Yearly Traffic Safety Analysis

126 CRASHES IN
IOWA, IA
2015

In 2015, Montgomery County recorded 126 traffic crashes, resulting in 1 fatality and 52 injuries. A significant portion of these incidents, 35.7%, were single-vehicle, non-collision events. The most frequently cited contributing factor was collisions with animals, accounting for 10.3% of all crashes.

126

Total Crash Events

1

Persons Killed

52

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, all reported traffic fatalities and injuries in Montgomery County involved motor vehicle occupants. One motorist was killed and 52 were injured in crashes. There were no recorded fatalities or injuries involving pedestrians or cyclists during this period.

1

Motorists Killed

52

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 Montgomery County were most frequent on Wednesdays, which saw 23 incidents over the year. The afternoon commute hours were peak times for collisions, with both the 3 p.m. and 5 p.m. hours recording 13 crashes each. The majority of crashes, 91 out of 126, occurred during daylight hours.

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

Of the 126 total crashes, 69% (87 crashes) resulted in no injuries and were classified as property-damage-only. The remaining 31% involved some level of injury, including one fatal crash, 5 serious injury crashes, and 33 minor or possible injury crashes. The single fatal crash resulted in one fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
Serious Injury5serious injury crashes4%
Minor Injury15minor injury crashes11.9%
Possible Injury18possible injury crashes14.3%
No Injury87no injury crashes69%

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 identified in crashes was 'Animal,' cited in 13 incidents (10.3%). This was followed by 'Followed too close' and 'Lost Control,' each contributing to 11 crashes (8.7% each). 'Ran Stop Sign' was another significant factor, noted in 9 crashes, or 7.1% of the total.

Officer-Reported Primary Contributing Cause

Animal13 (10.3%)
Followed too close11 (8.7%)
Lost Control11 (8.7%)
Ran Stop Sign9 (7.1%)
Driving too fast for conditions7 (5.6%)
FTYROW: At uncontrolled intersection7 (5.6%)
FTYROW: From yield sign7 (5.6%)
Other (explain in narrative): Other6 (4.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner6 (4.8%)
Ran off road - straight5 (4%)

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

Road & Environmental Conditions

The majority of collisions occurred under ideal driving conditions, with 72.2% (91 crashes) happening in daylight. Similarly, 61.9% of crashes (78 incidents) took place on dry road surfaces, and 54% (68 incidents) occurred in clear weather. Adverse conditions were less frequent, with 13 crashes on wet roads and 7 on snow-covered surfaces.

Weather

Clear68 (59.1%)
Cloudy37 (32.2%)
Rain5 (4.3%)
Freezing rain/drizzle2 (1.7%)
Snow2 (1.7%)
Fog, smoke, smog1 (0.9%)

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

Lighting

Daylight91 (77.8%)
Dark - roadway not lighted11 (9.4%)
Dark - roadway lighted6 (5.1%)
Dusk5 (4.3%)
Dawn3 (2.6%)
Dark - unknown roadway lighting1 (0.9%)

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

Road Surface

Dry78 (67.2%)
Wet13 (11.2%)
Gravel8 (6.9%)
Snow7 (6.0%)
Ice/frost6 (5.2%)
Slush2 (1.7%)
Sand1 (0.9%)
Mud, dirt1 (0.9%)

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

Vehicles & Demographics

Combining abbreviated and full names, Chevrolet was the most frequent vehicle make involved in crashes with 41 vehicles, followed by Ford with 36 and Dodge with 27. Among all persons involved in crashes, the 16-20 age group was the most represented with 47 individuals, followed by the 65+ age group with 41 individuals.

Top Vehicle Makes (209 vehicles)

1
FORD36 (17.2%)
2
CHEV29 (13.9%)
3
DODG19 (9.1%)
4
CHEVROLET12 (5.7%)
5
DODGE8 (3.8%)
6
PONT8 (3.8%)
7
BUIC7 (3.3%)
8
OLDS6 (2.9%)
9
TOYT6 (2.9%)
10
CHRY5 (2.4%)

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

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

Sex Distribution (180 persons with recorded sex)

Male93 (51.7%)
Female87 (48.3%)

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 common major cause attributed to crashes was interactions with animals, accounting for 13 incidents. Following this, 'Followed too close' and 'Lost Control' were each cited as the major cause in 11 crashes. Running a stop sign was the cause for 9 crashes.

