Monthly Traffic Safety Analysis

4,425 CRASHES IN
IOWA, IA
FEBRUARY 2015

In February 2015, Iowa recorded 4,425 traffic crashes, resulting in 18 fatalities and 1,245 injuries. These incidents included 16 fatal crashes and 122 crashes involving a driver under the influence of alcohol or drugs. The most frequently cited contributing factor to these crashes was 'Driving too fast for conditions,' which was identified in 572 incidents, accounting for 12.9% of all crashes.

4,425

Total Crash Events

18

Persons Killed

1,245

Persons Injured

16

Fatal Crash Events

Note: "Persons Killed" (18) counts individual fatalities across all crash events. "Fatal" in the severity table below (16) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Of the 1,263 people killed or injured in crashes, the vast majority were motorists. A total of 17 motorists were killed and 1,208 were injured. One pedestrian fatality and 32 pedestrian injuries were recorded. No bicyclists were killed, but five sustained injuries.

1

Pedestrians Killed

0

Cyclists Killed

17

Motorists Killed

32

Pedestrians Injured

5

Cyclists Injured

1,208

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency peaked midweek, with Wednesday recording the highest number of incidents at 913. The afternoon commute represented the most dangerous time of day, with the hour from 4:00 p.m. to 4:59 p.m. seeing a peak of 379 crashes. A majority of collisions, 2,935 in total, occurred during daylight hours.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 76.2% (3,374 incidents), resulted in no injuries. Injury-involved crashes accounted for 23.8% of the total, including 58 serious injury crashes, 282 minor injury crashes, and 695 possible injury crashes. A total of 16 crashes were fatal, which resulted in the deaths of 18 individuals.

Severity is per crash event (most severe injury). 16 fatal crash events resulted in 18 persons killed.

Outcome by Severity (Crash Events)

Fatal16fatal crashes0.4%
Serious Injury58serious injury crashes1.3%
Minor Injury282minor injury crashes6.4%
Possible Injury695possible injury crashes15.7%
No Injury3,374no injury crashes76.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor identified in crashes was 'Driving too fast for conditions,' cited in 572 incidents (12.9%). This was followed by 'Followed too close' with 353 crashes (8.0%) and 'Ran off road - left' with 351 crashes (7.9%). Collisions involving an animal were also notable, contributing to 276 crashes.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions572 (12.9%)
Followed too close353 (8%)
Ran off road - left351 (7.9%)
Animal276 (6.2%)
Lost Control269 (6.1%)
FTYROW: From stop sign259 (5.9%)
Other (explain in narrative): Other213 (4.8%)
FTYROW: Making left turn208 (4.7%)
Ran off road - straight196 (4.4%)
Ran Traffic Signal192 (4.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While adverse conditions were a factor in many incidents, a significant portion of crashes occurred in favorable weather. Clear weather was reported in 2,431 crashes (54.9%), and daylight conditions were present for 2,935 crashes (66.3%). However, road surface conditions played a major role, with 1,149 crashes on snow and 549 on ice, compared to 1,887 on dry roads.

Weather

Clear2,431 (58.2%)
Cloudy925 (22.1%)
Snow702 (16.8%)
Blowing Snow70 (1.7%)
Freezing rain/drizzle19 (0.5%)
Fog, smoke, smog12 (0.3%)
Severe Winds10 (0.2%)
Rain5 (0.1%)
Sleet, hail3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Weather condition at time of crash

Lighting

Daylight2,935 (70.1%)
Dark - roadway lighted620 (14.8%)
Dark - roadway not lighted421 (10.1%)
Dusk113 (2.7%)
Dawn72 (1.7%)
Dark - unknown roadway lighting27 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Lighting condition field

Road Surface

Dry1,887 (45.0%)
Snow1,149 (27.4%)
Ice/frost549 (13.1%)
Wet386 (9.2%)
Slush160 (3.8%)
Gravel39 (0.9%)
Other (explain in narrative)11 (0.3%)
Mud, dirt5 (0.1%)
Sand4 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Road surface condition field

Vehicles & Demographics

Analysis of the 9,248 people involved in crashes shows the highest representation among individuals aged 26-34 (1,541 people), followed by the 35-44 age group (1,395 people). Among the 7,875 vehicles involved, the most frequent makes were Chevrolet (1,502 vehicles), Ford (1,296 vehicles), and Dodge (647 vehicles).

