Monthly Traffic Safety Analysis

4,059 CRASHES IN
IOWA, IA
AUGUST 2015

In August 2015, Iowa recorded 4,059 motor vehicle crashes, resulting in 51 fatalities and 1,765 injuries. These incidents involved 9,156 people and 7,239 vehicles. A notable finding from the data is the high proportion of single-vehicle incidents, which accounted for 1,160 crashes, or 28.6% of the total for the month.

4,059

Total Crash Events

51

Persons Killed

1,765

Persons Injured

41

Fatal Crash Events

Note: "Persons Killed" (51) counts individual fatalities across all crash events. "Fatal" in the severity table below (41) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Motorists comprised the vast majority of those killed or seriously injured, with 45 fatalities and 1,694 injuries. However, vulnerable road users also suffered significant harm. Crashes resulted in 3 pedestrian fatalities and 21 pedestrian injuries. Additionally, there were 2 cyclist fatalities and 45 cyclist injuries during this period.

3

Pedestrians Killed

2

Cyclists Killed

45

Motorists Killed

1

Other Killed

21

Pedestrians Injured

45

Cyclists Injured

1,694

Motorists Injured

5

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequencies peaked during the weekday evening commute. The single busiest day for crashes was Monday, with 667 incidents, while the peak hour was the 4 PM hour with 367 crashes. Overall, a significant majority of collisions, 2,928 or approximately 72%, occurred during daylight hours.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 4,059 crashes, 2,671 (65.8%) resulted in no injuries, involving only property damage. The remaining incidents involved injuries of varying severity: 732 crashes with possible injuries, 485 with minor injuries, and 130 with serious injuries. There were 41 distinct fatal crashes, which resulted in a total of 51 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 41 fatal crash events resulted in 51 persons killed.

Outcome by Severity (Crash Events)

Fatal41fatal crashes1%
Serious Injury130serious injury crashes3.2%
Minor Injury485minor injury crashes11.9%
Possible Injury732possible injury crashes18%
No Injury2,671no injury crashes65.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor to crashes was 'Followed too close,' attributed to 521 incidents (12.8% of the total). Other leading factors included collisions with an animal (299 crashes, 7.4%), drivers losing control of their vehicle (259 crashes, 6.4%), and failure to yield the right-of-way from a stop sign (244 crashes, 6.0%).

Officer-Reported Primary Contributing Cause

Followed too close521 (12.8%)
Animal299 (7.4%)
Lost Control259 (6.4%)
Other (explain in narrative): Other256 (6.3%)
FTYROW: From stop sign244 (6%)
Ran off road - left219 (5.4%)
FTYROW: Making left turn201 (5%)
Ran off road - straight139 (3.4%)
Ran Stop Sign131 (3.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner129 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred in ideal driving conditions. Data shows that 2,752 crashes (67.8%) happened in clear weather, 3,301 (81.3%) on dry road surfaces, and 2,928 (72.1%) during daylight hours. Crashes in adverse conditions were less frequent, with 303 incidents occurring during rain and 383 on wet roads.

Weather

Clear2,752 (72.2%)
Cloudy724 (19.0%)
Rain303 (8.0%)
Fog, smoke, smog24 (0.6%)
Blowing sand, soil, dirt3 (0.1%)
Freezing rain/drizzle3 (0.1%)
Severe Winds1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Weather condition at time of crash

Lighting

Daylight2,928 (76.7%)
Dark - roadway lighted412 (10.8%)
Dark - roadway not lighted320 (8.4%)
Dusk77 (2.0%)
Dawn64 (1.7%)
Dark - unknown roadway lighting18 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Lighting condition field

Road Surface

Dry3,301 (86.5%)
Wet383 (10.0%)
Gravel112 (2.9%)
Other (explain in narrative)8 (0.2%)
Mud, dirt8 (0.2%)
Oil2 (0.1%)
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Road surface condition field

Vehicles & Demographics

Among persons involved in crashes, the 26-34 age group was the most represented, with 1,409 individuals, followed by the 16-20 age group (1,352) and the 35-44 age group (1,220). Analysis of the 7,239 vehicles involved shows that Chevrolet was the most common make with 1,447 vehicles, followed by Ford with 1,181 vehicles and Dodge with 516 vehicles.