Major Cause

1
Animal13 (10.9%)
2
Followed too close11 (9.2%)
3
Lost Control11 (9.2%)
4
Ran Stop Sign9 (7.6%)
5
Driving too fast for conditions7 (5.9%)
6
FTYROW: At uncontrolled intersection7 (5.9%)
7
FTYROW: From yield sign7 (5.9%)
8
Other (explain in narrative): Other6 (5%)
9
Operating vehicle in an reckless, erratic, careless, negligent manner6 (5%)

Showing top 9 of 31 reported. 22 additional (42 total) not shown: Ran off road - straight, FTYROW: From stop sign, Improper Backing, Ran off road - left, Driver Distraction: Exterior distraction, Made improper turn, FTYROW: Making left turn, Swerving/Evasive Action, Other (explain in narrative): No improper action, Driver Distraction: Other interior distraction, Driver Distraction: Reaching for object(s)/fallen object(s), Exceeded authorized speed, Failed to keep in proper lane, Driver Distraction: Manual operation of an electronic communication device, FTYROW: From parked position, Cargo/equipment loss or shift, Driver Distraction: Inattentive/lost in thought, Other (explain in narrative): Vision obstructed, Passing: Through/around barrier, Ran Traffic Signal, Driver Distraction: Passenger, Separation of units.

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

First Harmful Event

The most frequent first harmful event was a collision with another vehicle in traffic, which occurred in 66 crashes. Collisions with animals were the second most common event, recorded in 13 incidents. Collisions with fixed objects, such as ditches (7 crashes) and parked vehicles (7 crashes), were also a notable pattern.

First Harmful Event

1
Collision with: Vehicle in traffic66 (53.7%)
2
Collision with: Animal13 (10.6%)
3
Collision with fixed object: Ditch7 (5.7%)
4
Collision with: Parked motor vehicle7 (5.7%)
5
Non-collision events: Non-contact vehicle (phantom)4 (3.3%)
6
Non-collision events: Overturn/rollover3 (2.4%)
7
Collision with: Struck/struck by object/cargo/person from other vehicle3 (2.4%)
8
Collision with fixed object: Traffic sign support2 (1.6%)
9
Collision with fixed object: Bridge/bridge rail parapet2 (1.6%)

Showing top 9 of 23 reported. 14 additional (16 total) not shown: Collision with fixed object: Tree, Miscellaneous events: Hit and run, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Cable barrier, Collision with fixed object: Utility pole/light support, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Mailbox, Collision with fixed object: Ground, Collision with fixed object: Fence, Other (explain in narrative), Collision with fixed object: Embankment, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Other traffic barrier (explain in narrative).

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

Roadway Junction / Feature

Crashes were slightly more common on non-intersection road segments, which accounted for 53 incidents, compared to 39 crashes at four-way intersections. An additional 8 crashes were related to driveway access. Overall, crashes at or related to intersections comprised approximately 44% of the total where junction type was specified.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature53 (45.7%)
2
Intersection: Four-way intersection39 (33.6%)
3
Non-intersection: Driveway access (related, not in)8 (6.9%)
4
Intersection: T-intersection6 (5.2%)
5
Intersection: Other intersection (explain in narrative)4 (3.4%)
6
Non-intersection: Other non-intersection (explain in narrative)2 (1.7%)
7
Non-intersection: Driveway access (within)1 (0.9%)
8
Intersection: Y-intersection1 (0.9%)
9
Non-intersection: Alley1 (0.9%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Intersection: Traffic circle.

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

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, with 96 vehicles recorded. Sport utility vehicles (40 vehicles) and light pickup trucks (39 vehicles) were the next most frequent types. A small number of motorcycles (3) and tractor-trailers (3) were also involved in collisions.

Vehicle Type

"Other" combines 5 smaller categories (6 records): Farm tractor (2), Cargo/panel van (1), Single unit truck (2-axle, 6-tire) (1), Single-unit truck (>= 3 axles) (1), Farm equipment (explain in narrative) (1).

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

Traffic Control Device

A significant majority of vehicles involved in crashes were on roadways with no traffic controls present, accounting for 144 of the 209 vehicles. For crashes where traffic controls were a factor, stop signs were the most common, present for 24 vehicles. Traffic signals were noted for 13 vehicles involved in collisions.

Traffic Control Device

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

Most Damaged Area

Frontal impacts were the most common area of vehicle damage, with the primary front area being the most damaged point on 44 vehicles. Including corners, front-related impacts accounted for 89 vehicles. Rear damage was noted as the most severe on 21 vehicles, while various side impacts were the primary damage area for 56 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (48 records): Driver side - front (11), Passenger side - front (8), Passenger side - rear (7), Driver side - rear (7), Top (4), Non-collision/no damage (4), Rear - driver side corner (4), Other (explain in narrative) (2), Undercarriage (1).

