Yearly Traffic Safety Analysis

118 CRASHES IN
IOWA, IA
2017

All metrics benchmarked against2016

In 2017, Fremont County recorded 118 total crashes, a 10.6% decrease from the 132 crashes reported in 2016. While total fatalities remained unchanged at 3, the number of crashes attributed to following too closely more than doubled, increasing from 7 in the prior year to 16 in the current period. Overall injuries saw a slight decrease from 67 to 62.

118

▼ -10.6%was 132

Total Crash Events

3

Persons Killed

62

▼ -7.5%was 67

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Overall, traffic crashes in Fremont County saw a downward trend from 2016 to 2017. The total number of crashes decreased by 10.6%, from 132 to 118. Similarly, the number of injuries fell by 7.5% from 67 to 62, while the number of fatalities remained constant at 3 for both years.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 3→0.0%

62

Motorists Injured

Prior: 65↓-4.6%

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 temporal patterns of crashes showed some shifts between 2016 and 2017. While Friday remained the peak day for crashes in both years, the count on Fridays decreased from 31 to 25. The peak hour for collisions shifted from 1 p.m. in 2016, with 12 crashes, to 4 p.m. in 2017, with 11 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

The number of fatal crashes was unchanged at 3 in both 2016 and 2017, though the fatal crash rate per 100 crashes increased from 2.27 to 2.54. The proportion of crashes resulting in possible injuries saw a notable increase, rising from 9.8% of all crashes in 2016 to 17.8% in 2017. Concurrently, the share of non-injury crashes decreased from 65.9% to 59.3% year-over-year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.5%
→0.0%prior 3
Serious Injury13serious injury crashes11%
↑8.3%prior 12
Minor Injury11minor injury crashes9.3%
↓-35.3%prior 17
Possible Injury21possible injury crashes17.8%
↑61.5%prior 13
No Injury70no injury crashes59.3%
↓-19.5%prior 87

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

The leading contributing factors for crashes shifted significantly between 2016 and 2017. Crashes involving animals, the top factor in 2016, were halved from 26 incidents to 13. In contrast, crashes attributed to 'Followed too close' more than doubled in count, increasing from 7 to 16, making it a top-ranked factor in 2017. Incidents involving 'Lost Control' also decreased from 21 to 16.

Officer-Reported Primary Contributing Cause

Followed too close16 (13.6%)↑128.6%prior 7
Lost Control16 (13.6%)↓-23.8%prior 21
Animal13 (11%)↓-50.0%prior 26
Ran off road - straight9 (7.6%)↓-43.8%prior 16
Operating vehicle in an reckless, erratic, careless, negligent manner6 (5.1%)
FTYROW: From stop sign6 (5.1%)
Ran off road - left5 (4.2%)→0.0%prior 5
Other (explain in narrative): Other4 (3.4%)
Exceeded authorized speed3 (2.5%)
Ran Stop Sign3 (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

A larger proportion of crashes in 2017 occurred during clear conditions compared to the previous year. The share of crashes in daylight increased from 53.0% of the total in 2016 to 69.5% in 2017. Similarly, the proportion of incidents on dry road surfaces grew from 65.2% to 75.4%. The share of crashes in adverse weather or on adverse road surfaces remained relatively stable.

Weather

Clear84 (73.7%)
↑9.1%prior 77
Cloudy17 (14.9%)
↓-22.7%prior 22
Freezing rain/drizzle7 (6.1%)
Rain5 (4.4%)
Sleet, hail1 (0.9%)

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

Lighting

Daylight82 (71.3%)
↑17.1%prior 70
Dark - roadway not lighted18 (15.7%)
↓-40.0%prior 30
Dark - roadway lighted7 (6.1%)
↓-12.5%prior 8
Dusk4 (3.5%)
Dawn3 (2.6%)
Dark - unknown roadway lighting1 (0.9%)

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

Road Surface

Dry89 (77.4%)
↑3.5%prior 86
Wet13 (11.3%)
↑116.7%prior 6
Ice/frost6 (5.2%)
↓-53.8%prior 13
Gravel5 (4.3%)
→0.0%prior 5
Snow2 (1.7%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford and Chevrolet leading in both 2016 and 2017. However, the age demographics of persons involved in crashes showed notable changes. The proportion of individuals aged 65 and older increased from 9.1% of all persons in 2016 to 15.4% in 2017. Conversely, the share of persons in the 26-34 age group decreased from 19.0% to 12.7%.

Top Vehicle Makes (176 vehicles)

1
FORD27 (15.3%)
↓-20.6%prior 34
2
CHEV21 (11.9%)
↑133.3%prior 9
3
CHEVROLET16 (9.1%)
↓-38.5%prior 26
4
DODGE12 (6.8%)
↑20.0%prior 10
5
JEEP7 (4%)
6
DODG6 (3.4%)
↓-25.0%prior 8
7
GMC6 (3.4%)
→0.0%prior 6
8
BUICK5 (2.8%)
9
PONTIAC5 (2.8%)
10
NISS4 (2.3%)

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

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

Sex Distribution (134 persons with recorded sex)

Male86 (64.2%)
↑8.9%prior 79
Female48 (35.8%)
↑17.1%prior 41

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: 118
  • Total persons involved: 221
  • Total vehicles involved: 176

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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