Monthly Traffic Safety Analysis

3,680 CRASHES IN
IOWA, IA
APRIL 2015

In April 2015, Iowa recorded 3,680 traffic crashes, resulting in 31 fatalities and 1,389 injuries. Analysis of contributing factors reveals that following too closely was the leading cause, cited in 455 incidents, representing 12.4% of crashes with a determined factor. The majority of collisions were rear-end impacts, accounting for 27.3% of all crash types.

3,680

Total Crash Events

31

Persons Killed

1,389

Persons Injured

25

Fatal Crash Events

Note: "Persons Killed" (31) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Motorists comprised the vast majority of individuals killed or injured, with 30 fatalities and 1,325 injuries. Vulnerable road users also suffered casualties; one pedestrian was killed and 35 were injured. No cyclists were killed, but 28 sustained injuries during this period.

1

Pedestrians Killed

0

Cyclists Killed

30

Motorists Killed

0

Other Killed

35

Pedestrians Injured

28

Cyclists Injured

1,325

Motorists Injured

1

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash analysis reveals distinct temporal patterns, with Thursdays being the most frequent day for incidents, recording 653 crashes. The daily peak for collisions occurred during the afternoon commute, specifically in the 4 p.m. hour with 326 crashes. A secondary, smaller peak is visible during the morning commute between 7 a.m. and 8 a.m., which together saw 359 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 3,680 crashes, 68.8% resulted in no injuries, categorized as property-damage-only incidents. The remaining crashes involved various levels of injury: 18.5% with possible injuries, 9.6% with minor injuries, and 2.3% with serious injuries. A total of 25 crashes were classified as fatal, which collectively resulted in 31 individual fatalities.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 31 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.7%
Serious Injury86serious injury crashes2.3%
Minor Injury355minor injury crashes9.6%
Possible Injury682possible injury crashes18.5%
No Injury2,532no injury crashes68.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor identified in crashes was 'Followed too close,' accounting for 455 incidents (12.4%). Collisions with animals were the second most common factor, cited in 352 crashes (9.6%). Other significant factors included drivers losing control (215 crashes) and failing to yield the right-of-way from a stop sign (214 crashes).

Officer-Reported Primary Contributing Cause

Followed too close455 (12.4%)
Animal352 (9.6%)
Lost Control215 (5.8%)
FTYROW: From stop sign214 (5.8%)
Other (explain in narrative): Other212 (5.8%)
Ran off road - left191 (5.2%)
FTYROW: Making left turn172 (4.7%)
Ran Traffic Signal138 (3.8%)
Ran off road - straight126 (3.4%)
Ran Stop Sign106 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred in what would be considered ideal driving conditions. Data shows that 71.6% of crashes happened in daylight (2,634 incidents), 76.9% on dry road surfaces (2,829 incidents), and 62.6% in clear weather (2,303 incidents). Crashes in adverse conditions were less frequent, with rain being a factor in 293 incidents and wet roads in 443.

Weather

Clear2,303 (68.2%)
Cloudy698 (20.7%)
Rain293 (8.7%)
Fog, smoke, smog23 (0.7%)
Freezing rain/drizzle20 (0.6%)
Severe Winds19 (0.6%)
Snow12 (0.4%)
Sleet, hail5 (0.1%)
Blowing sand, soil, dirt2 (0.1%)
Blowing Snow2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Weather condition at time of crash

Lighting

Daylight2,634 (77.4%)
Dark - roadway lighted363 (10.7%)
Dark - roadway not lighted279 (8.2%)
Dusk62 (1.8%)
Dawn51 (1.5%)
Dark - unknown roadway lighting13 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Lighting condition field

Road Surface

Dry2,829 (83.5%)
Wet443 (13.1%)
Gravel83 (2.4%)
Ice/frost10 (0.3%)
Slush9 (0.3%)
Mud, dirt8 (0.2%)
Snow3 (0.1%)
Other (explain in narrative)2 (0.1%)
Water (standing or moving)1 (0.0%)
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was the most represented, with 1,225 individuals. Among vehicle makes involved, Chevrolet was the most frequent (1,282 vehicles), followed by Ford (1,003 vehicles) and Dodge (492 vehicles). These figures represent the frequency of involvement in crashes and do not reflect market share.