Top Vehicle Makes (7,875 vehicles)

1
FORD1,296 (16.5%)
2
CHEV941 (11.9%)
3
CHEVROLET561 (7.1%)
4
DODG390 (5%)
5
TOYT380 (4.8%)
6
DODGE257 (3.3%)
7
JEEP235 (3%)
8
HOND230 (2.9%)
9
PONT223 (2.8%)
10
GMC204 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Vehicle unit records

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

Sex Distribution (6,828 persons with recorded sex)

Male3,929 (57.5%)
Female2,899 (42.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Person-level records linked to crash events

Major Cause

The most common major cause assigned to crashes was 'Driving too fast for conditions,' accounting for 572 incidents. 'Followed too close' was the second leading cause with 353 crashes, followed closely by 'Ran off road - left' with 351 crashes. Collisions with animals were the fourth-most-common cause, noted in 276 crashes.

Major Cause

1
Driving too fast for conditions572 (14.1%)
2
Followed too close353 (8.7%)
3
Ran off road - left351 (8.7%)
4
Animal276 (6.8%)
5
Lost Control269 (6.7%)
6
FTYROW: From stop sign259 (6.4%)
7
Other (explain in narrative): Other213 (5.3%)
8
FTYROW: Making left turn208 (5.1%)
9
Ran off road - straight196 (4.8%)

Showing top 9 of 49 reported. 40 additional (1,348 total) not shown: Ran Traffic Signal, Ran Stop Sign, FTYROW: From driveway, Operating vehicle in an reckless, erratic, careless, negligent manner, Made improper turn, FTYROW: At uncontrolled intersection, Swerving/Evasive Action, Improper or erratic lane changing, Driver Distraction: Other interior distraction, Driver Distraction: Exterior distraction, FTYROW: Other (explain in narrative), Driver Distraction: Inattentive/lost in thought, FTYROW: From yield sign, Other (explain in narrative): No improper action, FTYROW: From parked position, Failed to keep in proper lane, Improper Backing, Ran off road - right, Passing: Other passing (explain in narrative), Exceeded authorized speed, Traveling wrong way or on wrong side of road, Other (explain in narrative): Vision obstructed, Driver Distraction: Passenger, Driver Distraction: Reaching for object(s)/fallen object(s), Crossed centerline (undivided), Driver Distraction: Adjusting devices (radio, climate), FTYROW: To pedestrian, Driver Distraction: Talking on a hand-held device, Aggressive driving/road rage, Driver Distraction: Other electronic device activity, Driver Distraction: Manual operation of an electronic communication device, Illegally Parked/Unattended, Failed to yield to emergency vehicle, Equipment failure, FTYROW: Making right turn on red signal, Cargo/equipment loss or shift, Other (explain in narrative): Disregarded signs/road markings, Passing: With insufficient distance/inadequate visibility, Operator inexperience, Passing: Through/around barrier.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

First Harmful Event

The most frequent first harmful event was a 'Collision with: Vehicle in traffic,' which occurred in 2,847 crashes, representing 64.3% of all incidents. Single-vehicle events were also common, with the leading types being collisions with an animal (275 crashes), running into a ditch (175 crashes), and vehicle overturns or rollovers (148 crashes).

