Yearly Traffic Safety Analysis

286 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Dickinson County recorded 286 crashes, a 3.4% decrease from the 296 crashes documented in 2022. While total crashes, fatalities (1), and injuries (92) were largely stable, there was a notable shift in contributing factors, with incidents attributed to improper backing increasing by 157% from 7 to 18 cases year-over-year.

286

▼ -3.4%was 296

Total Crash Events

1

Persons Killed

92

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 collisions in Dickinson County saw a slight decline in 2023 compared to the previous year. The total number of crashes fell by 3.4%, from 296 in 2022 to 286 in 2023. Despite this decrease in total incidents, the number of resulting injuries and fatalities remained unchanged, with 92 injuries and 1 fatality recorded in both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

2

Pedestrians Injured

Prior: 3↓-33.3%

2

Cyclists Injured

Prior: 1↑100.0%

88

Motorists Injured

Prior: 88→0.0%

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 timing of crashes shifted between the two years. In 2023, Friday became the peak day for crashes with 54 incidents, a change from Monday (52 crashes) in 2022. The peak hour for collisions also shifted earlier, from 3 p.m. in 2022 (29 crashes) to 1 p.m. in 2023 (25 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

The severity of crashes showed a mixed trend year-over-year. The number of fatal crashes remained constant at one in both 2023 and 2022. However, crashes resulting in serious injuries decreased from 14 to 10. In contrast, crashes involving minor injuries increased from 24 to 26, and those with possible injuries rose from 40 to 44.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
→0.0%prior 1
Serious Injury10serious injury crashes3.5%
↓-28.6%prior 14
Minor Injury26minor injury crashes9.1%
↑8.3%prior 24
Possible Injury44possible injury crashes15.4%
↑10.0%prior 40
No Injury205no injury crashes71.7%
↓-5.5%prior 217

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

While 'Followed too close' remained a primary contributing factor in both years, its count decreased from 41 in 2022 to 37 in 2023. There was a significant year-over-year increase in the count of crashes attributed to 'Improper Backing,' which rose 157% from 7 to 18 incidents. Collisions involving animals also increased by 57% in count, from 14 to 22. Conversely, crashes where 'Lost Control' was a factor decreased from 20 to 9.

Officer-Reported Primary Contributing Cause

Followed too close37 (12.9%)↓-9.8%prior 41
FTYROW: Making left turn23 (8%)↑27.8%prior 18
Animal22 (7.7%)↑57.1%prior 14
Other (explain in narrative): Other21 (7.3%)↑40.0%prior 15
Driving too fast for conditions19 (6.6%)↓-13.6%prior 22
FTYROW: From stop sign18 (6.3%)↓-5.3%prior 19
Improper Backing18 (6.3%)↑157.1%prior 7
Ran off road - left16 (5.6%)→0.0%prior 16
Ran Stop Sign10 (3.5%)↓-23.1%prior 13
Made improper turn9 (3.1%)↑80.0%prior 5

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

Road & Environmental Conditions

Crashes in adverse weather conditions saw a notable decrease in 2023. Collisions occurring in snow or blowing snow dropped from 33 incidents in 2022 to 14 in 2023. However, crashes on wet road surfaces increased from 17 to 30. The majority of crashes in both periods occurred in clear weather (188 in 2023 vs. 186 in 2022) and on dry roads (181 in 2023 vs. 205 in 2022).

Weather

Clear188 (71.2%)
↑1.1%prior 186
Cloudy44 (16.7%)
↓-17.0%prior 53
Rain12 (4.5%)
↑100.0%prior 6
Blowing Snow9 (3.4%)
↑28.6%prior 7
Snow5 (1.9%)
↓-80.8%prior 26
Freezing rain/drizzle4 (1.5%)
Fog, smoke, smog1 (0.4%)
Sleet, hail1 (0.4%)

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

Lighting

Daylight195 (72.8%)
↓-10.1%prior 217
Dark - roadway lighted35 (13.1%)
↑16.7%prior 30
Dark - roadway not lighted27 (10.1%)
→0.0%prior 27
Dusk5 (1.9%)
Dawn4 (1.5%)
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

Dry181 (67.8%)
↓-11.7%prior 205
Wet30 (11.2%)
↑76.5%prior 17
Snow26 (9.7%)
↓-39.5%prior 43
Ice/frost24 (9.0%)
↑71.4%prior 14
Slush4 (1.5%)
Gravel2 (0.7%)
↓-60.0%prior 5

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

Vehicles & Demographics

The top makes of vehicles involved in crashes, including Chevrolet, Ford, and Toyota, remained consistent between 2022 and 2023. However, the age demographics of people involved in crashes shifted significantly. The number of individuals aged 16-20 involved in collisions decreased from 129 to 84. Conversely, involvement of the 65+ age group increased from 90 individuals in 2022 to 113 in 2023.

Top Vehicle Makes (511 vehicles)

1
CHEV83 (16.2%)
↑10.7%prior 75
2
FORD81 (15.9%)
↑2.5%prior 79
3
TOYT29 (5.7%)
↓-23.7%prior 38
4
GMC28 (5.5%)
↑40.0%prior 20
5
CHEVROLET27 (5.3%)
↓-25.0%prior 36
6
JEEP26 (5.1%)
↓-10.3%prior 29
7
DODG18 (3.5%)
↓-21.7%prior 23
8
TOYOTA16 (3.1%)
↑220.0%prior 5
9
CHRY16 (3.1%)
↑23.1%prior 13
10
TOYO15 (2.9%)
↑25.0%prior 12

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

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

Sex Distribution (467 persons with recorded sex)

Male279 (59.7%)
↑1.5%prior 275
Female188 (40.3%)
↓-6.9%prior 202

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: 286
  • Total persons involved: 657
  • Total vehicles involved: 511

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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