Monthly Traffic Safety Analysis

4,336 CRASHES IN
IOWA, IA
JUNE 2015

In June 2015, Iowa reported 4,336 traffic crashes, resulting in 25 fatalities and 1,548 injuries. A notable finding from the data is that collisions with animals were the single most frequently cited contributing factor, accounting for 758 incidents, or 17.5% of all crashes during this period.

4,336

Total Crash Events

25

Persons Killed

1,548

Persons Injured

23

Fatal Crash Events

Note: "Persons Killed" (25) counts individual fatalities across all crash events. "Fatal" in the severity table below (23) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Motorists comprised the largest group of individuals killed or injured, with 20 fatalities and 1,464 injuries. Vulnerable road users also suffered significant harm; 3 pedestrians were killed and 31 were injured. Additionally, 1 cyclist was killed and 50 were injured during this period.

3

Pedestrians Killed

1

Cyclists Killed

20

Motorists Killed

1

Other Killed

31

Pedestrians Injured

50

Cyclists Injured

1,464

Motorists Injured

3

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency in Iowa during this period peaked on Mondays, which saw 777 incidents. The single busiest hour for crashes was the afternoon commute period from 4:00 PM to 4:59 PM, with 371 events. A significant majority of crashes, 2,983 or approximately 69%, occurred during daylight hours.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The majority of crashes, 3,051 out of 4,336 (70.4%), resulted in no injuries and involved only property damage. The remaining 29.6% of crashes involved some level of injury, including 114 serious injury crashes and 440 minor injury crashes. There were 23 distinct fatal crashes, which resulted in a total of 25 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 23 fatal crash events resulted in 25 persons killed.

Outcome by Severity (Crash Events)

Fatal23fatal crashes0.5%
Serious Injury114serious injury crashes2.6%
Minor Injury440minor injury crashes10.1%
Possible Injury708possible injury crashes16.3%
No Injury3,051no injury crashes70.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Most severe injury per crash record

Top Contributing Factors

The most common contributing factor identified in crashes was an animal in the roadway, cited in 758 incidents (17.5%). Following this, driver behaviors such as following too closely (409 crashes, 9.4%), losing control of the vehicle (262 crashes, 6.0%), and failure to yield the right-of-way from a stop sign (245 crashes, 5.7%) were the next most frequent causes.

Officer-Reported Primary Contributing Cause

Animal758 (17.5%)
Followed too close409 (9.4%)
Lost Control262 (6%)
FTYROW: From stop sign245 (5.7%)
Ran off road - left228 (5.3%)
Other (explain in narrative): Other215 (5%)
FTYROW: Making left turn195 (4.5%)
Ran Traffic Signal153 (3.5%)
Ran off road - straight134 (3.1%)
Driving too fast for conditions114 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The vast majority of crashes occurred in ideal driving conditions. Approximately 69% of incidents (2,983 crashes) happened in daylight, 70.5% (3,058 crashes) on dry road surfaces, and 52.5% (2,276 crashes) in clear weather. Adverse conditions were less frequent, with 443 crashes occurring during rain and 577 on wet roads.

Weather

Clear2,276 (60.9%)
Cloudy988 (26.4%)
Rain443 (11.9%)
Fog, smoke, smog21 (0.6%)
Freezing rain/drizzle5 (0.1%)
Sleet, hail2 (0.1%)
Severe Winds1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Weather condition at time of crash

Lighting

Daylight2,983 (79.3%)
Dark - roadway lighted323 (8.6%)
Dark - roadway not lighted312 (8.3%)
Dusk74 (2.0%)
Dawn59 (1.6%)
Dark - unknown roadway lighting11 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Lighting condition field

Road Surface

Dry3,058 (81.7%)
Wet577 (15.4%)
Gravel97 (2.6%)
Other (explain in narrative)5 (0.1%)
Mud, dirt3 (0.1%)
Water (standing or moving)3 (0.1%)
Sand1 (0.0%)
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Road surface condition field

Vehicles & Demographics

Among the 9,030 people involved in crashes, the most represented age groups were 26-34 year olds (1,359 people), 16-20 year olds (1,285 people), and 45-54 year olds (1,213 people). Of the 7,347 vehicles involved, the most frequent makes were Chevrolet (1,430 vehicles), Ford (1,238 vehicles), and Toyota (516 vehicles).