First Harmful Event

1
Collision with: Vehicle in traffic2,847 (64.8%)
2
Collision with: Animal275 (6.3%)
3
Collision with: Parked motor vehicle191 (4.3%)
4
Collision with fixed object: Ditch175 (4%)
5
Non-collision events: Overturn/rollover148 (3.4%)
6
Collision with fixed object: Cable barrier86 (2%)
7
Collision with fixed object: Utility pole/light support74 (1.7%)
8
Collision with fixed object: Concrete traffic barrier (median or right side)45 (1%)
9
Collision with: Re-entering roadway43 (1%)

Showing top 9 of 48 reported. 39 additional (509 total) not shown: Collision with fixed object: Tree, Collision with fixed object: Curb/island/raised median, Collision with: Non-motorist (see non-motorist section - NOT a unit), Miscellaneous events: Hit and run, Other (explain in narrative), Collision with fixed object: Traffic sign support, Collision with fixed object: Guardrail - face, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fence, Collision with fixed object: Other post/pole/support (explain in narrative), Non-collision events: Jackknife, Collision with fixed object: Snow bank, Collision with: Struck/struck by object/cargo/person from other vehicle, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Embankment, Collision with fixed object: Fire hydrant, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Mailbox, Non-collision events: Vehicle went airborne, Collision with fixed object: Guardrail - end, Collision with fixed object: Building, Collision with: Thrown or falling object, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Bridge overhead structure, Collision with: Railway vehicle/train, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Wall, Collision with fixed object: Traffic signal support, Miscellaneous events: Vehicle out of gear/rolled, Collision with fixed object: Other traffic barrier (explain in narrative), Miscellaneous events: Immersion, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Ground, Non-collision events: Fell/jumped from vehicle, Collision with: Work zone maintenance equipment, Collision with fixed object: Bridge pier or support, Collision with fixed object: Impact attenuator/crash cushion.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Roadway Junction / Feature

Crashes were more likely to occur away from intersections, with 2,075 incidents (46.9%) happening at non-junction locations. Four-way intersections were the most common type of junction for crashes, accounting for 1,236 incidents. T-intersections were the site of 324 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature2,075 (49.3%)
2
Intersection: Four-way intersection1,236 (29.4%)
3
Intersection: T-intersection324 (7.7%)
4
Non-intersection: Driveway access (related, not in)166 (3.9%)
5
Intersection: Other intersection (explain in narrative)67 (1.6%)
6
Non-intersection: Driveway access (within)59 (1.4%)
7
Non-intersection: Other non-intersection (explain in narrative)52 (1.2%)
8
Intersection: Intersection with ramp39 (0.9%)
9
Interchange-related: On-ramp merge area30 (0.7%)

Showing top 9 of 23 reported. 14 additional (158 total) not shown: Interchange-related: Off-ramp, Interchange-related: Off-ramp, diverge area, Non-intersection: Alley, Non-intersection: Railroad grade crossing, Non-intersection: Crossover-related, Intersection: Y-intersection, Intersection: L-intersection, Interchange-related: Mainline, between ramps, Interchange-related: On-ramp, Intersection: Roundabout, Non-intersection: Bike lanes, Interchange-related: Other interchange (explain in narrative), Intersection: Five points or more, Intersection: Traffic circle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 3,828 of the 7,875 vehicles. Sport utility vehicles were the second-most common with 1,616 involved, followed by four-tire light trucks and pickups at 1,222. Tractor/semi-trailers were involved in 246 crashes.

Vehicle Type

"Other" combines 21 smaller categories (195 records): Single-unit truck (>= 3 axles) (52), School bus (seats > 15) (28), Other bus (seats > 15) (19), Maintenance/construction vehicle (17), Other (explain in narrative) (14), Passenger van (seats 9-15) (11), Other light truck (<=10000 lbs) (8), Snowmobile (7), Truck/trailer (6), Truck tractor (bobtail) (6), All-terrain vehicle (ATV) (4), Farm equipment (explain in narrative) (4), Tractor/doubles (4), Train (4), Other small bus (seats 9-15) (3), Small school bus (seats 9-15) (2), Other heavy truck (> 10000 lbs) (cannot classify) (2), Limousine/taxi (seats 8 or less) (1), Limousine/taxi (seats 9-15) (1), Motorcycle (1), Farm tractor (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Vehicle unit records

Traffic Control Device

Data on vehicles involved in crashes shows that 4,656 were in areas with 'No controls present.' For crashes where traffic controls were a factor, traffic signals were present for 1,795 vehicles and stop signs were present for 880 vehicles. Yield signs were a factor for 50 vehicles.

