Yearly Traffic Safety Analysis

33 CRASHES IN
IOWA, IA
2015

In 2015, Taylor County recorded 33 total traffic crashes, which resulted in 0 fatalities and 7 injuries. A significant portion of these incidents, nearly 40%, were attributed to collisions involving animals, making it the most notable statistical finding from the period.

33

Total Crash Events

0

Persons Killed

7

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 · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

In 2015, there were no traffic-related fatalities in Taylor County. A total of 7 people were injured, comprising 6 vehicle motorists and 1 pedestrian. No cyclists were reported as killed or injured in crashes during this period.

0

Pedestrians Killed

0

Motorists Killed

1

Pedestrians Injured

6

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in Taylor County occurred most frequently on Fridays, which saw 10 of the 33 total incidents in 2015. The peak times for crashes were the 7 a.m. and 6 p.m. hours, each with 4 incidents. A notable number of crashes, 6 out of 33, occurred on unlighted roadways after dark.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 78.8% (26 incidents), resulted in no injuries. The remaining 7 crashes involved injuries, including 1 serious injury, 4 minor injuries, and 2 possible injuries. There were no fatal crashes recorded in Taylor County during this period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3%
Minor Injury4minor injury crashes12.1%
Possible Injury2possible injury crashes6.1%
No Injury26no injury crashes78.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor to crashes was animals on the roadway, cited in 13 incidents and accounting for 39.4% of all crashes. The next most common factors were losing control of the vehicle, which was a factor in 6 crashes (18.2%), and reckless or negligent vehicle operation, noted in 3 crashes (9.1%).

Officer-Reported Primary Contributing Cause

Animal13 (39.4%)
Lost Control6 (18.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (9.1%)
Other (explain in narrative): No improper action3 (9.1%)
Ran Stop Sign2 (6.1%)
Made improper turn1 (3%)
Driver Distraction: Other interior distraction1 (3%)
Ran off road - straight1 (3%)
Failed to keep in proper lane1 (3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A majority of crashes occurred in favorable conditions, with 19 incidents happening in clear weather and on dry road surfaces. Daylight conditions were present for 13 crashes. However, a notable number of crashes, 6 in total, occurred after dark on unlighted roadways, and 1 crash was reported on an icy or frosty surface.

Weather

Clear19 (90.5%)
Cloudy2 (9.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight13 (59.1%)
Dark - roadway not lighted6 (27.3%)
Dark - roadway lighted1 (4.5%)
Dawn1 (4.5%)
Dusk1 (4.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry19 (86.4%)
Gravel2 (9.1%)
Ice/frost1 (4.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (43 vehicles)

1
FORD18 (41.9%)
2
DODGE4 (9.3%)
3
CHEVROLET4 (9.3%)
4
CHEV4 (9.3%)
5
PONTIAC3 (7%)
6
JEEP2 (4.7%)
7
SATR1 (2.3%)
8
TOYOTA1 (2.3%)
9
VOLVO1 (2.3%)
10
CHRY1 (2.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

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

Sex Distribution (41 persons with recorded sex)

Male22 (53.7%)
Female19 (46.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most frequently cited major cause for crashes was 'Animal,' which was attributed to 13 incidents (39.4%). 'Lost Control' was the second leading cause, contributing to 6 crashes (18.2%). 'Operating vehicle in a reckless, erratic, careless, negligent manner' was listed as the cause for 3 crashes (9.1%).

Major Cause

1
Animal13 (41.9%)
2
Lost Control6 (19.4%)
3
Operating vehicle in an reckless, erratic, careless, negligent manner3 (9.7%)
4
Other (explain in narrative): No improper action3 (9.7%)
5
Ran Stop Sign2 (6.5%)
6
Made improper turn1 (3.2%)
7
Driver Distraction: Other interior distraction1 (3.2%)
8
Ran off road - straight1 (3.2%)
9
Failed to keep in proper lane1 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with an animal, which occurred in 13 of the 33 crashes. Collisions with another vehicle in traffic were the next most frequent event, accounting for 5 incidents. Non-collision events like overturns or rollovers were recorded in 3 crashes.

