Yearly Traffic Safety Analysis

379 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Cedar County recorded 379 total crashes, a 1.9% increase from the 372 crashes reported in 2022. While overall crash volume remained relatively stable, fatalities rose from 3 to 5 year-over-year. The most notable shift was a 75% increase in the number of crashes involving a driver under the influence, which grew from 8 in 2022 to 14 in 2023.

379

▲ 1.9%was 372

Total Crash Events

5

▲ 66.7%was 3

Persons Killed

96

▼ -12.7%was 110

Persons Injured

5

▲ 66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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

Overall traffic crashes in Cedar County saw a slight increase of 1.9%, from 372 in 2022 to 379 in 2023. Despite this small rise in total incidents, the number of people injured decreased by 12.7% from 110 to 96. However, fatalities increased from 3 in the prior year to 5 in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 3↑33.3%

0

Pedestrians Injured

Prior: 2↓-100.0%

1

Cyclists Injured

Prior: 2↓-50.0%

95

Motorists Injured

Prior: 106↓-10.4%

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 showed some shifts between the two periods. The peak day for crashes moved from Friday (70 crashes) in 2022 to Thursday (68 crashes) in 2023. The peak hour for collisions remained the 5 p.m. hour in both years, though the number of crashes during this hour increased from 29 to 33.

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

The severity of crashes shifted year-over-year, with an increase in the most severe outcomes. Fatal crashes rose from 3 in 2022 to 5 in 2023, and their share of all crashes increased from 0.8% to 1.3%. Serious injury crashes also increased from 8 to 12. Conversely, the number of crashes resulting in minor or possible injuries decreased, and the proportion of crashes with no injuries rose from 76.9% to 79.7%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes1.3%
↑66.7%prior 3
Serious Injury12serious injury crashes3.2%
↑50.0%prior 8
Minor Injury31minor injury crashes8.2%
↓-24.4%prior 41
Possible Injury29possible injury crashes7.7%
↓-14.7%prior 34
No Injury302no injury crashes79.7%
↑5.6%prior 286

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

Collisions involving an animal remained the leading contributing factor in both years, with counts holding steady at 96 in 2022 and 98 in 2023. 'Ran off road - straight' and 'Lost Control' saw decreases in their respective crash counts, falling from 41 to 32 and 39 to 36. A notable change was observed in 'Driver Distraction: Other interior distraction,' for which the crash count tripled from 6 incidents in 2022 to 18 in 2023, a 200% increase in count.

Officer-Reported Primary Contributing Cause

Animal98 (25.9%)↑2.1%prior 96
Lost Control36 (9.5%)↓-7.7%prior 39
Ran off road - straight32 (8.4%)↓-22.0%prior 41
Followed too close30 (7.9%)↑7.1%prior 28
Driving too fast for conditions19 (5%)↑11.8%prior 17
Driver Distraction: Other interior distraction18 (4.7%)↑200.0%prior 6
FTYROW: From stop sign16 (4.2%)↓-11.1%prior 18
Ran off road - left15 (4%)↓-6.3%prior 16
Operating vehicle in an reckless, erratic, careless, negligent manner13 (3.4%)↑44.4%prior 9
Improper or erratic lane changing10 (2.6%)↑25.0%prior 8

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 year-over-year, with most incidents in both periods occurring in clear weather on dry roads. However, the proportion of crashes happening in daylight increased from 47.0% of all crashes in 2022 to 54.6% in 2023. Concurrently, the share of crashes occurring in dark, unlit conditions decreased from 22.0% to 16.1%.

Weather

Clear197 (67.9%)
↑4.2%prior 189
Cloudy46 (15.9%)
↑7.0%prior 43
Snow27 (9.3%)
↑58.8%prior 17
Rain7 (2.4%)
↓-61.1%prior 18
Freezing rain/drizzle6 (2.1%)
Blowing Snow3 (1.0%)
↓-62.5%prior 8
Fog, smoke, smog3 (1.0%)
Severe Winds1 (0.3%)

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

Lighting

Daylight207 (71.1%)
↑18.3%prior 175
Dark - roadway not lighted61 (21.0%)
↓-25.6%prior 82
Dark - roadway lighted12 (4.1%)
↑20.0%prior 10
Dusk5 (1.7%)
↓-37.5%prior 8
Dawn4 (1.4%)
↓-42.9%prior 7
Dark - unknown roadway lighting2 (0.7%)

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

Road Surface

Dry212 (73.1%)
↑9.8%prior 193
Wet25 (8.6%)
↓-21.9%prior 32
Snow20 (6.9%)
↓-9.1%prior 22
Gravel16 (5.5%)
↑6.7%prior 15
Ice/frost12 (4.1%)
↓-42.9%prior 21
Slush3 (1.0%)
Mud, dirt2 (0.7%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both periods, though the count for Ford-made vehicles decreased from 108 to 94. The number of Freightliner trucks involved in crashes increased from 22 to 28. An analysis of persons involved in crashes shows a relatively stable age distribution, with the 45-54 age group seeing a slight increase in representation from 112 to 121 individuals, while the 26-34 age group saw a small decrease from 123 to 112.

Top Vehicle Makes (569 vehicles)

1
FORD94 (16.5%)
↓-13.0%prior 108
2
CHEV59 (10.4%)
↑15.7%prior 51
3
FREIGHTLINER28 (4.9%)
↑27.3%prior 22
4
CHEVROLET28 (4.9%)
↓-12.5%prior 32
5
TOYT19 (3.3%)
↓-5.0%prior 20
6
HOND18 (3.2%)
↑100.0%prior 9
7
DODG18 (3.2%)
↑12.5%prior 16
8
CHRY18 (3.2%)
↑260.0%prior 5
9
TOYOTA17 (3%)
↓-5.6%prior 18
10
KIA17 (3%)
↑54.5%prior 11

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

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

Sex Distribution (515 persons with recorded sex)

Male333 (64.7%)
↓-1.8%prior 339
Female182 (35.3%)
↑10.3%prior 165

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: 379
  • Total persons involved: 796
  • Total vehicles involved: 569

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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