Top Vehicle Makes (7,347 vehicles)

1
FORD1,238 (16.9%)
2
CHEV803 (10.9%)
3
CHEVROLET627 (8.5%)
4
TOYT278 (3.8%)
5
DODG269 (3.7%)
6
TOYOTA238 (3.2%)
7
DODGE230 (3.1%)
8
JEEP206 (2.8%)
9
HOND200 (2.7%)
10
GMC185 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Vehicle unit records

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

Sex Distribution (6,361 persons with recorded sex)

Male3,587 (56.4%)
Female2,774 (43.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Person-level records linked to crash events

Major Cause

The leading major cause attributed to crashes was an animal, responsible for 758 incidents (17.5%). Other significant causes included drivers following too closely (409 crashes), losing control (262 crashes), and failing to yield the right-of-way from a stop sign (245 crashes). Driver distraction was noted in several forms, including other interior distraction (90 crashes) and inattentiveness (61 crashes).

Major Cause

1
Animal758 (18.8%)
2
Followed too close409 (10.2%)
3
Lost Control262 (6.5%)
4
FTYROW: From stop sign245 (6.1%)
5
Ran off road - left228 (5.7%)
6
Other (explain in narrative): Other215 (5.3%)
7
FTYROW: Making left turn195 (4.8%)
8
Ran Traffic Signal153 (3.8%)
9
Ran off road - straight134 (3.3%)

Showing top 9 of 49 reported. 40 additional (1,425 total) not shown: Driving too fast for conditions, Operating vehicle in an reckless, erratic, careless, negligent manner, Ran Stop Sign, Driver Distraction: Other interior distraction, Made improper turn, Improper or erratic lane changing, Other (explain in narrative): No improper action, FTYROW: From driveway, Driver Distraction: Inattentive/lost in thought, Swerving/Evasive Action, Improper Backing, FTYROW: Other (explain in narrative), Driver Distraction: Exterior distraction, Exceeded authorized speed, FTYROW: At uncontrolled intersection, FTYROW: From parked position, FTYROW: From yield sign, Failed to keep in proper lane, Driver Distraction: Reaching for object(s)/fallen object(s), Driver Distraction: Manual operation of an electronic communication device, Passing: Other passing (explain in narrative), Driver Distraction: Passenger, Ran off road - right, Driver Distraction: Adjusting devices (radio, climate), Crossed centerline (undivided), FTYROW: To pedestrian, Other (explain in narrative): Vision obstructed, FTYROW: Making right turn on red signal, Traveling wrong way or on wrong side of road, Driver Distraction: Other electronic device activity, Passing: With insufficient distance/inadequate visibility, Driver Distraction: Talking on a hand-held device, Passing: Through/around barrier, Equipment failure, Aggressive driving/road rage, Operator inexperience, Cargo/equipment loss or shift, Illegally Parked/Unattended, Failed to yield to emergency vehicle, Driver Distraction: Unrestrained animal.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, which occurred in 2,376 crashes, representing 54.8% of the total. The second most frequent event was a collision with an animal, documented in 745 cases (17.2%). Single-vehicle run-off-road events were also common, with the first harmful event being a collision with a ditch (201 crashes) or an overturn/rollover (158 crashes).

First Harmful Event

1
Collision with: Vehicle in traffic2,376 (55.3%)
2
Collision with: Animal745 (17.3%)
3
Collision with fixed object: Ditch201 (4.7%)
4
Collision with: Parked motor vehicle185 (4.3%)
5
Non-collision events: Overturn/rollover158 (3.7%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)76 (1.8%)
7
Collision with fixed object: Utility pole/light support54 (1.3%)
8
Other (explain in narrative)41 (1%)
9
Collision with: Re-entering roadway37 (0.9%)

Showing top 9 of 46 reported. 37 additional (426 total) not shown: Collision with fixed object: Cable barrier, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Curb/island/raised median, Collision with fixed object: Tree, Collision with fixed object: Other post/pole/support (explain in narrative), Miscellaneous events: Hit and run, Collision with fixed object: Traffic sign support, Collision with fixed object: Guardrail - face, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Other non-fixed object (explain in narrative), Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Embankment, Collision with fixed object: Ground, Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Fence, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Building, Collision with fixed object: Other fixed object (explain in narrative), Non-collision events: Vehicle went airborne, Non-collision events: Jackknife, Collision with fixed object: Mailbox, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fire hydrant, Collision with fixed object: Landscape/shrubbery, Collision with: Work zone maintenance equipment, Collision with fixed object: Culvert/pipe opening, Collision with: Thrown or falling object, Collision with fixed object: Guardrail - end, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with: Railway vehicle/train, Miscellaneous events: Fire/explosion, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Bridge pier or support, Miscellaneous events: Immersion, Collision with fixed object: Wall, Miscellaneous events: Vehicle out of gear/rolled.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Roadway Junction / Feature