Top Vehicle Makes (6,500 vehicles)

1
FORD1,003 (15.4%)
2
CHEV773 (11.9%)
3
CHEVROLET509 (7.8%)
4
TOYT298 (4.6%)
5
DODG283 (4.4%)
6
DODGE209 (3.2%)
7
HOND195 (3%)
8
PONT176 (2.7%)
9
GMC174 (2.7%)
10
JEEP174 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Vehicle unit records

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

Sex Distribution (5,675 persons with recorded sex)

Male3,100 (54.6%)
Female2,575 (45.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Person-level records linked to crash events

Major Cause

The primary cause assigned to crashes was 'Followed too close,' which was responsible for 455 incidents. The second most frequent major cause was collisions with an 'Animal,' recorded in 352 crashes. 'Lost Control' (215 crashes) and 'FTYROW: From stop sign' (214 crashes) were also leading causes identified in the data.

Major Cause

1
Followed too close455 (13.5%)
2
Animal352 (10.4%)
3
Lost Control215 (6.4%)
4
FTYROW: From stop sign214 (6.3%)
5
Other (explain in narrative): Other212 (6.3%)
6
Ran off road - left191 (5.7%)
7
FTYROW: Making left turn172 (5.1%)
8
Ran Traffic Signal138 (4.1%)
9
Ran off road - straight126 (3.7%)

Showing top 9 of 49 reported. 40 additional (1,299 total) not shown: Ran Stop Sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Other interior distraction, Made improper turn, FTYROW: From driveway, Driving too fast for conditions, Improper or erratic lane changing, Driver Distraction: Inattentive/lost in thought, Exceeded authorized speed, Driver Distraction: Exterior distraction, FTYROW: Other (explain in narrative), Improper Backing, Other (explain in narrative): No improper action, Swerving/Evasive Action, Driver Distraction: Reaching for object(s)/fallen object(s), FTYROW: At uncontrolled intersection, Failed to keep in proper lane, Passing: Other passing (explain in narrative), FTYROW: From yield sign, FTYROW: From parked position, Driver Distraction: Passenger, Ran off road - right, Driver Distraction: Manual operation of an electronic communication device, Crossed centerline (undivided), Driver Distraction: Other electronic device activity, Driver Distraction: Adjusting devices (radio, climate), FTYROW: Making right turn on red signal, Aggressive driving/road rage, Passing: With insufficient distance/inadequate visibility, Failed to yield to emergency vehicle, Traveling wrong way or on wrong side of road, Passing: Through/around barrier, FTYROW: To pedestrian, Other (explain in narrative): Vision obstructed, Cargo/equipment loss or shift, Driver Distraction: Unrestrained animal, Over correcting/over steering, Disregarded RR Signal, Passing: Where prohibited by signs/markings, Equipment failure.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

First Harmful Event

The most common initial event in a crash sequence was a 'Collision with: Vehicle in traffic,' which occurred in 2,270 incidents. The second most frequent first harmful event was a 'Collision with: Animal,' accounting for 347 crashes. Single-vehicle run-off-road events were also notable, including 154 overturns and 146 collisions with a ditch.

First Harmful Event

1
Collision with: Vehicle in traffic2,270 (62.3%)
2
Collision with: Animal347 (9.5%)
3
Collision with: Parked motor vehicle173 (4.7%)
4
Non-collision events: Overturn/rollover154 (4.2%)
5
Collision with fixed object: Ditch146 (4%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)61 (1.7%)
7
Collision with fixed object: Utility pole/light support56 (1.5%)
8
Other (explain in narrative)41 (1.1%)
9
Collision with fixed object: Curb/island/raised median35 (1%)

