Yearly Traffic Safety Analysis

40 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In 2017, Taylor County recorded 40 total vehicle crashes, a 33.3% decrease from the 60 crashes reported in 2016. While the number of fatalities remained stable at two, total injuries fell by 36.7%, from 30 to 19. The most significant shift was the overall reduction in crash volume across the county.

40

▼ -33.3%was 60

Total Crash Events

2

Persons Killed

19

▼ -36.7%was 30

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Taylor County showed a significant downward trend year-over-year. Total crashes decreased by 33.3%, from 60 in 2016 to 40 in 2017. This trend was mirrored in injuries, which fell by 36.7% from 30 to 19, while fatalities held steady at two for both periods.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

19

Motorists Injured

Prior: 29↓-34.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · 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 periods. In 2017, the peak day for crashes was Friday with 10 incidents, a change from Saturday (14 incidents) in the prior year. The peak hour for crashes also shifted from the evening to the morning, moving from 8 p.m. in 2016 (5 crashes) to 7 a.m. in 2017 (4 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the absolute number of fatal crashes remained unchanged at two in both 2016 and 2017, the fatal crash rate increased from 3.3% to 5.0% due to the lower overall crash volume in the current period. The proportion of crashes resulting in any injury (serious, minor, or possible) saw a slight decrease, accounting for 30% of all crashes in 2017 compared to 31.7% in 2016. The share of no-injury crashes remained constant at 65% for both years.

Outcome by Severity (Crash Events)

Fatal2fatal crashes5%
→0.0%prior 2
Serious Injury2serious injury crashes5%
↓-33.3%prior 3
Minor Injury8minor injury crashes20%
↑33.3%prior 6
Possible Injury2possible injury crashes5%
↓-80.0%prior 10
No Injury26no injury crashes65%
↓-33.3%prior 39

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, though the count decreased from 18 in 2016 to 16 in 2017. 'Lost Control' incidents increased in count from 4 to 7, becoming the second-most cited factor in 2017. Conversely, crashes attributed to 'Ran off road - straight' saw a significant drop in count from 5 to 1. Crashes involving running a stop sign also decreased, falling from 4 incidents to 2.

Officer-Reported Primary Contributing Cause

Animal16 (40%)↓-11.1%prior 18
Lost Control7 (17.5%)
Ran off road - left3 (7.5%)
Driving too fast for conditions2 (5%)
Driver Distraction: Other interior distraction2 (5%)
Other (explain in narrative): Other2 (5%)↓-71.4%prior 7
Ran Stop Sign2 (5%)
Passing: With insufficient distance/inadequate visibility1 (2.5%)
Exceeded authorized speed1 (2.5%)
Followed too close1 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in daylight decreased from 50% (30 crashes) in 2016 to 40% (16 crashes) in 2017. Correspondingly, crashes during dawn increased from 1 to 5, and crashes in unlighted dark conditions rose from 2 to 4. Crashes on snowy roads increased from 1 to 4, while incidents on dry roads decreased from 28 to 13. The share of crashes in clear weather conditions remained dominant but fell slightly from 48.3% to 42.5%.

Weather

Clear17 (68.0%)
↓-41.4%prior 29
Cloudy4 (16.0%)
Fog, smoke, smog2 (8.0%)
Snow2 (8.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight16 (61.5%)
↓-46.7%prior 30
Dawn5 (19.2%)
Dark - roadway not lighted4 (15.4%)
Dusk1 (3.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry13 (50.0%)
↓-53.6%prior 28
Snow4 (15.4%)
Gravel3 (11.5%)
Wet3 (11.5%)
Ice/frost1 (3.8%)
Mud, dirt1 (3.8%)
Slush1 (3.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes for both years, though their counts decreased along with the overall crash trend. Ford-made vehicles were involved in 11 crashes in 2017, down from 20 in 2016, and Chevrolet-made vehicles were involved in 10 crashes, down from 18. A notable demographic shift occurred among persons involved in crashes; the number of individuals aged 65 and older dropped from 21 in 2016 to 8 in 2017. The 26-34 age group was the most represented in 2017 with 14 individuals, a slight decrease from 15 in the prior year.

Top Vehicle Makes (51 vehicles)

1
FORD11 (21.6%)
↓-45.0%prior 20
2
CHEV6 (11.8%)
↓-14.3%prior 7
3
DODGE5 (9.8%)
↓-28.6%prior 7
4
CHEVROLET4 (7.8%)
↓-63.6%prior 11
5
CHRY4 (7.8%)
6
DODG3 (5.9%)
7
PONT2 (3.9%)
8
LINCOLN2 (3.9%)
9
CHRYSLER2 (3.9%)
10
TOYOTA1 (2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records

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

Sex Distribution (28 persons with recorded sex)

Male18 (64.3%)
↓-50.0%prior 36
Female10 (35.7%)
↓-50.0%prior 20

Source: Iowa Crash Data · ArcGIS Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 40
  • Total persons involved: 64
  • Total vehicles involved: 51

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: 2017." Published September 9, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2017-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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