Yearly Traffic Safety Analysis

1,882 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Pottawattamie County recorded 1,882 total crashes, a 5.0% decrease from the 1,980 crashes reported in 2023. This overall decline in collisions was accompanied by a significant 30.8% reduction in traffic fatalities, which fell from 13 in the prior year to 9. While overall trends were positive, crashes attributed to driving under the influence (DUI) saw an increase, rising from 84 incidents in 2023 to 96 in 2024.

1,882

▼ -4.9%was 1,980

Total Crash Events

9

▼ -30.8%was 13

Persons Killed

646

▼ -1.2%was 654

Persons Injured

9

▼ -30.8%was 13

Fatal Crash Events

Note: "Persons Killed" (9) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Pottawattamie County showed a downward trend year-over-year. Total collisions decreased by 5.0%, from 1,980 in 2023 to 1,882 in 2024. This decline was mirrored by a 1.2% decrease in total injuries (from 654 to 646) and a 30.8% drop in fatalities (from 13 to 9).

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 3↑33.3%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 10↓-50.0%

0

Other Killed

Prior: 0→0.0%

18

Pedestrians Injured

Prior: 20↓-10.0%

20

Cyclists Injured

Prior: 23↓-13.0%

603

Motorists Injured

Prior: 608↓-0.8%

5

Other Injured

Prior: 3↑66.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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 the two periods. Friday was the peak day for crashes in both 2024 (359 crashes) and 2023 (330 crashes). Similarly, the 3 p.m. hour was the peak time for collisions in both years, though the count at that hour decreased from 156 to 141. The afternoon commute hours, from 3 p.m. to 5 p.m., consistently represented the time of day with the highest crash frequency across both years.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, with the fatal crash rate decreasing from 0.7% of all incidents in 2023 to 0.5% in 2024. While fatal and possible injury crashes declined, the number of crashes resulting in more severe non-fatal injuries increased. Crashes involving serious injuries rose from 29 to 40, and minor injury crashes increased from 167 to 180.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.5%
↓-30.8%prior 13
Serious Injury40serious injury crashes2.1%
↑37.9%prior 29
Minor Injury180minor injury crashes9.6%
↑7.8%prior 167
Possible Injury365possible injury crashes19.4%
↓-9.2%prior 402
No Injury1,288no injury crashes68.4%
↓-5.9%prior 1,369

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both periods was "Followed too close," though its count decreased from 270 in 2023 to 250 in 2024. A significant year-over-year change was the reduction in crashes involving animals, which fell by 40.3% from 154 incidents to 92, dropping from the third to the fifth most common factor. In contrast, crashes attributed to "FTYROW: Making left turn" increased in count by 32.7%, from 49 to 65 incidents.

Officer-Reported Primary Contributing Cause

Followed too close250 (13.3%)↓-7.4%prior 270
Ran off road - left166 (8.8%)↓-1.2%prior 168
Lost Control113 (6%)↓-2.6%prior 116
FTYROW: From stop sign98 (5.2%)↑7.7%prior 91
Animal92 (4.9%)↓-40.3%prior 154
Ran off road - straight89 (4.7%)↓-3.3%prior 92
Ran Traffic Signal89 (4.7%)↓-14.4%prior 104
Other (explain in narrative): Other81 (4.3%)↑28.6%prior 63
Ran Stop Sign69 (3.7%)↓-19.8%prior 86
Driving too fast for conditions68 (3.6%)↑13.3%prior 60

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In both periods, the majority of crashes occurred in clear weather on dry roads during daylight hours, with the proportion of crashes in daylight remaining stable at around 63%. However, there was a notable increase in crashes occurring on adverse road surfaces. The count of collisions on wet, icy, snowy, or slushy roads rose from 304 in 2023 to 375 in 2024, driven by increases in crashes on icy surfaces (from 60 to 96) and wet surfaces (from 166 to 208).

Weather

Clear1,331 (73.9%)
↑1.5%prior 1,311
Cloudy273 (15.2%)
↓-14.7%prior 320
Rain94 (5.2%)
↑16.0%prior 81
Snow33 (1.8%)
↓-45.9%prior 61
Freezing rain/drizzle27 (1.5%)
↓-12.9%prior 31
Fog, smoke, smog15 (0.8%)
↑50.0%prior 10
Blowing Snow10 (0.6%)
↑25.0%prior 8
Severe Winds9 (0.5%)
Sleet, hail4 (0.2%)
Other (explain in narrative)2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight1,194 (65.9%)
↓-4.3%prior 1,248
Dark - roadway lighted337 (18.6%)
↑0.6%prior 335
Dark - roadway not lighted184 (10.2%)
↑10.2%prior 167
Dusk45 (2.5%)
↓-2.2%prior 46
Dawn39 (2.2%)
↓-4.9%prior 41
Dark - unknown roadway lighting13 (0.7%)
↓-13.3%prior 15

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,404 (78.0%)
↓-6.9%prior 1,508
Wet208 (11.5%)
↑25.3%prior 166
Ice/frost96 (5.3%)
↑60.0%prior 60
Snow61 (3.4%)
↑3.4%prior 59
Gravel16 (0.9%)
↓-11.1%prior 18
Slush10 (0.6%)
↓-47.4%prior 19
Other (explain in narrative)3 (0.2%)
Oil1 (0.1%)
Water (standing or moving)1 (0.1%)
Mud, dirt1 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford and Chevrolet leading in both years, although the count for both decreased in 2024. Ford-made vehicles were involved in 480 crashes, down from 539, while Chevrolet vehicles were involved in a combined 524 crashes, down from 572. The age distribution of persons involved in crashes showed minimal changes, with most age groups maintaining a similar share of the total year-over-year.

Top Vehicle Makes (3,292 vehicles)

1
FORD480 (14.6%)
↓-10.9%prior 539
2
CHEV307 (9.3%)
↓-8.1%prior 334
3
CHEVROLET217 (6.6%)
↓-8.8%prior 238
4
JEEP160 (4.9%)
↑6.7%prior 150
5
KIA142 (4.3%)
↑14.5%prior 124
6
NISS122 (3.7%)
↓-7.6%prior 132
7
NR116 (3.5%)
↓-8.7%prior 127
8
GMC116 (3.5%)
↑14.9%prior 101
9
TOYOTA105 (3.2%)
↓-5.4%prior 111
10
HONDA96 (2.9%)
↑1.1%prior 95

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (2,168 persons with recorded sex)

Male1,286 (59.3%)
↓-27.3%prior 1,770
Female882 (40.7%)
↓-26.8%prior 1,205

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 1,882
  • Total persons involved: 3,457
  • Total vehicles involved: 3,292

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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