Yearly Traffic Safety Analysis

2,346 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Johnson County, total traffic crashes decreased by 2.1% from 2,395 in 2022 to 2,346 in 2023. Despite the overall reduction in crashes, the most significant year-over-year change was a doubling in the number of fatalities, which rose from 5 to 10.

2,346

▼ -2.0%was 2,395

Total Crash Events

10

▲ 100.0%was 5

Persons Killed

641

▲ 3.1%was 622

Persons Injured

9

▲ 80.0%was 5

Fatal Crash Events

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Johnson County saw a minor decrease of 2.1% from 2022 to 2023. However, the severity of crashes increased, as total fatalities doubled from 5 to 10 and the number of serious injury crashes rose by 56% from 25 to 39.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

8

Motorists Killed

Prior: 5↑60.0%

0

Other Killed

Prior: 0→0.0%

19

Pedestrians Injured

Prior: 30↓-36.7%

25

Cyclists Injured

Prior: 26↓-3.8%

594

Motorists Injured

Prior: 565↑5.1%

3

Other Injured

Prior: 1↑200.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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 year-over-year, with Friday being the peak day for crashes in both 2022 (438 crashes) and 2023 (410 crashes). The peak hour for collisions shifted slightly earlier, from 5 p.m. in 2022 (240 crashes) to 4 p.m. in 2023 (238 crashes). Weekday afternoon commute hours continued to be the period with the highest crash frequency in both years.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2023 compared to the prior year. The number of fatal crashes increased from 5 to 9, and the total number of fatalities doubled from 5 to 10. Similarly, serious injury crashes rose from 25 to 39, a 56% increase. Consequently, the proportion of crashes resulting in no injury decreased slightly from 77.1% in 2022 to 76.6% in 2023.

Severity is per crash event (most severe injury). 9 fatal crash events resulted in 10 persons killed.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.4%
↑80.0%prior 5
Serious Injury39serious injury crashes1.7%
↑56.0%prior 25
Minor Injury212minor injury crashes9%
↓-4.9%prior 223
Possible Injury290possible injury crashes12.4%
↓-2.0%prior 296
No Injury1,796no injury crashes76.6%
↓-2.7%prior 1,846

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

In 2023, 'Followed too close' was the leading contributing factor, with its count increasing by 27.1% from 347 to 441 crashes, representing 18.8% of all crashes. Conversely, 'Driving too fast for conditions,' the second-ranked factor in 2022 with 193 crashes, saw its count drop by 44.6% to 107 crashes in 2023, falling to the fifth-ranked position. The rankings of top factors shifted, with 'Ran off road - left' and 'Animal' becoming more prominent in the top five for 2023.

Officer-Reported Primary Contributing Cause

Followed too close441 (18.8%)↑27.1%prior 347
Other (explain in narrative): Other155 (6.6%)↓-4.3%prior 162
Ran off road - left135 (5.8%)↓-13.5%prior 156
Animal129 (5.5%)↑4.9%prior 123
Driving too fast for conditions107 (4.6%)↓-44.6%prior 193
Improper or erratic lane changing97 (4.1%)↑15.5%prior 84
FTYROW: Making left turn97 (4.1%)↓-1.0%prior 98
Ran Traffic Signal91 (3.9%)↑12.3%prior 81
Driver Distraction: Other interior distraction88 (3.8%)↑31.3%prior 67
Made improper turn88 (3.8%)↑15.8%prior 76

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in 2023 were more likely to occur in clear conditions compared to 2022. There was a substantial decrease in crashes occurring on adverse road surfaces, with incidents on snow, ice, or slush surfaces dropping from 328 in 2022 to 157 in 2023. Similarly, crashes on dark, unlit roadways decreased from 243 to 151, indicating a shift towards crashes occurring in seemingly ideal road and weather conditions.

Weather

Clear1,651 (72.9%)
↑2.1%prior 1,617
Cloudy381 (16.8%)
↑16.9%prior 326
Rain102 (4.5%)
↓-30.1%prior 146
Snow98 (4.3%)
↓-23.4%prior 128
Freezing rain/drizzle18 (0.8%)
↓-48.6%prior 35
Fog, smoke, smog6 (0.3%)
Blowing Snow3 (0.1%)
↓-94.4%prior 54
Severe Winds3 (0.1%)
↓-70.0%prior 10
Sleet, hail2 (0.1%)
Other (explain in narrative)2 (0.1%)
↓-75.0%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight1,691 (74.1%)
↑2.5%prior 1,649
Dark - roadway lighted323 (14.2%)
↑0.3%prior 322
Dark - roadway not lighted151 (6.6%)
↓-37.9%prior 243
Dusk66 (2.9%)
↓-13.2%prior 76
Dawn35 (1.5%)
↓-7.9%prior 38
Dark - unknown roadway lighting15 (0.7%)
↑36.4%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry1,872 (82.4%)
↑8.0%prior 1,734
Wet230 (10.1%)
↓-9.8%prior 255
Snow84 (3.7%)
↓-45.8%prior 155
Ice/frost48 (2.1%)
↓-69.8%prior 159
Slush25 (1.1%)
↑78.6%prior 14
Gravel9 (0.4%)
↓-18.2%prior 11
Sand2 (0.1%)
Water (standing or moving)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, including Ford, Chevrolet, and Toyota, remained consistent in ranking and volume between 2022 and 2023. Regarding driver demographics, the most notable shift occurred in the 55-64 age group, where the number of persons involved in crashes increased by 21.8%, from 464 in 2022 to 565 in 2023. Other age groups showed more stable year-over-year involvement.

Top Vehicle Makes (4,400 vehicles)

1
FORD601 (13.7%)
↓-1.5%prior 610
2
CHEV424 (9.6%)
↑12.8%prior 376
3
TOYT374 (8.5%)
↓-0.3%prior 375
4
HOND284 (6.5%)
↑16.4%prior 244
5
NISS183 (4.2%)
↑22.8%prior 149
6
JEEP178 (4%)
↑29.0%prior 138
7
TOYOTA155 (3.5%)
↑8.4%prior 143
8
CHEVROLET142 (3.2%)
↓-22.8%prior 184
9
KIA118 (2.7%)
↓-15.1%prior 139
10
DODG118 (2.7%)
↓-14.5%prior 138

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (4,039 persons with recorded sex)

Male2,220 (55.0%)
↑0.1%prior 2,217
Female1,819 (45.0%)
↑0.2%prior 1,815

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,346
  • Total persons involved: 5,339
  • Total vehicles involved: 4,400

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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

ThatCarHitMe.com · An Injuria.ai Company