Crashes occurred more frequently on non-intersection segments of roadway than at junctions. There were 1,938 crashes recorded at non-junction locations. Among intersections, the most common type was a four-way intersection, which accounted for 1,004 crashes, followed by T-intersections with 252 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature1,938 (51.5%)
2
Intersection: Four-way intersection1,004 (26.7%)
3
Intersection: T-intersection252 (6.7%)
4
Non-intersection: Driveway access (related, not in)164 (4.4%)
5
Intersection: Other intersection (explain in narrative)58 (1.5%)
6
Non-intersection: Other non-intersection (explain in narrative)48 (1.3%)
7
Non-intersection: Driveway access (within)46 (1.2%)
8
Intersection: Intersection with ramp46 (1.2%)
9
Interchange-related: On-ramp merge area32 (0.9%)

Showing top 9 of 22 reported. 13 additional (174 total) not shown: Interchange-related: Off-ramp, Non-intersection: Alley, Non-intersection: Crossover-related, Interchange-related: On-ramp, Non-intersection: Railroad grade crossing, Intersection: Y-intersection, Interchange-related: Off-ramp, diverge area, Intersection: Five points or more, Interchange-related: Other interchange (explain in narrative), Intersection: L-intersection, Interchange-related: Mainline, between ramps, Intersection: Roundabout, Non-intersection: Bike lanes.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 3,603 of the 7,347 vehicles. Sport utility vehicles (1,471 vehicles) and four-tire light trucks or pickups (1,082 vehicles) were the next most frequent. Commercial vehicles and motorcycles represented smaller portions, with 187 tractor-trailers and 168 motorcycles involved in incidents.

Vehicle Type

"Other" combines 22 smaller categories (194 records): Cargo/panel van (50), Single-unit truck (>= 3 axles) (33), Passenger van (seats 9-15) (18), Farm tractor (11), Moped (10), Motor home/recreational vehicle (9), Truck tractor (bobtail) (8), Truck/trailer (8), All-terrain vehicle (ATV) (7), Other light truck (<=10000 lbs) (6), Farm equipment (explain in narrative) (6), Other bus (seats > 15) (6), Maintenance/construction vehicle (5), Train (4), School bus (seats > 15) (3), Other heavy truck (> 10000 lbs) (cannot classify) (2), Tractor/doubles (2), Other small bus (seats 9-15) (2), 3-wheeled, unenclosed (1), 3-wheeled, enclosed (1), Other (explain in narrative) (1), Golf cart (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Vehicle unit records

Traffic Control Device

A large number of incidents, 4,130, occurred at locations where no traffic controls were present. For crashes at controlled locations, traffic signals were the most common device, present at 1,551 incidents. Stop signs were the second most common form of traffic control, noted in 705 crashes.

Traffic Control Device

"Other" combines 5 smaller categories (79 records): Flashing traffic control signal (31), Warning sign (28), Railway crossing device (13), Inoperative (not functioning properly) (6), Traffic director (person) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most frequent area of most severe damage, recorded for 1,855 vehicles. This was followed by the rear of the vehicle, which sustained the most damage in 979 cases, suggesting a high prevalence of rear-end collisions. Damage to the driver-side and passenger-side areas was also significant, with 410 and 316 vehicles sustaining primary damage to their middle sections, respectively, indicative of angle or broadside impacts.

Most Damaged Area

"Other" combines 10 smaller categories (1,501 records): Passenger side - front (316), Rear - driver side corner (236), Driver side - rear (220), Passenger side - rear (210), Rear - passenger side corner (193), Top (149), Other (explain in narrative) (98), Non-collision/no damage (38), Undercarriage (35), Cargo loss (6).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Vehicle unit records

Impairment (Alcohol / Drugs)

Driver impairment was noted in 156 crashes, representing approximately 3.6% of all incidents. Of these, alcohol was the sole factor in 138 cases. Drugs were a factor in 15 crashes, and a combination of alcohol and drugs was recorded in 3 instances.

Crashes by County

Crash distribution was heavily concentrated in Iowa's most populous counties. Polk County, home to Des Moines, recorded the highest volume with 796 crashes. It was followed by Scott County (329 crashes), Linn County (269 crashes), Black Hawk County (165 crashes), and Pottawattamie County (163 crashes). Together, these five counties accounted for nearly 40% of all crashes statewide.

