Yearly Traffic Safety Analysis

267 CRASHES IN
IOWA, IA
2016

All metrics benchmarked against2015

In 2016, Benton County recorded 267 total crashes, representing a 6.0% decrease from the 284 crashes reported in 2015. Despite the overall decline in collisions, the number of fatal crashes increased by 50%, rising from 4 in 2015 to 6 in 2016. Correspondingly, total injuries rose from 118 to 127, while total fatalities decreased slightly from 11 to 9.

267

▼ -6.0%was 284

Total Crash Events

9

▼ -18.2%was 11

Persons Killed

127

▲ 7.6%was 118

Persons Injured

6

▲ 50.0%was 4

Fatal Crash Events

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic collisions in Benton County showed a downward trend, decreasing by 6.0% from 284 in 2015 to 267 in 2016. However, this trend did not extend to crash outcomes, as total injuries increased by 7.6% from 118 to 127. The number of fatalities saw a slight reduction, falling from 11 in the prior year to 9 in the current year.

Vulnerable Road User Casualties

9

Motorists Killed

Prior: 10↓-10.0%

127

Motorists Injured

Prior: 118↑7.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes in Benton County shifted year-over-year. The peak day for collisions moved from Saturday (52 crashes) in 2015 to Thursday (45 crashes) in 2016. Similarly, the peak hour for crashes changed from the evening commute at 4 p.m. (23 crashes) in the prior year to the morning commute at 7 a.m. (21 crashes) in the current year.

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of collisions generally increased in 2016 compared to 2015. The number of fatal crashes rose from 4 to 6, and serious injury crashes increased from 15 to 18. Consequently, the proportion of crashes resulting in no injury fell from 70.4% in 2015 to 64.4% in 2016, while the share of crashes involving some level of injury increased.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes2.2%
↑50.0%prior 4
Serious Injury18serious injury crashes6.7%
↑20.0%prior 15
Minor Injury28minor injury crashes10.5%
↓-28.2%prior 39
Possible Injury43possible injury crashes16.1%
↑65.4%prior 26
No Injury172no injury crashes64.4%
↓-14.0%prior 200

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the top contributing factor in both periods but saw a substantial decrease in count, falling from 82 crashes in 2015 to 47 in 2016. 'Lost Control' was the second-most cited factor in both years, with a slight drop from 41 to 39 incidents. Notably, crashes attributed to 'Driving too fast for conditions' increased from 13 to 24, while incidents involving 'Failure to yield right of way from a stop sign' decreased from 20 to 11.

Officer-Reported Primary Contributing Cause

Animal47 (17.6%)↓-42.7%prior 82
Lost Control39 (14.6%)↓-4.9%prior 41
Driving too fast for conditions24 (9%)↑84.6%prior 13
Ran off road - straight20 (7.5%)→0.0%prior 20
Followed too close14 (5.2%)↑55.6%prior 9
Driver Distraction: Other interior distraction11 (4.1%)
FTYROW: From stop sign11 (4.1%)↓-45.0%prior 20
Ran Stop Sign9 (3.4%)→0.0%prior 9
Exceeded authorized speed6 (2.2%)
Improper Backing5 (1.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather on dry roads. In 2016, there was a notable decrease in crashes during rainy conditions (from 20 to 8) and on wet road surfaces (from 24 to 14). Conversely, crashes on icy or frosty roads increased from 14 in 2015 to 18 in 2016. The number of collisions in daylight increased from 135 to 148, while crashes in unlit dark conditions remained relatively stable.

Weather

Clear144 (63.7%)
↑12.5%prior 128
Cloudy53 (23.5%)
↑1.9%prior 52
Rain8 (3.5%)
↓-60.0%prior 20
Snow7 (3.1%)
→0.0%prior 7
Fog, smoke, smog6 (2.7%)
Blowing Snow4 (1.8%)
Freezing rain/drizzle3 (1.3%)
Severe Winds1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash

Lighting

Daylight148 (64.9%)
↑9.6%prior 135
Dark - roadway not lighted50 (21.9%)
↓-5.7%prior 53
Dawn15 (6.6%)
↑150.0%prior 6
Dark - roadway lighted12 (5.3%)
↓-25.0%prior 16
Dusk2 (0.9%)
↓-66.7%prior 6
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field

Road Surface

Dry162 (71.7%)
↑5.2%prior 154
Ice/frost18 (8.0%)
↑28.6%prior 14
Gravel15 (6.6%)
↑25.0%prior 12
Wet14 (6.2%)
↓-41.7%prior 24
Snow13 (5.8%)
↑8.3%prior 12
Slush4 (1.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet and Ford leading in both 2015 and 2016. An analysis of persons involved in collisions reveals a significant shift in age demographics, with the number of individuals in the 16-20 age group dropping from 92 in 2015 to 55 in 2016. Conversely, involvement for the 26-34 age group increased from 67 to 83 persons.

Top Vehicle Makes (405 vehicles)

1
FORD73 (18%)
↑21.7%prior 60
2
CHEVROLET57 (14.1%)
↑23.9%prior 46
3
CHEV48 (11.9%)
↓-22.6%prior 62
4
TOYOTA16 (4%)
↑100.0%prior 8
5
DODG15 (3.7%)
↓-16.7%prior 18
6
DODGE15 (3.7%)
↑87.5%prior 8
7
GMC13 (3.2%)
↑44.4%prior 9
8
TOYT13 (3.2%)
↓-7.1%prior 14
9
JEEP10 (2.5%)
↑11.1%prior 9
10
NR10 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · Vehicle unit records

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

Sex Distribution (289 persons with recorded sex)

Male163 (56.4%)
↓-24.5%prior 216
Female126 (43.6%)
↓-22.2%prior 162

Source: Iowa Crash Data · ArcGIS Open Data · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2016-01-01 through 2016-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 267
  • Total persons involved: 484
  • Total vehicles involved: 405

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: 2016." Published September 9, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2016-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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