Traffic Control Device

"Other" combines 7 smaller categories (63 records): Flashing traffic control signal (19), No Passing Zone (marked) (19), Work zone sign (9), Traffic director (person) (8), School zone signs (6), Inoperative (not functioning properly) (1), Traffic sign missing (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common area of impact, recorded as the most damaged area for 2,007 vehicles. The rear was the second-most common point of damage, recorded for 903 vehicles, suggesting a high number of rear-end collisions. Damage to the driver-side and passenger-side middle areas was noted on 492 and 416 vehicles, respectively, indicative of angle or sideswipe crashes.

Most Damaged Area

"Other" combines 10 smaller categories (1,650 records): Passenger side - front (330), Driver side - rear (282), Passenger side - rear (280), Rear - driver side corner (274), Rear - passenger side corner (183), Top (142), Other (explain in narrative) (79), Non-collision/no damage (42), Undercarriage (36), Cargo loss (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Vehicle unit records

Impairment (Alcohol / Drugs)

A total of 122 crashes, or 2.8% of all incidents, were recorded as involving an impaired driver. Among the 125 drivers identified as impaired, alcohol was the sole factor for 112 drivers. Drugs were a factor for 7 drivers, and a combination of alcohol and drugs was noted for 6 drivers.

Crashes by County

Crash distribution was concentrated in the state's most populous counties. Polk County alone accounted for 811 crashes, representing 18.3% of the statewide total. The top five counties—Polk, Scott (325 crashes), Linn (267), Johnson (256), and Black Hawk (251)—collectively made up 43.2% of all crashes in Iowa for the month.

Crashes by County

1
POLK811 (20.3%)
2
SCOTT325 (8.1%)
3
LINN267 (6.7%)
4
JOHNSON256 (6.4%)
5
BLACK HAWK251 (6.3%)
6
WOODBURY191 (4.8%)
7
DUBUQUE176 (4.4%)
8
POTTAWATTAMIE149 (3.7%)
9
STORY145 (3.6%)

Showing top 9 of 50 reported. 41 additional (1,432 total) not shown: DALLAS, CERRO GORDO, DES MOINES, WEBSTER, CLINTON, LEE, MARSHALL, MUSCATINE, JASPER, CEDAR, WARREN, MARION, WAPELLO, MAHASKA, IOWA, BOONE, SIOUX, BREMER, POWESHIEK, WINNESHIEK, CASS, FLOYD, HARDIN, PLYMOUTH, HAMILTON, WASHINGTON, HENRY, BUENA VISTA, PAGE, TAMA, HARRISON, DELAWARE, JONES, MADISON, CLAYTON, HUMBOLDT, BUCHANAN, BENTON, CLAY, APPANOOSE, GREENE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Crashes by City

The highest crash volumes were reported in Iowa's largest cities. Des Moines led with 439 crashes, followed by Davenport with 237, Cedar Rapids with 177, and Sioux City with 164. Waterloo and Dubuque also reported high volumes, with 144 and 146 crashes respectively.