Crashes by County

1
POLK796 (20.9%)
2
SCOTT329 (8.6%)
3
LINN269 (7.1%)
4
BLACK HAWK165 (4.3%)
5
POTTAWATTAMIE163 (4.3%)
6
JOHNSON162 (4.2%)
7
WOODBURY162 (4.2%)
8
DUBUQUE158 (4.1%)
9
STORY114 (3%)

Showing top 9 of 50 reported. 41 additional (1,495 total) not shown: CERRO GORDO, DALLAS, DES MOINES, MARSHALL, WARREN, LEE, CLINTON, JASPER, WEBSTER, WAPELLO, MARION, SIOUX, IOWA, BREMER, MUSCATINE, CEDAR, BOONE, BUCHANAN, HAMILTON, JEFFERSON, CLAYTON, HARRISON, FAYETTE, HARDIN, ADAIR, PLYMOUTH, HENRY, POWESHIEK, WASHINGTON, WINNESHIEK, BUENA VISTA, CLAY, DICKINSON, TAMA, ALLAMAKEE, FRANKLIN, DELAWARE, CARROLL, MILLS, BENTON, CLARKE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Crashes by City

The highest crash volumes were reported in Iowa's largest cities. Des Moines led with 444 crashes, followed by Davenport with 250, Cedar Rapids with 162, and Sioux City with 142. Dubuque rounded out the top five with 118 reported crashes during this period.

Crashes by City

1
DES MOINES444 (18.1%)
2
DAVENPORT250 (10.2%)
3
CEDAR RAPIDS162 (6.6%)
4
SIOUX CITY142 (5.8%)
5
DUBUQUE118 (4.8%)
6
COUNCIL BLUFFS117 (4.8%)
7
WATERLOO91 (3.7%)
8
WEST DES MOINES87 (3.6%)
9
ANKENY82 (3.3%)

Showing top 9 of 50 reported. 41 additional (955 total) not shown: IOWA CITY, AMES, BURLINGTON, URBANDALE, CEDAR FALLS, MASON CITY, MARSHALLTOWN, BETTENDORF, MARION, CLIVE, FORT DODGE, CORALVILLE, CLINTON, OTTUMWA, PLEASANT HILL, MUSCATINE, INDIANOLA, ALTOONA, KEOKUK, NEWTON, FORT MADISON, INDEPENDENCE, WINDSOR HEIGHTS, HIAWATHA, STORM LAKE, WAUKEE, MANCHESTER, CRESTON, CLEAR LAKE, PELLA, WEBSTER CITY, OSKALOOSA, SIOUX CENTER, BOONE, OSCEOLA, WAVERLY, SPIRIT LAKE, CARROLL, GRIMES, SPENCER, LE MARS.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 4,113, occurred on paved roadways. However, Iowa's extensive secondary road network was also a factor, with 195 crashes, or about 4.5% of the total with known surface type, taking place on unpaved gravel or dirt roads.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Roadway Contributing Factor

In a minority of crashes where a roadway factor was cited as a contributor, adverse surface conditions such as wet or icy pavement were the most common, noted in 113 incidents. Work zones were a factor in 61 crashes. Other less frequent factors included debris in the roadway (16 crashes) and traffic backups (16 crashes).

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)113 (42.2%)
2
Work Zone (roadway-related)61 (22.8%)
3
Debris16 (6%)
4
Traffic backup, regular congestion16 (6%)
5
Ruts/holes/bumps14 (5.2%)
6
Slippery, loose or worn surface14 (5.2%)
7
Shoulders (none, low, soft, high)10 (3.7%)
8
Traffic backup, prior crash7 (2.6%)
9
Obstruction in roadway6 (2.2%)

Showing top 9 of 13 reported. 4 additional (11 total) not shown: Non-highway work, Traffic backup, prior non-recurring incident, Disabled vehicle, Traffic control obscured.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Driver Condition

Among drivers where a condition other than 'apparently normal' was recorded, being under the influence of alcohol was the most frequent, noted in 157 cases. Driver fatigue or falling asleep was the next most common condition, cited for 74 drivers. Other documented conditions included being emotional (34 drivers) and suffering from a medical event (32 drivers).

Driver Condition

1
Under the influence of alcohol157 (47%)
2
Asleep/fatigued74 (22.2%)
3
Emotional (e.g. depressed, angry)34 (10.2%)
4
Medical condition (seizure, reaction)32 (9.6%)
5
Illness/fainted13 (3.9%)
6
Under the influence of drugs/meds10 (3%)
7
Physical impairment5 (1.5%)
8
Walks with a cane/crutches3 (0.9%)
9
Paraplegic/wheelchair restricted3 (0.9%)

Showing top 9 of 11 reported. 2 additional (3 total) not shown: Visually impaired, Impaired due to previous injury.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Crashes by Iowa DOT District

Crash distribution across the state's six DOT districts shows a concentration in the regions with major population centers. District 1, which includes the Des Moines metro area, had the highest number of crashes with 1,241. District 6, covering eastern Iowa including Cedar Rapids and Davenport, was second with 1,143 crashes. Together, these two districts accounted for 55% of all crashes in the state.