Top Vehicle Makes (7,239 vehicles)

1
FORD1,181 (16.3%)
2
CHEV838 (11.6%)
3
CHEVROLET609 (8.4%)
4
DODG288 (4%)
5
TOYT272 (3.8%)
6
DODGE228 (3.1%)
7
HOND218 (3%)
8
JEEP217 (3%)
9
TOYOTA195 (2.7%)
10
PONT183 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Vehicle unit records

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

Sex Distribution (6,339 persons with recorded sex)

Male3,615 (57.0%)
Female2,724 (43.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Person-level records linked to crash events

Major Cause

The leading major cause identified in crashes was 'Followed too close,' which was cited in 521 incidents. Collisions with animals were the second-most common cause, accounting for 299 crashes. Other significant causes included drivers losing control (259 crashes), failure to yield from a stop sign (244 crashes), and running off the road to the left (219 crashes).

Major Cause

1
Followed too close521 (14%)
2
Animal299 (8%)
3
Lost Control259 (7%)
4
Other (explain in narrative): Other256 (6.9%)
5
FTYROW: From stop sign244 (6.6%)
6
Ran off road - left219 (5.9%)
7
FTYROW: Making left turn201 (5.4%)
8
Ran off road - straight139 (3.7%)
9
Ran Stop Sign131 (3.5%)

Showing top 9 of 49 reported. 40 additional (1,456 total) not shown: Operating vehicle in an reckless, erratic, careless, negligent manner, Ran Traffic Signal, Driver Distraction: Other interior distraction, Driving too fast for conditions, Made improper turn, Improper or erratic lane changing, FTYROW: From driveway, Other (explain in narrative): No improper action, FTYROW: Other (explain in narrative), Exceeded authorized speed, Swerving/Evasive Action, Driver Distraction: Inattentive/lost in thought, FTYROW: At uncontrolled intersection, Driver Distraction: Exterior distraction, Improper Backing, Failed to keep in proper lane, FTYROW: From parked position, FTYROW: From yield sign, Ran off road - right, Passing: Other passing (explain in narrative), Driver Distraction: Reaching for object(s)/fallen object(s), Driver Distraction: Manual operation of an electronic communication device, Other (explain in narrative): Vision obstructed, Driver Distraction: Passenger, FTYROW: Making right turn on red signal, Driver Distraction: Adjusting devices (radio, climate), Crossed centerline (undivided), Aggressive driving/road rage, Equipment failure, Traveling wrong way or on wrong side of road, Driver Distraction: Other electronic device activity, Other (explain in narrative): Disregarded signs/road markings, Passing: Through/around barrier, FTYROW: To pedestrian, Operator inexperience, Passing: Where prohibited by signs/markings, Driver Distraction: Unrestrained animal, Over correcting/over steering, Cargo/equipment loss or shift, Driver Distraction: Talking on a hand-held device.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

First Harmful Event

The most common first harmful event was a 'Collision with: Vehicle in traffic,' which occurred in 2,560 crashes, representing 63.1% of all incidents. A significant number of crashes involved leaving the roadway, including 290 collisions with animals and 175 collisions with a ditch. Overturns or rollovers were the first harmful event in 161 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic2,560 (63.7%)
2
Collision with: Animal290 (7.2%)
3
Collision with fixed object: Ditch175 (4.4%)
4
Non-collision events: Overturn/rollover161 (4%)
5
Collision with: Parked motor vehicle157 (3.9%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)67 (1.7%)
7
Collision with fixed object: Utility pole/light support65 (1.6%)
8
Collision with fixed object: Curb/island/raised median51 (1.3%)
9
Other (explain in narrative)49 (1.2%)

Showing top 9 of 47 reported. 38 additional (444 total) not shown: Collision with fixed object: Tree, Non-collision events: Other non-collision (explain in narrative), Miscellaneous events: Hit and run, Collision with: Re-entering roadway, Collision with fixed object: Traffic sign support, Collision with fixed object: Cable barrier, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Guardrail - face, Collision with fixed object: Embankment, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Fence, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with: Other non-fixed object (explain in narrative), Non-collision events: Fell/jumped from vehicle, Non-collision events: Vehicle went airborne, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Bridge/bridge rail parapet, Collision with: Thrown or falling object, Collision with fixed object: Ground, Collision with fixed object: Guardrail - end, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Building, Non-collision events: Jackknife, Collision with fixed object: Fire hydrant, Collision with fixed object: Mailbox, Collision with: Railway vehicle/train, Collision with fixed object: Bridge overhead structure, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Traffic signal support, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Impact attenuator/crash cushion, Collision with: Work zone maintenance equipment, Miscellaneous events: Immersion, Collision with fixed object: Bridge pier or support, Miscellaneous events: Vehicle out of gear/rolled, Collision with fixed object: Wall.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Roadway Junction / Feature

