Yearly Traffic Safety Analysis

1,980 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Pottawattamie County, total traffic crashes decreased by 4.3% from 2,069 in 2022 to 1,980 in 2023. Despite the overall reduction in collisions and a 10.3% drop in injuries from 729 to 654, the number of fatalities increased by 30% from 10 to 13 during the same period.

1,980

▼ -4.3%was 2,069

Total Crash Events

13

▲ 30.0%was 10

Persons Killed

654

▼ -10.3%was 729

Persons Injured

13

▲ 30.0%was 10

Fatal Crash Events

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) 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

The overall trend in Pottawattamie County shows a decrease in traffic incidents year-over-year. Total crashes fell by 4.3%, from 2,069 in 2022 to 1,980 in 2023, and total injuries declined from 729 to 654. However, this downward trend did not extend to the most severe outcomes, as total fatalities rose from 10 to 13.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 1↓-100.0%

10

Motorists Killed

Prior: 9↑11.1%

0

Other Killed

Prior: 0→0.0%

20

Pedestrians Injured

Prior: 23↓-13.0%

23

Cyclists Injured

Prior: 17↑35.3%

608

Motorists Injured

Prior: 688↓-11.6%

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 incidents peaking during the afternoon commute. Friday was the day with the most crashes in both 2023 (330 crashes) and 2022 (350 crashes). The peak hour for collisions shifted slightly earlier, from the 4 p.m. hour in 2022 (177 crashes) to the 3 p.m. hour in 2023 (156 crashes).

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

While total crashes decreased, the severity of outcomes shifted year-over-year. The number of fatal crashes increased from 10 in 2022 to 13 in 2023, raising the fatal crash share from 0.5% to 0.7% of all incidents. Conversely, crashes resulting in serious injuries saw a notable drop, decreasing from 43 (2.1% of total) in 2022 to 29 (1.5% of total) in 2023. The proportion of crashes with no injuries increased slightly from 68.3% to 69.1%.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.7%
↑30.0%prior 10
Serious Injury29serious injury crashes1.5%
↓-32.6%prior 43
Minor Injury167minor injury crashes8.4%
↓-9.2%prior 184
Possible Injury402possible injury crashes20.3%
↓-3.8%prior 418
No Injury1,369no injury crashes69.1%
↓-3.2%prior 1,414

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

The leading contributing factor in both periods was 'Followed too close,' though its count decreased from 294 crashes in 2022 to 270 in 2023. Collisions involving animals became more frequent, increasing in count from 127 to 154 and moving from the fourth to the third most-cited factor. Crashes attributed to 'Lost Control' declined from 138 to 116, while 'Ran Stop Sign' incidents increased from 77 to 86.

Officer-Reported Primary Contributing Cause

Followed too close270 (13.6%)↓-8.2%prior 294
Ran off road - left168 (8.5%)↓-2.3%prior 172
Animal154 (7.8%)↑21.3%prior 127
Lost Control116 (5.9%)↓-15.9%prior 138
Ran Traffic Signal104 (5.3%)↑2.0%prior 102
Ran off road - straight92 (4.6%)↑19.5%prior 77
FTYROW: From stop sign91 (4.6%)↓-8.1%prior 99
Ran Stop Sign86 (4.3%)↑11.7%prior 77
Improper or erratic lane changing76 (3.8%)↑11.8%prior 68
Made improper turn69 (3.5%)↑13.1%prior 61

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

Road & Environmental Conditions

Crash conditions remained broadly similar between the two periods, with the majority of incidents occurring in daylight and on dry roads. In 2023, 63.0% of crashes happened in daylight and 76.2% on dry surfaces, nearly identical to the 2022 proportions of 63.2% and 76.1%, respectively. Crashes on roads with ice or frost saw a notable decrease in count, falling from 87 incidents in 2022 to 60 in 2023.

Weather

Clear1,311 (71.7%)
↓-12.3%prior 1,495
Cloudy320 (17.5%)
↑31.7%prior 243
Rain81 (4.4%)
↑6.6%prior 76
Snow61 (3.3%)
↓-17.6%prior 74
Freezing rain/drizzle31 (1.7%)
→0.0%prior 31
Fog, smoke, smog10 (0.5%)
↑42.9%prior 7
Blowing Snow8 (0.4%)
↓-55.6%prior 18
Sleet, hail4 (0.2%)
Severe Winds1 (0.1%)
↓-91.7%prior 12
Blowing sand, soil, dirt1 (0.1%)

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

Lighting

Daylight1,248 (67.4%)
↓-4.5%prior 1,307
Dark - roadway lighted335 (18.1%)
↓-8.0%prior 364
Dark - roadway not lighted167 (9.0%)
↓-16.5%prior 200
Dusk46 (2.5%)
↑4.5%prior 44
Dawn41 (2.2%)
↑2.5%prior 40
Dark - unknown roadway lighting15 (0.8%)
↑36.4%prior 11

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

Road Surface

Dry1,508 (82.2%)
↓-4.2%prior 1,574
Wet166 (9.0%)
↓-6.2%prior 177
Ice/frost60 (3.3%)
↓-31.0%prior 87
Snow59 (3.2%)
↓-30.6%prior 85
Slush19 (1.0%)
↑280.0%prior 5
Gravel18 (1.0%)
↓-37.9%prior 29
Mud, dirt4 (0.2%)
Other (explain in narrative)1 (0.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes were consistent year-over-year, with Chevrolet (572 vehicles) and Ford (539 vehicles) being the most numerous in 2023, similar to 2022 figures. An analysis of persons involved in crashes shows a shift in age demographics. The number of individuals aged 65 and older involved in crashes increased from 463 to 529, while involvement for those in the 26-34 and 35-44 age groups decreased from 714 to 624 and 713 to 673, respectively.

Top Vehicle Makes (3,455 vehicles)

1
FORD539 (15.6%)
↑5.3%prior 512
2
CHEV334 (9.7%)
↑2.1%prior 327
3
CHEVROLET238 (6.9%)
↓-16.8%prior 286
4
JEEP150 (4.3%)
↑10.3%prior 136
5
NISS132 (3.8%)
↑7.3%prior 123
6
NR127 (3.7%)
↓-9.9%prior 141
7
KIA124 (3.6%)
↓-13.9%prior 144
8
TOYOTA111 (3.2%)
↓-10.5%prior 124
9
NISSAN103 (3%)
↓-8.0%prior 112
10
HOND102 (3%)
↑4.1%prior 98

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

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

Sex Distribution (2,975 persons with recorded sex)

Male1,770 (59.5%)
↓-4.3%prior 1,849
Female1,205 (40.5%)
↓-5.3%prior 1,272

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: 1,980
  • Total persons involved: 4,622
  • Total vehicles involved: 3,455

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

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