Yearly Traffic Safety Analysis

261 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Benton County recorded 261 total vehicle crashes, a 20.4% decrease from the 328 crashes reported in 2019. While total crashes and fatalities declined, the number of people injured saw a slight increase from 114 in 2019 to 120 in 2020. The most significant change was the overall reduction in collisions, which occurred despite a proportional increase in injury-involved crashes.

261

▼ -20.4%was 328

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

120

▲ 5.3%was 114

Persons Injured

3

▼ -25.0%was 4

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 · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, Benton County experienced a significant downward trend in traffic collisions in 2020 compared to the previous year. The total number of crashes fell by 20.4%, from 328 to 261, and fatal crashes decreased from 4 to 3. Despite this reduction in overall incidents, the total number of persons injured increased by 5.3% from 114 to 120.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 4↓-25.0%

1

Cyclists Injured

Prior: 0→%

119

Motorists Injured

Prior: 114↑4.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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 2020, the peak day for crashes was Monday with 54 incidents, a change from 2019 when Friday was the peak day with 53 crashes. Similarly, the peak hour for collisions moved from the 6 p.m. hour in 2019 (28 crashes) to the 7 a.m. hour in 2020 (20 crashes), indicating a shift from an evening to a morning commute peak.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes decreased from 4 in 2019 to 3 in 2020, the proportion of crashes resulting in an injury increased. In 2020, 35.6% of all crashes involved an injury (93 crashes), up from a 29.6% share in 2019 (97 crashes). The share of serious injury crashes decreased from 3.7% to 2.7%, while the proportion of crashes with no injuries fell from 69.2% in 2019 to 63.2% in 2020.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.1%
↓-25.0%prior 4
Serious Injury7serious injury crashes2.7%
↓-41.7%prior 12
Minor Injury51minor injury crashes19.5%
↑15.9%prior 44
Possible Injury35possible injury crashes13.4%
↓-14.6%prior 41
No Injury165no injury crashes63.2%
↓-27.3%prior 227

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained the top contributing factor in both years, though the count decreased from 78 crashes in 2019 to 71 in 2020. 'Lost Control' also remained the second-most cited factor but saw a substantial reduction in count, falling from 47 incidents in 2019 to 32 in 2020. The factor 'Ran off road - straight' dropped from the third-ranked cause with 31 crashes in 2019 to the fourth-ranked with 13 crashes in 2020, a 58.1% decrease in count.

Officer-Reported Primary Contributing Cause

Animal71 (27.2%)↓-9.0%prior 78
Lost Control32 (12.3%)↓-31.9%prior 47
Driving too fast for conditions21 (8%)↓-4.5%prior 22
Ran off road - straight13 (5%)↓-58.1%prior 31
Followed too close11 (4.2%)↓-35.3%prior 17
Ran off road - left9 (3.4%)↑12.5%prior 8
FTYROW: From stop sign8 (3.1%)↓-52.9%prior 17
Driver Distraction: Inattentive/lost in thought8 (3.1%)→0.0%prior 8
Ran Stop Sign7 (2.7%)↓-36.4%prior 11
Driver Distraction: Other interior distraction7 (2.7%)↓-12.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in adverse conditions was lower in 2020 compared to 2019. Crashes on adverse road surfaces like ice, snow, or wet pavement accounted for 19.2% of all incidents in 2020, down from a 29.9% share in the prior year. Similarly, crashes during adverse weather made up 12.3% of the total in 2020, a decrease from 17.7% in 2019. The share of crashes occurring in daylight also decreased, from 52.4% in 2019 to 47.9% in 2020.

Weather

Clear139 (69.2%)
↓-7.9%prior 151
Cloudy27 (13.4%)
↓-46.0%prior 50
Rain10 (5.0%)
↑25.0%prior 8
Snow10 (5.0%)
↓-56.5%prior 23
Freezing rain/drizzle4 (2.0%)
↓-55.6%prior 9
Blowing Snow3 (1.5%)
↓-72.7%prior 11
Fog, smoke, smog3 (1.5%)
Severe Winds3 (1.5%)
Sleet, hail2 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight125 (61.6%)
↓-27.3%prior 172
Dark - roadway not lighted53 (26.1%)
↓-10.2%prior 59
Dawn11 (5.4%)
↑37.5%prior 8
Dark - roadway lighted11 (5.4%)
↓-38.9%prior 18
Dusk2 (1.0%)
↓-66.7%prior 6
Dark - unknown roadway lighting1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry129 (64.5%)
↓-12.8%prior 148
Wet26 (13.0%)
↓-3.7%prior 27
Gravel20 (10.0%)
↑42.9%prior 14
Ice/frost14 (7.0%)
↓-67.4%prior 43
Snow8 (4.0%)
↓-70.4%prior 27
Slush2 (1.0%)
Mud, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both years, with both seeing a reduction in total incidents from 2019 to 2020. An analysis of persons involved in crashes shows a shift in age demographics. The proportion of individuals in the 16-20 age group increased from representing 12.1% of all persons in 2019 to 17.4% in 2020. Conversely, the share of persons in the 35-44 and 45-54 age groups decreased over the same period.

Top Vehicle Makes (364 vehicles)

1
FORD67 (18.4%)
↓-25.6%prior 90
2
CHEV53 (14.6%)
↓-32.9%prior 79
3
CHEVROLET22 (6%)
↓-24.1%prior 29
4
DODG21 (5.8%)
↓-4.5%prior 22
5
TOYT18 (4.9%)
↓-10.0%prior 20
6
JEEP15 (4.1%)
↑25.0%prior 12
7
GMC12 (3.3%)
↓-20.0%prior 15
8
KIA11 (3%)
↑57.1%prior 7
9
BUIC10 (2.7%)
↓-16.7%prior 12
10
TOYOTA8 (2.2%)
→0.0%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

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

Sex Distribution (341 persons with recorded sex)

Male216 (63.3%)
↓-22.0%prior 277
Female125 (36.7%)
↓-25.1%prior 167

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 261
  • Total persons involved: 569
  • Total vehicles involved: 364

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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

ThatCarHitMe.com · An Injuria.ai Company