Showing top 9 of 48 reported. 39 additional (363 total) not shown: Non-collision events: Other non-collision (explain in narrative), Collision with: Re-entering roadway, Collision with fixed object: Cable barrier, Collision with fixed object: Embankment, Collision with fixed object: Traffic sign support, Collision with fixed object: Tree, Miscellaneous events: Hit and run, Collision with fixed object: Guardrail - face, Collision with fixed object: Bridge/bridge rail parapet, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Building, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Guardrail - end, Collision with fixed object: Fence, Non-collision events: Fell/jumped from vehicle, Non-collision events: Jackknife, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Ground, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Traffic signal support, Collision with: Work zone maintenance equipment, Collision with: Railway vehicle/train, Collision with fixed object: Wall, Miscellaneous events: Immersion, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Fire hydrant, Miscellaneous events: Vehicle out of gear/rolled, Collision with: Thrown or falling object, Collision with fixed object: Impact attenuator/crash cushion, Collision with fixed object: Mailbox, Collision with fixed object: Bridge pier or support, Miscellaneous events: Fire/explosion, Non-collision events: Vehicle went airborne, Miscellaneous events: Eluding law enforcement.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Roadway Junction / Feature

Crashes were more likely to occur on non-intersection roadway segments, which accounted for 1,683 incidents. Four-way intersections were the most common type of junction for crashes, with 976 incidents occurring at these locations. T-intersections were the site of another 251 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature1,683 (49.5%)
2
Intersection: Four-way intersection976 (28.7%)
3
Intersection: T-intersection251 (7.4%)
4
Non-intersection: Driveway access (related, not in)126 (3.7%)
5
Non-intersection: Driveway access (within)57 (1.7%)
6
Intersection: Other intersection (explain in narrative)57 (1.7%)
7
Intersection: Intersection with ramp41 (1.2%)
8
Non-intersection: Other non-intersection (explain in narrative)35 (1%)
9
Non-intersection: Alley28 (0.8%)

Showing top 9 of 24 reported. 15 additional (146 total) not shown: Interchange-related: On-ramp merge area, Interchange-related: Off-ramp, diverge area, Non-intersection: Railroad grade crossing, Intersection: Y-intersection, Interchange-related: Off-ramp, Non-intersection: Crossover-related, Interchange-related: Mainline, between ramps, Intersection: Five points or more, Interchange-related: On-ramp, Interchange-related: Other interchange (explain in narrative), Intersection: Traffic circle, Intersection: Roundabout, Intersection: L-intersection, Non-intersection: Bike lanes, Intersection: Shared use path or trail.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 3,350 vehicles. Sport utility vehicles (1,255 vehicles) and four-tire light trucks or pickups (939 vehicles) were the next most frequent. Commercial vehicles were also represented, with 156 tractor/semi-trailers involved in collisions, while 81 motorcycles were also involved.

Vehicle Type

"Other" combines 20 smaller categories (179 records): Cargo/panel van (42), Single-unit truck (>= 3 axles) (37), Other bus (seats > 15) (14), Moped (12), Farm tractor (12), Truck/trailer (11), Passenger van (seats 9-15) (10), School bus (seats > 15) (9), Maintenance/construction vehicle (7), Truck tractor (bobtail) (4), Train (4), Farm equipment (explain in narrative) (4), Other light truck (<=10000 lbs) (4), Other small bus (seats 9-15) (2), All-terrain vehicle (ATV) (2), Tractor/doubles (1), 3-wheeled, unenclosed (1), Other heavy truck (> 10000 lbs) (cannot classify) (1), Other (explain in narrative) (1), Golf cart (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Vehicle unit records

Traffic Control Device

A significant portion of crashes occurred where no traffic control devices were present, with 3,696 vehicles involved in such situations. For crashes at controlled locations, traffic signals were the most common device, present in 1,507 instances. Stop signs were the next most frequent control, involved in 691 instances.

Traffic Control Device

"Other" combines 5 smaller categories (74 records): Flashing traffic control signal (23), Railway crossing device (20), Warning sign (17), Traffic director (person) (10), School zone signs (4).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common area of initial impact, recorded for 1,680 vehicles. The rear of the vehicle was the second most frequent point of damage, noted in 913 cases, which is consistent with the high number of rear-end collisions. Corner and side impacts were also prevalent, with 522 vehicles sustaining damage to the front-driver-side corner.