Crashes were distributed across different parts of the road network, with a slight majority occurring outside of intersections. Non-junction segments, including driveways and alleys, accounted for 2,225 crashes. In contrast, 1,511 crashes occurred at or were related to intersections, with four-way intersections being the most common type, hosting 1,099 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature1,898 (49.6%)
2
Intersection: Four-way intersection1,099 (28.7%)
3
Intersection: T-intersection273 (7.1%)
4
Non-intersection: Driveway access (related, not in)170 (4.4%)
5
Intersection: Other intersection (explain in narrative)64 (1.7%)
6
Non-intersection: Driveway access (within)59 (1.5%)
7
Non-intersection: Other non-intersection (explain in narrative)43 (1.1%)
8
Intersection: Intersection with ramp32 (0.8%)
9
Interchange-related: On-ramp merge area32 (0.8%)

Showing top 9 of 23 reported. 14 additional (157 total) not shown: Non-intersection: Crossover-related, Interchange-related: Off-ramp, Non-intersection: Alley, Intersection: Y-intersection, Interchange-related: Off-ramp, diverge area, Interchange-related: On-ramp, Non-intersection: Railroad grade crossing, Intersection: Five points or more, Intersection: L-intersection, Intersection: Roundabout, Interchange-related: Mainline, between ramps, Interchange-related: Other interchange (explain in narrative), Intersection: Traffic circle, Intersection: Shared use path or trail.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Vehicle Type

Passenger cars were the most prevalent vehicle type involved in crashes, accounting for 3,485 of the 7,239 vehicles. Sport utility vehicles were the second-most common with 1,477 vehicles, followed by four-tire light trucks and pickups with 1,112. Commercial vehicles and motorcycles were also involved, with 192 tractor-trailers and 160 motorcycles recorded in crashes.

Vehicle Type

"Other" combines 23 smaller categories (205 records): Single-unit truck (>= 3 axles) (49), Cargo/panel van (38), Moped (17), Farm tractor (13), Other bus (seats > 15) (12), Motor home/recreational vehicle (11), Passenger van (seats 9-15) (10), Truck/trailer (7), School bus (seats > 15) (7), All-terrain vehicle (ATV) (6), Truck tractor (bobtail) (5), Train (5), Golf cart (4), Other (explain in narrative) (4), Maintenance/construction vehicle (4), Tractor/doubles (4), 3-wheeled, unenclosed (2), Farm equipment (explain in narrative) (2), Small school bus (seats 9-15) (1), Other small bus (seats 9-15) (1), Other light truck (<=10000 lbs) (1), Other heavy truck (> 10000 lbs) (cannot classify) (1), Limousine/taxi (sets >15) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Vehicle unit records

Traffic Control Device

Analysis of the 6,894 vehicles with traffic control information shows that a majority were operating where no traffic controls were present (4,082 vehicles). For crashes at controlled locations, traffic signals were the most common device, present for 1,767 vehicles. Stop signs were the next most frequent control, noted for 752 vehicles involved in crashes.

Traffic Control Device

"Other" combines 5 smaller categories (77 records): Flashing traffic control signal (37), Warning sign (23), Railway crossing device (11), Traffic director (person) (4), Inoperative (not functioning properly) (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most frequently damaged area, recorded in 1,931 instances. The rear of the vehicle was the second-most common point of impact, with 1,036 instances, which is consistent with the high number of rear-end collisions. Damage to the driver-side and passenger-side middle areas, indicative of angle or broadside collisions, was recorded in 394 and 357 cases, respectively.

Most Damaged Area

"Other" combines 10 smaller categories (1,537 records): Passenger side - front (310), Driver side - rear (249), Rear - driver side corner (239), Passenger side - rear (230), Rear - passenger side corner (168), Top (135), Other (explain in narrative) (94), Non-collision/no damage (62), Undercarriage (44), Cargo loss (6).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

A total of 181 crashes involved a driver noted for impairment, representing 4.5% of all crashes. Among these, alcohol was the most common factor, cited in 158 cases. Drugs were a factor in 17 crashes, and a combination of alcohol and drugs was noted in 6 incidents.

Crashes by County

Crash distribution was concentrated in Iowa's most populous counties. Polk County recorded the highest number of incidents with 840 crashes, accounting for 20.7% of the statewide total. Scott County followed with 311 crashes, Linn County with 246, Johnson County with 185, and Black Hawk County with 165.