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

Crashes by City

The vast majority of crashes within municipal limits occurred in Red Oak, which saw 75 incidents. Far fewer crashes were recorded in other towns, with Villisca reporting 6 crashes. Stanton and Elliott each had only one crash reported within their city limits.

Crashes by City

1
RED OAK75 (90.4%)
2
VILLISCA6 (7.2%)
3
ELLIOTT1 (1.2%)
4
STANTON1 (1.2%)

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

Paved vs Unpaved Road

Crashes on unpaved roads, such as gravel or dirt, accounted for 12 of the 126 total incidents, representing 9.5% of all crashes in the county. The remaining 114 crashes occurred on paved surfaces.

Paved vs Unpaved Road

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

Roadway Contributing Factor

In cases where a roadway factor was noted as a contributor, the most common was 'Surface condition,' cited in 17 crashes, which typically refers to wet or icy surfaces. Other factors like 'Slippery, loose or worn surface' and 'Work zone' were cited in 2 and 1 crashes, respectively.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)17 (73.9%)
2
Slippery, loose or worn surface2 (8.7%)
3
Ruts/holes/bumps1 (4.3%)
4
Shoulders (none, low, soft, high)1 (4.3%)
5
Traffic backup, prior crash1 (4.3%)
6
Work Zone (roadway-related)1 (4.3%)

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, impairment from alcohol was the most frequent, noted for 3 drivers. Other conditions included being asleep or fatigued (2 drivers), an emotional state (2 drivers), and a medical condition (2 drivers).

Driver Condition

1
Under the influence of alcohol3 (27.3%)
2
Asleep/fatigued2 (18.2%)
3
Emotional (e.g. depressed, angry)2 (18.2%)
4
Medical condition (seizure, reaction)2 (18.2%)
5
Illness/fainted1 (9.1%)
6
Under the influence of drugs/meds1 (9.1%)

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

Property Damage

The most common estimated property damage cost was in the $1,500 to $7,500 range, which applied to 87 of the 126 crashes. A smaller number of crashes, 34, resulted in damages between $7,500 and $25,000. Only one crash was reported with damage costs 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 most common crash type was a non-collision event involving a single vehicle, such as running off the road, which accounted for 45 incidents (35.7%). Broadside collisions were the second most frequent pattern with 35 crashes (27.8%), followed by rear-end collisions, which occurred 21 times (16.7%).

Manner of Collision

"Other" combines 2 smaller categories (4 records): Sideswipe, opposite direction (2), Angle, oncoming left turn (2).

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

Pre-Crash Driver Action

The vast majority of vehicles, 134 out of 209, were moving straight ahead just prior to their collision. The next most common pre-crash actions were being legally parked, which applied to 15 vehicles, and turning left, which was the action for 13 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight134 (66.7%)
2
Legally Parked15 (7.5%)
3
Turning left13 (6.5%)
4
Backing8 (4%)
5
Slowing/stopping (deceleration)6 (3%)
6
Other (explain in narrative)6 (3%)
7
Stopped in traffic4 (2%)
8
Negotiating a curve3 (1.5%)
9
Illegally Parked/Unattended3 (1.5%)

Showing top 9 of 15 reported. 6 additional (9 total) not shown: Making U-turn, Entering a parked position, Overtaking/passing, Leaving traffic lane, Changing lanes, Turning right.

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

Person Type

Of the 263 people involved in traffic crashes, the overwhelming majority were drivers, accounting for 248 individuals or 94.3%. The remaining 15 individuals were passengers in vehicles. No pedestrians or other non-occupant types were recorded in the crash data for this period.

Person Type

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

Person Injury Severity

Across all persons involved in crashes, 53 individuals sustained some level of injury or were killed. This total includes one fatality, 6 serious injuries, 22 minor injuries, and 24 possible injuries. The remaining 210 persons involved were not injured.

Person Injury Severity

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

Occupant Safety Equipment

Among the small subset of vehicle occupants for whom safety equipment use was recorded, 11 out of 43 individuals (25.6%) were noted as not using any restraints. The majority in this group, 32 individuals, were recorded as using a shoulder and lap belt. Data on restraint use was not available for most participants.

Occupant Safety Equipment

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

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 77 of the 126 total crashes (61.1%). Single-vehicle crashes were also frequent, with 46 incidents making up 36.5% of the total. Crashes involving three vehicles were rare, with only 3 such events recorded.

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: 126
  • Total persons involved: 263
  • Total vehicles involved: 209

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

ThatCarHitMe.com · An Injuria.ai Company