FTYROW: Making left turn98 (4.1%)↑36.1%prior 72
FTYROW: From stop sign94 (3.9%)↑11.9%prior 84
Improper or erratic lane changing84 (3.5%)↓-12.5%prior 96
Lost Control82 (3.4%)↑9.3%prior 75
Ran Traffic Signal81 (3.4%)↓-3.6%prior 84

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 environmental conditions under which crashes occurred saw minimal changes between 2021 and 2022. In both years, the majority of crashes happened in daylight on dry roads. In 2022, 67.5% of crashes occurred in clear weather, compared to 66.7% in 2021. Crashes on dry road surfaces accounted for 72.4% of the total in 2022, nearly identical to the 71.8% recorded in the prior year. The proportion of crashes happening after dark also remained stable, accounting for 23.6% of incidents in 2022 versus 21.6% in 2021.

Weather

Clear1,617 (69.5%)
↑3.1%prior 1,569
Cloudy326 (14.0%)
↓-18.5%prior 400
Rain146 (6.3%)
↑20.7%prior 121
Snow128 (5.5%)
↑25.5%prior 102
Blowing Snow54 (2.3%)
↑170.0%prior 20
Freezing rain/drizzle35 (1.5%)
↑6.1%prior 33
Severe Winds10 (0.4%)
↑100.0%prior 5
Other (explain in narrative)8 (0.3%)
Sleet, hail3 (0.1%)
↓-62.5%prior 8
Fog, smoke, smog1 (0.0%)
↓-94.7%prior 19

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

Lighting

Daylight1,649 (70.5%)
↓-1.8%prior 1,680
Dark - roadway lighted322 (13.8%)
↑15.4%prior 279
Dark - roadway not lighted243 (10.4%)
↑6.6%prior 228
Dusk76 (3.2%)
↑35.7%prior 56
Dawn38 (1.6%)
↑18.8%prior 32
Dark - unknown roadway lighting11 (0.5%)
→0.0%prior 11

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

Road Surface

Dry1,734 (74.4%)
↑2.7%prior 1,689
Wet255 (10.9%)
↓-2.3%prior 261
Ice/frost159 (6.8%)
↑28.2%prior 124
Snow155 (6.6%)
↑6.2%prior 146
Slush14 (0.6%)
↓-64.1%prior 39
Gravel11 (0.5%)
↓-45.0%prior 20
Other (explain in narrative)4 (0.2%)

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 consistent, with Ford (as FORD), Chevrolet (as CHEV), and Toyota (as TOYT) being the top three in both 2021 and 2022. Ford-made vehicles were involved in 610 crashes in 2022, down from 637, while CHEV- and TOYT-involved crashes increased. An analysis of persons involved shows increases across several age demographics, most notably the 65+ age group, which saw its involvement rise from 435 individuals in 2021 to 549 in 2022.

Top Vehicle Makes (4,419 vehicles)

1
FORD610 (13.8%)
↓-4.2%prior 637
2
CHEV376 (8.5%)
↑10.3%prior 341
3
TOYT375 (8.5%)
↑16.8%prior 321
4
HOND244 (5.5%)
↑44.4%prior 169
5
CHEVROLET184 (4.2%)
↓-33.6%prior 277
6
NISS149 (3.4%)
↑20.2%prior 124
7
TOYOTA143 (3.2%)
↓-31.9%prior 210
8
KIA139 (3.1%)
↑35.0%prior 103
9
JEEP138 (3.1%)
↓-8.0%prior 150
10
DODG138 (3.1%)
↑35.3%prior 102

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

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

Sex Distribution (4,032 persons with recorded sex)

Male2,217 (55.0%)
↑3.4%prior 2,145
Female1,815 (45.0%)
↑10.2%prior 1,647

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: 2,395
  • Total persons involved: 5,395
  • Total vehicles involved: 4,419

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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