Crashes by County

1
POLK840 (23%)
2
SCOTT311 (8.5%)
3
LINN246 (6.7%)
4
JOHNSON185 (5.1%)
5
BLACK HAWK165 (4.5%)
6
WOODBURY164 (4.5%)
7
POTTAWATTAMIE153 (4.2%)
8
DUBUQUE152 (4.2%)
9
STORY115 (3.1%)

Showing top 9 of 50 reported. 41 additional (1,323 total) not shown: DALLAS, DES MOINES, CERRO GORDO, LEE, WEBSTER, CLINTON, WARREN, WAPELLO, MARSHALL, JASPER, MUSCATINE, MARION, SIOUX, BOONE, HENRY, BREMER, PLYMOUTH, IOWA, WASHINGTON, DICKINSON, HARRISON, BUENA VISTA, BENTON, MILLS, MAHASKA, JONES, CARROLL, CEDAR, CASS, BUCHANAN, HAMILTON, HARDIN, WINNESHIEK, CLARKE, CLAY, ALLAMAKEE, POWESHIEK, CRAWFORD, JEFFERSON, JACKSON, FAYETTE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Crashes by City

Among municipalities, Des Moines had the highest crash volume with 476 incidents. Other cities with high crash counts include Davenport with 239 crashes, Cedar Rapids with 158, and Sioux City with 146. A significant number of crashes occur in unincorporated areas and are not included in this city-level breakdown.

Crashes by City

1
DES MOINES476 (18.4%)
2
DAVENPORT239 (9.3%)
3
CEDAR RAPIDS158 (6.1%)
4
SIOUX CITY146 (5.7%)
5
DUBUQUE124 (4.8%)
6
COUNCIL BLUFFS116 (4.5%)
7
IOWA CITY106 (4.1%)
8
WATERLOO106 (4.1%)
9
WEST DES MOINES103 (4%)

Showing top 9 of 50 reported. 41 additional (1,008 total) not shown: AMES, ANKENY, BURLINGTON, FORT DODGE, URBANDALE, MASON CITY, CORALVILLE, BETTENDORF, CEDAR FALLS, MARION, CLINTON, ALTOONA, CLIVE, MARSHALLTOWN, OTTUMWA, INDIANOLA, PLEASANT HILL, KEOKUK, MUSCATINE, FORT MADISON, STORM LAKE, PELLA, WAVERLY, WAUKEE, BOONE, CARROLL, HIAWATHA, WINDSOR HEIGHTS, MOUNT PLEASANT, CLEAR LAKE, GRIMES, NEWTON, LE MARS, SPIRIT LAKE, INDEPENDENCE, DENISON, OSCEOLA, OSKALOOSA, JOHNSTON, WEBSTER CITY, CRESTON.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 3,832, occurred on paved roadways. However, Iowa's extensive secondary road network was also a factor, with 204 crashes, or 5.1% of the total with surface data, taking place on unpaved gravel or dirt roads.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Roadway Contributing Factor

Roadway-related factors were identified as contributors in a minority of crashes. The most common factor was 'Surface condition (e.g.wet, icy),' cited in 91 incidents. Work zone-related issues were the second-leading roadway factor, contributing to 89 crashes during this period.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)91 (35%)
2
Work Zone (roadway-related)89 (34.2%)
3
Slippery, loose or worn surface20 (7.7%)
4
Debris15 (5.8%)
5
Traffic backup, prior crash13 (5%)
6
Traffic backup, regular congestion8 (3.1%)
7
Obstruction in roadway8 (3.1%)
8
Ruts/holes/bumps4 (1.5%)
9
Shoulders (none, low, soft, high)4 (1.5%)

Showing top 9 of 12 reported. 3 additional (8 total) not shown: Disabled vehicle, Traffic backup, prior non-recurring incident, Non-highway work.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Driver Condition

Among drivers where a condition other than 'apparently normal' was noted, impairment was the most frequent. A total of 188 drivers were recorded as being under the influence of alcohol. The next most common condition was being asleep or fatigued, which was noted for 75 drivers, followed by being emotional (e.g., depressed, angry), which was recorded for 45 drivers.

Driver Condition

1
Under the influence of alcohol188 (50.7%)
2
Asleep/fatigued75 (20.2%)
3
Emotional (e.g. depressed, angry)45 (12.1%)
4
Medical condition (seizure, reaction)26 (7%)
5
Under the influence of drugs/meds17 (4.6%)
6
Illness/fainted10 (2.7%)
7
Physical impairment5 (1.3%)
8
Paraplegic/wheelchair restricted2 (0.5%)
9
Visually impaired2 (0.5%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Walks with a cane/crutches.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Crashes by Iowa DOT District

The distribution of crashes across Iowa's six DOT districts shows that District 1, which includes the Des Moines metro area, had the highest volume with 1,226 crashes. District 6, covering eastern Iowa including Cedar Rapids and Davenport, recorded the second-highest number with 1,090 crashes. These two districts combined accounted for over half of all crashes in the state.