Most Damaged Area

"Other" combines 10 smaller categories (1,383 records): Passenger side - middle (267), Passenger side - rear (225), Driver side - rear (216), Rear - driver side corner (196), Rear - passenger side corner (177), Top (144), Other (explain in narrative) (89), Non-collision/no damage (34), Undercarriage (29), Cargo loss (6).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Vehicle unit records

Impairment (Alcohol / Drugs)

Impairment was suspected or confirmed in 159 crashes. Of these, alcohol was a factor in 144 incidents, drugs were a factor in 8, and a combination of alcohol and drugs was noted in 7. These 159 crashes represent 4.3% of all crashes during this period.

Crashes by County

Crash distribution was concentrated in the state's most populous counties. Polk County recorded the highest number of incidents with 716 crashes. Scott County followed with 294 crashes, and Linn County had 221. Together, these three counties accounted for 33.2% of all crashes statewide.

Crashes by County

1
POLK716 (21.7%)
2
SCOTT294 (8.9%)
3
LINN221 (6.7%)
4
WOODBURY173 (5.2%)
5
POTTAWATTAMIE169 (5.1%)
6
JOHNSON156 (4.7%)
7
BLACK HAWK147 (4.5%)
8
DUBUQUE122 (3.7%)
9
STORY109 (3.3%)

Showing top 9 of 50 reported. 41 additional (1,194 total) not shown: DES MOINES, CLINTON, CERRO GORDO, DALLAS, LEE, WAPELLO, MARSHALL, WARREN, WEBSTER, SIOUX, MUSCATINE, BOONE, MARION, BUENA VISTA, CRAWFORD, BUCHANAN, BREMER, FAYETTE, PLYMOUTH, POWESHIEK, HARDIN, HAMILTON, APPANOOSE, CARROLL, HENRY, JASPER, IOWA, MAHASKA, BENTON, HARRISON, KOSSUTH, JONES, FLOYD, CEDAR, JEFFERSON, CLAYTON, CLAY, EMMET, DELAWARE, TAMA, GREENE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Crashes by City

Among municipalities, Des Moines had the highest crash volume with 406 incidents. Davenport recorded the second-highest number with 231 crashes, followed by Cedar Rapids with 156. These figures highlight the concentration of traffic incidents within Iowa's primary urban areas.

Crashes by City

1
DES MOINES406 (17.3%)
2
DAVENPORT231 (9.8%)
3
CEDAR RAPIDS156 (6.6%)
4
SIOUX CITY144 (6.1%)
5
COUNCIL BLUFFS128 (5.5%)
6
DUBUQUE95 (4%)
7
WATERLOO94 (4%)
8
IOWA CITY93 (4%)
9
WEST DES MOINES82 (3.5%)

Showing top 9 of 50 reported. 41 additional (917 total) not shown: AMES, ANKENY, URBANDALE, BURLINGTON, MASON CITY, CLINTON, BETTENDORF, CEDAR FALLS, CORALVILLE, MARION, FORT DODGE, OTTUMWA, MARSHALLTOWN, CLIVE, BOONE, DENISON, PLEASANT HILL, INDIANOLA, STORM LAKE, FORT MADISON, WAUKEE, WEBSTER CITY, KEOKUK, CARROLL, ESTHERVILLE, CENTERVILLE, ALGONA, OSKALOOSA, WAVERLY, JOHNSTON, MUSCATINE, CHARLES CITY, WINDSOR HEIGHTS, NEWTON, GRIMES, HIAWATHA, INDEPENDENCE, ORANGE CITY, KNOXVILLE, FAIRFIELD, DE WITT.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 3,498, occurred on paved road surfaces. A smaller but notable number of incidents, 167, took place on unpaved roads such as gravel or dirt. This represents 4.5% of crashes where the road surface type was specified.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Roadway Contributing Factor

In a minority of crashes, roadway factors were noted as contributors. The most cited factor was 'Surface condition (e.g. wet, icy),' which was a factor in 92 crashes. 'Work Zone' conditions were noted as a contributing factor in 61 incidents.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)92 (43.6%)
2
Work Zone (roadway-related)61 (28.9%)
3
Slippery, loose or worn surface15 (7.1%)
4
Traffic backup, regular congestion11 (5.2%)
5
Debris8 (3.8%)
6
Traffic backup, prior crash7 (3.3%)
7
Ruts/holes/bumps7 (3.3%)
8
Shoulders (none, low, soft, high)6 (2.8%)
9
Traffic backup, prior non-recurring incident2 (0.9%)

Showing top 9 of 10 reported. 1 additional (2 total) not shown: Obstruction in roadway.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Driver Condition

While most drivers were recorded as 'Apparently normal,' other conditions were noted in some cases. Among these, 185 drivers were reported as being under the influence of alcohol. Driver fatigue was also a factor, with 56 drivers reported as 'Asleep/fatigued,' and 42 were noted as being 'Emotional.'

