Yearly Traffic Safety Analysis

1,483 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Story County recorded 1,483 total traffic crashes, a 3.8% decrease from the 1,541 crashes reported in 2023. While overall crashes and the total number of injuries declined, the count of crashes resulting in serious injuries increased significantly, rising from 14 in the prior period to 25 in the current period.

1,483

▼ -3.8%was 1,541

Total Crash Events

4

Persons Killed

329

▼ -10.4%was 367

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 Story County showed a downward trend year-over-year, with total collisions falling by 3.8% from 1,541 in 2023 to 1,483 in 2024. This trend extended to injuries, which decreased by 10.4% from 367 to 329. The number of fatalities remained unchanged at four for both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 4→0.0%

0

Other Killed

Prior: 0→0.0%

17

Pedestrians Injured

Prior: 9↑88.9%

11

Cyclists Injured

Prior: 20↓-45.0%

296

Motorists Injured

Prior: 336↓-11.9%

5

Other Injured

Prior: 2↑150.0%

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 saw some shifts between 2023 and 2024. The peak day for crashes moved from Thursday (293 crashes) in the prior year to Friday (278 crashes) in the current year. However, the 5 PM hour remained the most frequent time for crashes in both periods, with 151 incidents in 2023 and 143 in 2024. Monthly crash distribution also varied, with the highest volume occurring in November in 2023 and October in 2024.

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

While the number of fatal crashes remained constant at four year-over-year, the severity profile of non-fatal crashes shifted. The count of serious injury crashes rose from 14 in 2023 to 25 in 2024, an increase of 78.6%; these crashes represented 1.7% of all incidents in 2024 compared to 0.9% in the prior year. Conversely, crashes involving minor injuries decreased from 119 to 97, and those with possible injuries fell from 184 to 168.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.3%
→0.0%prior 4
Serious Injury25serious injury crashes1.7%
↑78.6%prior 14
Minor Injury97minor injury crashes6.5%
↓-18.5%prior 119
Possible Injury168possible injury crashes11.3%
↓-8.7%prior 184
No Injury1,189no injury crashes80.2%
↓-2.5%prior 1,220

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 factors to crashes remained consistent, with 'Animal' (231 incidents) and 'Followed too close' (192 incidents) being the top two in 2024. However, the count for crashes attributed to following too closely decreased by 13.9% from 223 incidents in 2023. A notable increase was observed in crashes caused by 'Driving too fast for conditions,' which rose in count by 14.8% from 88 to 101 incidents. Similarly, crashes from running a traffic signal increased in count by 58.3%, from 36 in 2023 to 57 in 2024.

Officer-Reported Primary Contributing Cause

Animal231 (15.6%)↓-2.9%prior 238
Followed too close192 (12.9%)↓-13.9%prior 223
FTYROW: Making left turn106 (7.1%)↓-12.4%prior 121
Driving too fast for conditions101 (6.8%)↑14.8%prior 88
FTYROW: From stop sign81 (5.5%)↑3.8%prior 78
Other (explain in narrative): Other81 (5.5%)↓-14.7%prior 95
Ran off road - left66 (4.5%)↓-2.9%prior 68
Ran Traffic Signal57 (3.8%)↑58.3%prior 36
Improper or erratic lane changing45 (3%)↓-21.1%prior 57
Lost Control41 (2.8%)↓-8.9%prior 45

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

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and daylight on dry roads, with conditions remaining broadly stable year-over-year. In 2024, 62.4% of crashes were in clear weather, compared to 63.9% in 2023. However, there was a notable increase in crashes occurring during adverse conditions, with the number of incidents in the rain increasing by 70% from 50 in 2023 to 85 in 2024. Correspondingly, crashes on wet road surfaces rose by 37% from 108 to 148.

Weather

Clear925 (73.1%)
↓-6.1%prior 985
Cloudy173 (13.7%)
↑1.2%prior 171
Rain85 (6.7%)
↑70.0%prior 50
Snow45 (3.6%)
↓-47.1%prior 85
Fog, smoke, smog13 (1.0%)
↑85.7%prior 7
Freezing rain/drizzle11 (0.9%)
↓-42.1%prior 19
Blowing Snow10 (0.8%)
↑11.1%prior 9
Sleet, hail2 (0.2%)
Severe Winds1 (0.1%)
Other (explain in narrative)1 (0.1%)

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

Lighting

Daylight917 (72.0%)
↓-7.4%prior 990
Dark - roadway lighted193 (15.1%)
↑6.6%prior 181
Dark - roadway not lighted96 (7.5%)
↑2.1%prior 94
Dawn29 (2.3%)
↑11.5%prior 26
Dusk29 (2.3%)
↓-25.6%prior 39
Dark - unknown roadway lighting10 (0.8%)
↓-23.1%prior 13

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

Road Surface

Dry950 (74.7%)
↓-10.0%prior 1,056
Wet148 (11.6%)
↑37.0%prior 108
Snow85 (6.7%)
↓-6.6%prior 91
Ice/frost52 (4.1%)
↑4.0%prior 50
Gravel20 (1.6%)
↑66.7%prior 12
Slush14 (1.1%)
↑7.7%prior 13
Other (explain in narrative)1 (0.1%)
Water (standing or moving)1 (0.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained broadly consistent, with Ford, Chevrolet, and Toyota being the most common in both periods, although the count of Fords involved decreased from 480 to 385. An analysis of persons involved in crashes shows a shift in age demographics. While the 16-20 and 21-25 age groups remained the largest cohorts, their proportional share of persons involved slightly decreased. In contrast, the 65+ age group saw its representation increase, accounting for 12.6% of persons with a known age in 2024, up from 10.6% in 2023.

Top Vehicle Makes (2,600 vehicles)

1
FORD385 (14.8%)
↓-19.8%prior 480
2
CHEV347 (13.3%)
→0.0%prior 347
3
TOYT215 (8.3%)
↑1.4%prior 212
4
HOND158 (6.1%)
↑6.8%prior 148
5
JEEP130 (5%)
↑12.1%prior 116
6
CHEVROLET117 (4.5%)
↓-0.8%prior 118
7
NISS114 (4.4%)
↑9.6%prior 104
8
GMC77 (3%)
↑26.2%prior 61
9
TOYOTA66 (2.5%)
↑17.9%prior 56
10
DODG66 (2.5%)
↓-16.5%prior 79

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

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

Sex Distribution (1,843 persons with recorded sex)

Male1,018 (55.2%)
↓-26.9%prior 1,393
Female825 (44.8%)
↓-26.1%prior 1,116

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: 1,483
  • Total persons involved: 2,683
  • Total vehicles involved: 2,600

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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