Yearly Traffic Safety Analysis

97 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Lucas County, total traffic crashes decreased by 7.6%, from 105 incidents in 2024 to 97 in 2025. The most notable year-over-year change was the elimination of traffic fatalities, which fell from one in the prior period to zero in the current period. Total injuries saw a slight increase from 21 to 22.

97

▼ -7.6%was 105

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

22

▲ 4.8%was 21

Persons Injured

0

▼ -100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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

Traffic crashes in Lucas County showed a modest year-over-year decline, falling from 105 in 2024 to 97 in 2025, a 7.6% decrease. While total injuries remained nearly flat, increasing by one person from 21 to 22, the county recorded zero traffic fatalities in the current period, compared to one in the previous year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

22

Motorists Injured

Prior: 21↑4.8%

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 timing of crashes shifted year-over-year. The peak day for collisions moved from Thursday (19 crashes) in the prior period to Wednesday (22 crashes) in the current period. The peak hour also shifted an hour earlier, from 7 p.m. (12 crashes) in 2024 to 6 p.m. (9 crashes) in 2025.

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 improved, with fatal crashes decreasing from one in the prior period to zero in the current period. The number of serious injury crashes increased slightly from 3 to 4. Overall, the proportion of crashes resulting in any level of injury (serious, minor, or possible) was similar, accounting for 20.6% of crashes in 2025 compared to 19.0% in 2024.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes4.1%
↑33.3%prior 3
Minor Injury9minor injury crashes9.3%
↓-10.0%prior 10
Possible Injury7possible injury crashes7.2%
→0.0%prior 7
No Injury77no injury crashes79.4%
↓-8.3%prior 84

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

Collisions involving an "Animal" remained the top contributing factor in both periods but saw a 34.2% decrease in count, from 38 incidents in 2024 to 25 in 2025. Conversely, crashes attributed to "FTYROW: From stop sign" increased by 150%, rising from 4 to 10 incidents, which moved it from the fifth-ranked factor in the prior period to the third-ranked in the current period. "Lost Control" incidents remained a top factor, with a slight decrease from 10 to 9 crashes.

Officer-Reported Primary Contributing Cause

Animal25 (25.8%)↓-34.2%prior 38
Other (explain in narrative): Other11 (11.3%)↑10.0%prior 10
FTYROW: From stop sign10 (10.3%)
Lost Control9 (9.3%)↓-10.0%prior 10
Ran off road - left6 (6.2%)
Driving too fast for conditions5 (5.2%)
FTYROW: From yield sign4 (4.1%)
Followed too close3 (3.1%)
Ran off road - straight3 (3.1%)
Driver Distraction: Other interior distraction2 (2.1%)

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

Road & Environmental Conditions

Crashes in daylight conditions increased from 43 to 52, representing a larger share of total incidents (53.6% in 2025 vs. 41.0% in 2024). While collisions on dry roads were constant at 55 for both years, their proportion of the total also increased. Incidents on snow-covered road surfaces increased from 4 to 7, and those on icy or frosty roads rose from 1 to 3.

Weather

Clear60 (81.1%)
↑5.3%prior 57
Cloudy6 (8.1%)
↓-33.3%prior 9
Snow3 (4.1%)
Freezing rain/drizzle2 (2.7%)
Rain2 (2.7%)
Severe Winds1 (1.4%)

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

Lighting

Daylight52 (69.3%)
↑20.9%prior 43
Dark - roadway not lighted12 (16.0%)
↓-29.4%prior 17
Dark - roadway lighted6 (8.0%)
↑20.0%prior 5
Dusk4 (5.3%)
Dark - unknown roadway lighting1 (1.3%)

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

Road Surface

Dry55 (74.3%)
→0.0%prior 55
Snow7 (9.5%)
Gravel5 (6.8%)
Ice/frost3 (4.1%)
Wet3 (4.1%)
↓-50.0%prior 6
Slush1 (1.4%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes saw a shift; while Ford and Chevrolet remained the top two, their positions reversed with Chevrolet becoming number one. Ford vehicles involved in crashes decreased from 37 to 22, and Chevrolet vehicles decreased from 33 to 29. The age demographics of persons involved also changed, with a notable increase in the 16-20 and 65+ age groups (from 18 to 23 and 15 to 23 persons, respectively) and a decrease in the 26-34 age group (from 29 to 17 persons).

Top Vehicle Makes (148 vehicles)

1
CHEV29 (19.6%)
↓-12.1%prior 33
2
FORD22 (14.9%)
↓-40.5%prior 37
3
DODG9 (6.1%)
4
GMC8 (5.4%)
5
CHEVROLET8 (5.4%)
↑33.3%prior 6
6
JEEP6 (4.1%)
→0.0%prior 6
7
RAM5 (3.4%)
↓-16.7%prior 6
8
DODGE5 (3.4%)
9
BUIC4 (2.7%)
10
NISS4 (2.7%)
↓-63.6%prior 11

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

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

Sex Distribution (82 persons with recorded sex)

Male46 (56.1%)
↓-13.2%prior 53
Female36 (43.9%)
↑71.4%prior 21

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: 97
  • Total persons involved: 151
  • Total vehicles involved: 148

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

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