Crashes by City

1
DES MOINES439 (15.5%)
2
DAVENPORT237 (8.4%)
3
CEDAR RAPIDS177 (6.3%)
4
SIOUX CITY164 (5.8%)
5
DUBUQUE146 (5.2%)
6
WATERLOO144 (5.1%)
7
IOWA CITY138 (4.9%)
8
COUNCIL BLUFFS109 (3.9%)
9
AMES108 (3.8%)

Showing top 9 of 50 reported. 41 additional (1,167 total) not shown: WEST DES MOINES, CEDAR FALLS, ANKENY, FORT DODGE, BURLINGTON, URBANDALE, CORALVILLE, MASON CITY, CLINTON, BETTENDORF, MARSHALLTOWN, CLIVE, MARION, OTTUMWA, ALTOONA, FORT MADISON, MUSCATINE, OSKALOOSA, CHARLES CITY, BOONE, KEOKUK, WAUKEE, DECORAH, WEBSTER CITY, LE MARS, NEWTON, WAVERLY, INDIANOLA, SPENCER, GRIMES, FAIRFIELD, CLARINDA, NORTH LIBERTY, HIAWATHA, WEST BURLINGTON, EVANSDALE, HUMBOLDT, KNOXVILLE, HAMPTON, OSCEOLA, STORM LAKE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Paved vs Unpaved Road

The overwhelming majority of crashes occurred on paved roadways, with 4,269 incidents reported. Crashes on unpaved surfaces like gravel or dirt roads were much less frequent, accounting for 134 incidents, or approximately 3.0% of crashes where the surface type was specified.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Roadway Contributing Factor

Roadway-related contributing factors were noted in a minority of crashes, but surface condition was the most significant when present. 'Surface condition (e.g. wet, icy)' was cited as a factor in 1,336 crashes, aligning with the winter month. 'Slippery, loose or worn surface' was a distant second with 54 crashes, while work zones were a factor in 9 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)1,336 (92.4%)
2
Slippery, loose or worn surface54 (3.7%)
3
Traffic backup, prior crash10 (0.7%)
4
Work Zone (roadway-related)9 (0.6%)
5
Debris8 (0.6%)
6
Shoulders (none, low, soft, high)5 (0.3%)
7
Ruts/holes/bumps5 (0.3%)
8
Traffic backup, regular congestion5 (0.3%)
9
Traffic backup, prior non-recurring incident4 (0.3%)

Showing top 9 of 13 reported. 4 additional (10 total) not shown: Disabled vehicle, Obstruction in roadway, Traffic control obscured, Non-highway work.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, impairment was the most common. A total of 135 drivers were noted as being 'Under the influence of alcohol.' The second-most cited condition was 'Asleep/fatigued,' which was recorded for 45 drivers, followed by emotional distress for 24 drivers.

Driver Condition

1
Under the influence of alcohol135 (54%)
2
Asleep/fatigued45 (18%)
3
Emotional (e.g. depressed, angry)24 (9.6%)
4
Medical condition (seizure, reaction)23 (9.2%)
5
Paraplegic/wheelchair restricted5 (2%)
6
Illness/fainted5 (2%)
7
Under the influence of drugs/meds5 (2%)
8
Physical impairment4 (1.6%)
9
Visually impaired2 (0.8%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Hearing impaired/deaf, Walks with a cane/crutches.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Crashes by Iowa DOT District

Crash distribution varied significantly across Iowa's six DOT districts. District 1, which includes the Des Moines metro area, had the highest number of crashes with 1,296. District 6, covering eastern Iowa including Cedar Rapids and Davenport, followed closely with 1,253 crashes. Together, these two districts accounted for over 57% of all crashes.

Crashes by Iowa DOT District

1
District 11,296 (29.3%)
2
District 61,253 (28.3%)
3
District 2565 (12.8%)
4
District 5504 (11.4%)
5
District 3405 (9.2%)
6
District 4402 (9.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Property Damage

The most common estimated cost of property damage fell into the '$1,500 - $7,500' category, which applied to 3,339 crashes. A smaller number of incidents resulted in severe damage, with 906 crashes estimated between $7,500 and $25,000, and 83 crashes exceeding $25,000 in property damage.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Manner of Collision

Crashes were almost evenly split between single-vehicle incidents and multi-vehicle collisions. Non-collision single-vehicle events, such as running off the road, accounted for 1,065 crashes (24.1%). Rear-end collisions were the most common type of crash between vehicles, with 1,062 incidents (24.0%), followed by broadside collisions with 967 incidents (21.9%).