Crashes by Iowa DOT District

1
District 11,241 (28.6%)
2
District 61,143 (26.4%)
3
District 2533 (12.3%)
4
District 5523 (12.1%)
5
District 4449 (10.4%)
6
District 3447 (10.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Property Damage

The most common estimated property damage cost per crash was in the range of $1,500 to $7,500, which applied to 3,165 incidents, or 73% of all crashes. High-cost crashes were less frequent, with 84 incidents (1.9%) resulting in estimated damages of $25,000 or more.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events such as running off the road or rollovers were the most frequent crash type, accounting for 1,204 incidents (27.8%). The most common multi-vehicle crash type was a rear-end collision, which occurred 1,034 times (23.8%). Broadside, or front-to-side, collisions were the third most common manner, with 658 incidents (15.2%).

Manner of Collision

"Other" combines 3 smaller categories (154 records): Sideswipe, opposite direction (68), Head-on (front to front) (65), Rear to rear (21).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was moving essentially straight, which was the case for 3,919 vehicles. The next most frequent actions were turning left (693 vehicles) and slowing or stopping in traffic (439 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight3,919 (58%)
2
Turning left693 (10.3%)
3
Slowing/stopping (deceleration)439 (6.5%)
4
Stopped in traffic358 (5.3%)
5
Legally Parked352 (5.2%)
6
Turning right239 (3.5%)
7
Backing191 (2.8%)
8
Other (explain in narrative)139 (2.1%)
9
Changing lanes138 (2%)

Showing top 9 of 19 reported. 10 additional (288 total) not shown: Negotiating a curve, Overtaking/passing, Entering traffic lane (merging), Making U-turn, Illegally Parked/Unattended, Accelerating in road, Leaving traffic lane, Starting in road, Leaving a parked position, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Vehicle unit records

Pedestrian/Cyclist Action

For non-motorists involved in crashes, the most frequently recorded action was entering or crossing the roadway, which was documented in 50 incidents. Other actions included moving along the roadway with traffic (11 incidents) and being on a sidewalk (6 incidents).

Pedestrian/Cyclist Action

1
Entering or crossing roadway50 (56.2%)
2
Movement: Along roadway with traffic11 (12.4%)
3
Other10 (11.2%)
4
Movement: On sidewalk6 (6.7%)
5
Movement: Along roadway against traffic3 (3.4%)
6
Approaching or leaving vehicle3 (3.4%)
7
Working in trafficway1 (1.1%)
8
Disabled vehicle-related/pushing vehicle1 (1.1%)
9
Entering/exiting vehicle1 (1.1%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Movement: On shoulder/median, Playing on or working on vehicle, Waiting to cross roadway.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Non-motorist records linked to crash events

Person Type

Of the 9,030 individuals involved in crashes, the vast majority, 8,589 people (95.1%), were drivers. Passengers accounted for 352 individuals (3.9%). Vulnerable road users represented a small fraction of the total persons involved, with 51 bicyclists and 34 pedestrians recorded.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Person Injury Severity

Among all persons involved in crashes, a total of 1,573 individuals sustained some level of injury or were fatally wounded. This included 25 fatalities, 128 serious injuries, 555 minor injuries, and 865 possible injuries. These figures represent the human toll across all crash severities.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Crash-level records

Occupant Safety Equipment

Among the subset of occupants for whom safety equipment use was recorded, 994 were reported as using a shoulder and lap belt. In 133 cases, it was noted that no safety equipment was used. For motorcycle and bicycle riders, 32 were recorded as wearing a DOT-compliant helmet.

Occupant Safety Equipment

"Other" combines 4 smaller categories (12 records): Helmet (other) (5), Other (4), Booster seat (2), Child safety seat (type unknown) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 2,443 crashes. Single-vehicle crashes were the second most frequent type, with 1,625 incidents, representing 37.5% of the total. Crashes involving three or more vehicles were less common, with 265 such events recorded.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-06-01 to 2015-06-30 · 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: 2015-06-01 through 2015-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-06-01 through 2015-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,336
  • Total persons involved: 9,030
  • Total vehicles involved: 7,347

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: June 2015." Published September 9, 2026. Reporting period: 2015-06-01 to 2015-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-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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