Yearly Traffic Safety Analysis

9 CRASHES IN
AKRON, IA
2017

All metrics benchmarked against2016

Total crashes in AKRON decreased by 18.2%, from 11 in 2016 to 9 in 2017. Despite this reduction in overall crashes, total injuries increased by 100% year-over-year, rising from 1 in 2016 to 2 in 2017. Fatalities remained at 0 in both periods, indicating no change in the most severe outcomes.

9

▼ -18.2%was 11

Total Crash Events

0

Persons Killed

2

▲ 100.0%was 1

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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, the total number of crashes in AKRON decreased by 18.2%, from 11 crashes in 2016 to 9 crashes in 2017. While fatalities remained stable at 0 in both periods, total injuries increased by 100%, rising from 1 in 2016 to 2 in 2017.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

2

Motorists Injured

Prior: 1↑100.0%

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

Saturday remained a peak day for crashes, with the count increasing from 2 in 2016 to 3 in 2017. The peak hour for crashes shifted from 1p with 3 crashes in 2016 to 4p with 2 crashes in 2017. This indicates a shift in the timing of peak crash occurrences.

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

Fatalities remained at 0 in both 2016 and 2017, showing no change in the most severe crash outcomes. However, total injuries increased by 100% year-over-year, from 1 injury in 2016 to 2 injuries in 2017. In 2016, there was 1 serious injury reported, whereas in 2017, 1 minor injury was reported.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes11.1%
No Injury8no injury crashes88.9%
↓-20.0%prior 10

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 count of crashes attributed to 'Improper Backing' remained stable at 2 in both 2016 and 2017. Crashes related to 'FTYROW: At uncontrolled intersection' decreased from 3 in 2016 to 1 in 2017. New contributing factors emerged in 2017, including 'Operating vehicle in an reckless, erratic, careless, negligent manner' and 'Ran Stop Sign,' each accounting for 1 crash. Conversely, factors like 'Followed too close' and 'Animal' were reported in 2016 with 1 crash each but were not present in 2017 data.

Officer-Reported Primary Contributing Cause

Improper Backing2 (22.2%)
FTYROW: At uncontrolled intersection1 (11.1%)
FTYROW: From parked position1 (11.1%)
Operating vehicle in an reckless, erratic, careless, negligent manner1 (11.1%)
Ran off road - left1 (11.1%)
Ran Stop Sign1 (11.1%)
Driver Distraction: Unrestrained animal1 (11.1%)

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

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 9 in 2016 to 8 in 2017. The adverse weather condition of 'Blowing Snow' (1 crash in 2016) was replaced by 'Rain' (1 crash in 2017). On road surfaces, 'Dry' conditions saw a decrease from 8 crashes in 2016 to 7 crashes in 2017, while 'Snow' conditions remained stable at 1 crash in both years. 'Sand' (1 crash in 2016) was not reported in 2017, and 'Wet' (1 crash in 2017) was not reported in 2016.

Weather

Clear8 (88.9%)
↓-11.1%prior 9
Rain1 (11.1%)

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

Lighting

Daylight7 (77.8%)
Dark - roadway lighted2 (22.2%)

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

Road Surface

Dry7 (77.8%)
↓-12.5%prior 8
Snow1 (11.1%)
Wet1 (11.1%)

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

Vehicles & Demographics

Top Vehicle Makes (16 vehicles)

1
FORD3 (18.8%)
2
CHEV2 (12.5%)
3
DODG2 (12.5%)
4
CHEVROLET2 (12.5%)
↓-75.0%prior 8
5
NR1 (6.3%)
6
PONTIAC1 (6.3%)
7
BUIC1 (6.3%)
8
TOYOTA1 (6.3%)
9
CHRYSLER1 (6.3%)
10
DODGE1 (6.3%)

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

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

Sex Distribution (6 persons with recorded sex)

Male4 (66.7%)
↓-42.9%prior 7
Female2 (33.3%)
↓-71.4%prior 7

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: AKRON, IA
  • Total crash records analyzed: 9
  • Total persons involved: 19
  • Total vehicles involved: 16

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). "AKRON, 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/akron/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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