Manner of Collision

"Other" combines 3 smaller categories (173 records): Other (explain in narrative) (80), Rear to side (79), Rear to rear (14).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Pre-Crash Driver Action

The vast majority of vehicles involved in collisions were engaged in 'Movement essentially straight' prior to the crash, a pre-crash action recorded for 4,580 vehicles. Turning left was the second-most common action, noted for 731 vehicles, while 470 vehicles were in the process of slowing or stopping.

Pre-Crash Driver Action

1
Movement essentially straight4,580 (61%)
2
Turning left731 (9.7%)
3
Slowing/stopping (deceleration)470 (6.3%)
4
Stopped in traffic390 (5.2%)
5
Legally Parked374 (5%)
6
Turning right273 (3.6%)
7
Other (explain in narrative)181 (2.4%)
8
Backing140 (1.9%)
9
Changing lanes108 (1.4%)

Showing top 9 of 19 reported. 10 additional (264 total) not shown: Overtaking/passing, Negotiating a curve, Entering traffic lane (merging), Accelerating in road, Illegally Parked/Unattended, Leaving traffic lane, Starting in road, Making U-turn, Leaving a parked position, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Vehicle unit records

Pedestrian/Cyclist Action

For the 33 pedestrians involved in crashes, the most common action was 'Entering or crossing roadway,' which was recorded for 20 individuals. Other actions included moving along the roadway with traffic (4 pedestrians) and working in the trafficway (2 pedestrians).

Pedestrian/Cyclist Action

1
Entering or crossing roadway20 (52.6%)
2
Movement: Along roadway with traffic4 (10.5%)
3
Movement: Along roadway (direction unknown)3 (7.9%)
4
Working in trafficway2 (5.3%)
5
Going to/coming from school2 (5.3%)
6
Movement: On sidewalk2 (5.3%)
7
Approaching or leaving vehicle2 (5.3%)
8
Other1 (2.6%)
9
Disabled vehicle-related/pushing vehicle1 (2.6%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Playing on or working on vehicle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Non-motorist records linked to crash events

Person Type

Of the 9,248 individuals involved in crashes during this period, the great majority were drivers (8,907 people). Passengers accounted for 303 of the individuals involved. A smaller number of vulnerable road users were documented, including 33 pedestrians and 5 bicyclists.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Person Injury Severity

Among all 9,248 people involved in crashes, 18 sustained fatal injuries and 73 received serious injuries. An additional 356 people had minor injuries and 816 had possible injuries. The data shows that 1,245 individuals sustained some level of injury.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Crash-level records

Occupant Safety Equipment

Among the subset of 1,002 vehicle occupants for whom safety equipment use was recorded, 891 (88.9%) were using a shoulder and lap belt. A total of 74 individuals (7.4%) were documented as using no safety equipment at all. Child safety seats were in use by 15 occupants.

Occupant Safety Equipment

"Other" combines 4 smaller categories (7 records): Booster seat (2), Helmet (DOT compliant) (2), Child safety seat (rear-facing) (2), Child safety seat (type unknown) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common type of crash, accounting for 2,990 incidents (67.6%). Single-vehicle crashes were the next most frequent, with 1,223 incidents (27.6%). Crashes involving three or more vehicles were less common, with 212 such events recorded.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-02-01 to 2015-02-28 · 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: 2015-02-01 through 2015-02-28
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-02-01 through 2015-02-28 (28 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,425
  • Total persons involved: 9,248
  • Total vehicles involved: 7,875

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: February 2015." Published September 9, 2026. Reporting period: 2015-02-01 to 2015-02-28. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/february-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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