Yearly Traffic Safety Analysis

2,655 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Johnson County recorded 2,655 vehicle crashes, a 5.7% increase from the 2,513 crashes reported in 2024. Despite the rise in total collisions, the number of fatalities saw a significant year-over-year decrease, dropping from eight in 2024 to one in 2025.

2,655

▲ 5.7%was 2,513

Total Crash Events

1

▼ -87.5%was 8

Persons Killed

654

▼ -7.8%was 709

Persons Injured

1

▼ -87.5%was 8

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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Johnson County increased by 5.7% from 2024 to 2025, rising from 2,513 to 2,655 incidents. However, the outcomes of these crashes were less severe, with total injuries decreasing by 7.8% from 709 to 654. Fatalities fell sharply from eight in the prior year to one in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 1↓-100.0%

1

Motorists Killed

Prior: 6↓-83.3%

0

Other Killed

Prior: 0→0.0%

27

Pedestrians Injured

Prior: 31↓-12.9%

38

Cyclists Injured

Prior: 38→0.0%

584

Motorists Injured

Prior: 628↓-7.0%

5

Other Injured

Prior: 12↓-58.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In 2025, the peak day for crashes was Wednesday with 471 incidents, a change from Monday (412 crashes) in 2024. The peak hour for collisions also shifted slightly earlier, moving from the 5 p.m. hour in 2024 (240 crashes) to the 4 p.m. hour in 2025 (272 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased significantly year-over-year. Fatal crashes dropped from 8 in 2024 to 1 in 2025, and serious injury crashes fell from 59 to 35. Consequently, the proportion of no-injury crashes increased from 75.1% of all incidents in 2024 to 77.7% in 2025, while the share of serious injury crashes declined from 2.3% to 1.3%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0%
↓-87.5%prior 8
Serious Injury35serious injury crashes1.3%
↓-40.7%prior 59
Minor Injury196minor injury crashes7.4%
↓-19.0%prior 242
Possible Injury360possible injury crashes13.6%
↑13.9%prior 316
No Injury2,063no injury crashes77.7%
↑9.3%prior 1,888

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both periods was 'Followed too close,' with incidents increasing by 16.1% from 386 in 2024 to 448 in 2025. 'Driving too fast for conditions' remained the second-most common factor, with its count rising from 200 to 205. The top three primary factors maintained their rankings year-over-year, with each seeing an increase in the number of associated crashes.

Officer-Reported Primary Contributing Cause

Followed too close448 (16.9%)↑16.1%prior 386
Driving too fast for conditions205 (7.7%)↑2.5%prior 200
Ran off road - left172 (6.5%)↑10.3%prior 156
Other (explain in narrative): Other164 (6.2%)↑5.8%prior 155
Animal141 (5.3%)↑25.9%prior 112
Improper or erratic lane changing139 (5.2%)↑26.4%prior 110
FTYROW: From stop sign101 (3.8%)↑6.3%prior 95
FTYROW: Making left turn96 (3.6%)↓-6.8%prior 103
Made improper turn96 (3.6%)↑24.7%prior 77
Ran Traffic Signal85 (3.2%)↓-9.6%prior 94

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both years occurred in clear weather on dry roads during daylight hours, with these proportions remaining stable. However, there was a notable increase in crashes under adverse winter conditions in 2025. Crashes during 'Snow' weather conditions increased from 119 to 214, and incidents on roads with a 'Snow' surface condition rose from 180 to 274 compared to the prior year.

Weather

Clear1,769 (69.4%)
↑4.4%prior 1,695
Cloudy399 (15.7%)
↓-0.7%prior 402
Snow214 (8.4%)
↑79.8%prior 119
Rain87 (3.4%)
↓-32.6%prior 129
Blowing Snow30 (1.2%)
→0.0%prior 30
Freezing rain/drizzle30 (1.2%)
↑25.0%prior 24
Fog, smoke, smog10 (0.4%)
↓-44.4%prior 18
Other (explain in narrative)5 (0.2%)
↓-28.6%prior 7
Severe Winds5 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight1,890 (74.0%)
↑3.7%prior 1,823
Dark - roadway lighted359 (14.1%)
↑14.3%prior 314
Dark - roadway not lighted189 (7.4%)
↓-6.0%prior 201
Dusk66 (2.6%)
↑11.9%prior 59
Dawn35 (1.4%)
↑6.1%prior 33
Dark - unknown roadway lighting15 (0.6%)
↓-16.7%prior 18

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry1,929 (75.6%)
↑6.2%prior 1,817
Snow274 (10.7%)
↑52.2%prior 180
Wet232 (9.1%)
↓-17.7%prior 282
Ice/frost89 (3.5%)
↓-32.1%prior 131
Slush14 (0.5%)
↓-6.7%prior 15
Gravel10 (0.4%)
↑11.1%prior 9
Other (explain in narrative)2 (0.1%)
Mud, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, Toyota, and Honda representing the top makes in both 2024 and 2025. The age distribution of persons involved in crashes also showed stability year-over-year. The largest age cohort in both periods was the 26-34 group, accounting for 15.5% of involved persons in 2025, nearly identical to its 15.8% share in 2024.

Top Vehicle Makes (4,929 vehicles)

1
FORD640 (13%)
↓-1.2%prior 648
2
CHEV488 (9.9%)
↑7.3%prior 455
3
TOYT378 (7.7%)
↓-7.8%prior 410
4
HOND339 (6.9%)
↑15.3%prior 294
5
JEEP210 (4.3%)
↑2.4%prior 205
6
NISS208 (4.2%)
↑11.8%prior 186
7
KIA172 (3.5%)
↑17.8%prior 146
8
TOYO170 (3.4%)
↑139.4%prior 71
9
CHEVROLET163 (3.3%)
↑12.4%prior 145
10
NR140 (2.8%)
↑14.8%prior 122

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (3,711 persons with recorded sex)

Male2,091 (56.3%)
↑8.8%prior 1,921
Female1,620 (43.7%)
↑1.6%prior 1,594

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,655
  • Total persons involved: 5,082
  • Total vehicles involved: 4,929

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: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2025-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