Crashes by Iowa DOT District

1
District 11,226 (30.2%)
2
District 61,090 (26.9%)
3
District 5487 (12%)
4
District 2425 (10.5%)
5
District 3416 (10.2%)
6
District 4415 (10.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Property Damage

Based on officer-estimated property damage, the most common cost bracket was '$1,500 - $7,500,' which applied to 2,831 crashes. A smaller but significant number of incidents resulted in severe damage, with 105 crashes (2.6% of the total) estimated to have damage costs exceeding $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Manner of Collision

The two most common types of collisions were non-collision single-vehicle events (1,160 crashes, 28.6%) and rear-end collisions (1,125 crashes, 27.7%). Together, these two categories accounted for more than half of all reported incidents. Broadside collisions were the third-most frequent type, with 692 occurrences.

Manner of Collision

"Other" combines 3 smaller categories (161 records): Sideswipe, opposite direction (75), Head-on (front to front) (73), Rear to rear (13).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Pre-Crash Driver Action

The vast majority of vehicles involved in crashes were engaged in straightforward movement. Of the vehicles with pre-crash action data, 4,058 were recorded as 'Movement essentially straight.' The next most common actions were 'Turning left' (715 vehicles) and 'Slowing/stopping' (427 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight4,058 (58%)
2
Turning left715 (10.2%)
3
Slowing/stopping (deceleration)427 (6.1%)
4
Stopped in traffic425 (6.1%)
5
Legally Parked363 (5.2%)
6
Turning right273 (3.9%)
7
Backing181 (2.6%)
8
Other (explain in narrative)146 (2.1%)
9
Changing lanes124 (1.8%)

Showing top 9 of 19 reported. 10 additional (279 total) not shown: Negotiating a curve, Entering traffic lane (merging), Overtaking/passing, Accelerating in road, Starting in road, Leaving a parked position, Illegally Parked/Unattended, Making U-turn, Leaving traffic lane, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Vehicle unit records

Pedestrian/Cyclist Action

Among the 77 recorded actions for pedestrians and bicyclists involved in crashes, the most common was 'Entering or crossing roadway,' which was noted in 48 instances. The second-most frequent action was moving along the roadway with traffic, which was recorded 10 times.

Pedestrian/Cyclist Action

1
Entering or crossing roadway48 (62.3%)
2
Movement: Along roadway with traffic10 (13%)
3
Other7 (9.1%)
4
Movement: On sidewalk4 (5.2%)
5
Disabled vehicle-related/pushing vehicle2 (2.6%)
6
Movement: Along roadway against traffic2 (2.6%)
7
Movement: Along roadway (direction unknown)1 (1.3%)
8
Entering/exiting vehicle1 (1.3%)
9
Waiting to cross roadway1 (1.3%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Working in trafficway.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Non-motorist records linked to crash events

Person Type

Of the 9,156 people involved in crashes, the overwhelming majority were drivers, accounting for 8,602 individuals (94.0%). Passengers made up the next largest group with 476 people. Vulnerable road users included 47 bicyclists and 24 pedestrians.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Person Injury Severity

Out of 9,156 total persons involved in crashes, 1,816 suffered some level of injury or were killed. This includes 51 fatalities, 147 serious injuries, 650 minor injuries, and 968 possible injuries. The data indicates that approximately one in five people involved in a crash sustained an injury.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Crash-level records

Occupant Safety Equipment

Among vehicle occupants for whom safety equipment use was recorded, 1,115 were reported as using a shoulder and lap belt. A concerning number, 154 individuals, were recorded as using no safety equipment at all. An additional 38 individuals, likely motorcyclists, were noted as wearing a DOT-compliant helmet.

Occupant Safety Equipment

"Other" combines 3 smaller categories (12 records): Other (5), Helmet (other) (5), Shoulder belt only used (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common type of crash, accounting for 2,608 incidents (64.2% of the total). Single-vehicle crashes were also very frequent, with 1,187 incidents, making up 29.2% of all crashes. Multi-vehicle crashes involving three or more vehicles were less common, with 224 such incidents recorded.

Vehicles Per Crash

"Other" combines 1 smaller categories (1 records): 7 (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-08-01 to 2015-08-31 · 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: 2015-08-01 through 2015-08-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-08-01 through 2015-08-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,059
  • Total persons involved: 9,156
  • Total vehicles involved: 7,239

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: August 2015." Published September 9, 2026. Reporting period: 2015-08-01 to 2015-08-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/august-2015-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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