First Harmful Event

1
Collision with: Animal13 (39.4%)
2
Collision with: Vehicle in traffic5 (15.2%)
3
Non-collision events: Overturn/rollover3 (9.1%)
4
Non-collision events: Other non-collision (explain in narrative)2 (6.1%)
5
Collision with fixed object: Traffic sign support1 (3%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)1 (3%)
7
Collision with: Parked motor vehicle1 (3%)
8
Collision with: Struck/struck by object/cargo/person from other vehicle1 (3%)
9
Miscellaneous events: Hit and run1 (3%)

Showing top 9 of 14 reported. 5 additional (5 total) not shown: Non-collision events: Vehicle went airborne, Other (explain in narrative), Collision with fixed object: Building, Collision with fixed object: Ditch, Collision with fixed object: Fence.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

The majority of crashes, 15 out of 33, occurred at non-junction locations along a road segment. Intersections accounted for a smaller share, with 4 crashes at four-way intersections and 1 at a T-intersection. An additional 2 crashes were related to driveways.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature15 (68.2%)
2
Intersection: Four-way intersection4 (18.2%)
3
Intersection: T-intersection1 (4.5%)
4
Non-intersection: Driveway access (related, not in)1 (4.5%)
5
Non-intersection: Driveway access (within)1 (4.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Of the 43 vehicles involved in crashes, passenger cars were the most common type, accounting for 22 vehicles. Light trucks and pickups were the second most frequent with 12 vehicles, followed by sport utility vehicles with 6. One tractor/semi-trailer was involved in a crash during this period.

Vehicle Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

The vast majority of crashes, 27 out of 33, occurred where no traffic controls were present. Stop signs were the only other traffic control device noted, present at the location of 5 crashes. No crashes were reported at locations with traffic signals.

Traffic Control Device

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common area of damage, recorded for 10 vehicles involved in collisions. Rear-end damage was also significant, noted as the primary impact area for 5 vehicles, with an additional 4 vehicles sustaining damage to a rear corner.

Most Damaged Area

"Other" combines 5 smaller categories (5 records): Driver side - middle (1), Front - driver side corner (1), Passenger side - front (1), Passenger side - middle (1), Rear - driver side corner (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Crashes by City

Within Taylor County, the city of Lenox had the highest crash volume with 6 incidents. Bedford and New Market each recorded 2 crashes. Clearfield and Sharpsburg each had 1 crash.

Crashes by City

1
LENOX6 (50%)
2
BEDFORD2 (16.7%)
3
NEW MARKET2 (16.7%)
4
CLEARFIELD1 (8.3%)
5
SHARPSBURG1 (8.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

The majority of crashes, 28 out of 33, occurred on paved roadways. A smaller portion, 5 crashes, took place on unpaved surfaces such as gravel or dirt roads.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

Officer-estimated property damage for the 33 crashes was primarily in the $1,500 to $7,500 range, which accounted for 23 incidents. The remaining 10 crashes were estimated to have damage between $7,500 and $25,000. No crashes were reported with property damage exceeding $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

The predominant manner of collision was single-vehicle, non-collision incidents, such as running off the road or overturning, which accounted for 23 crashes or 69.7% of the total. Multi-vehicle collisions were less frequent, with angle and rear-end crashes each accounting for a small number of incidents.

Manner of Collision

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for the vehicles involved was 'Movement essentially straight,' recorded for 24 of the 43 vehicles. Backing was the next most frequent action, noted for 3 vehicles. Turning left and being legally parked were each recorded for 2 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight24 (66.7%)
2
Backing3 (8.3%)
3
Legally Parked2 (5.6%)
4
Other (explain in narrative)2 (5.6%)
5
Turning left2 (5.6%)
6
Leaving traffic lane1 (2.8%)
7
Slowing/stopping (deceleration)1 (2.8%)
8
Stopped in traffic1 (2.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 50 individuals involved in crashes, 49 were drivers of vehicles. The remaining individual was a pedestrian. No passengers were recorded in any of the crashes during this period.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicles Per Crash

Single-vehicle crashes were the most common type, accounting for 24 of the 33 total incidents (72.7%). Two-vehicle collisions occurred 8 times, and there was one crash that involved three vehicles.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

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: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 33
  • Total persons involved: 50
  • Total vehicles involved: 43

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: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-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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