Driver Condition

1
Under the influence of alcohol185 (55.2%)
2
Asleep/fatigued56 (16.7%)
3
Emotional (e.g. depressed, angry)42 (12.5%)
4
Medical condition (seizure, reaction)26 (7.8%)
5
Illness/fainted6 (1.8%)
6
Under the influence of drugs/meds6 (1.8%)
7
Physical impairment6 (1.8%)
8
Walks with a cane/crutches4 (1.2%)
9
Paraplegic/wheelchair restricted2 (0.6%)

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

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Crashes by Iowa DOT District

The distribution of crashes across Iowa's DOT districts shows a concentration in the state's most traveled regions. District 1, which includes the Des Moines metro area, had the highest number of crashes with 1,064. District 6, covering eastern Iowa, had the second-highest volume with 991 crashes.

Crashes by Iowa DOT District

1
District 11,064 (28.9%)
2
District 6991 (26.9%)
3
District 3434 (11.8%)
4
District 5423 (11.5%)
5
District 2416 (11.3%)
6
District 4352 (9.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Property Damage

The most frequent estimated property damage cost fell within the '$1,500 - $7,500' range, which applied to 2,616 crashes. A smaller number of incidents resulted in more severe damage, with 855 crashes in the '$7,500 - $25,000' range and 71 crashes causing damage estimated at '$25,000+.'

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Manner of Collision

Rear-end collisions were the most frequent type of crash, accounting for 1,003 incidents or 27.3% of the total. Single-vehicle crashes, classified as 'Non-collision,' were the second most common scenario, with 882 incidents (24.0%). Broadside collisions were the third most common type, with 636 crashes recorded.

Manner of Collision

"Other" combines 3 smaller categories (149 records): Sideswipe, opposite direction (71), Head-on (front to front) (62), Rear to rear (16).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Pre-Crash Driver Action

The predominant pre-crash action for vehicles involved was 'Movement essentially straight,' reported for 3,575 vehicles. The next most common actions were 'Turning left,' involving 589 vehicles, and 'Slowing/stopping (deceleration),' which was the action for 390 vehicles before impact.

Pre-Crash Driver Action

1
Movement essentially straight3,575 (58.3%)
2
Turning left589 (9.6%)
3
Slowing/stopping (deceleration)390 (6.4%)
4
Stopped in traffic379 (6.2%)
5
Legally Parked319 (5.2%)
6
Turning right214 (3.5%)
7
Backing183 (3%)
8
Other (explain in narrative)135 (2.2%)
9
Changing lanes125 (2%)

Showing top 9 of 19 reported. 10 additional (220 total) not shown: Negotiating a curve, Overtaking/passing, Entering traffic lane (merging), Making U-turn, Starting in road, Illegally Parked/Unattended, Accelerating in road, Leaving a parked position, Leaving traffic lane, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Vehicle unit records

Pedestrian/Cyclist Action

For non-motorists involved in crashes, the most frequently recorded action was 'Entering or crossing roadway,' which was cited in 44 instances. A much smaller number, 6 individuals, were moving along the roadway with traffic at the time of the collision.

Pedestrian/Cyclist Action

1
Entering or crossing roadway44 (66.7%)
2
Movement: Along roadway with traffic6 (9.1%)
3
Other5 (7.6%)
4
Movement: On sidewalk3 (4.5%)
5
Approaching or leaving vehicle2 (3%)
6
Going to/coming from school2 (3%)
7
Playing on or working on vehicle1 (1.5%)
8
Entering/exiting vehicle1 (1.5%)
9
Movement: Along roadway against traffic1 (1.5%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Movement: Along roadway (direction unknown).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Non-motorist records linked to crash events

Person Type

Of the 8,037 individuals involved in crashes, the vast majority, 7,648 people, were drivers. Passengers constituted the next largest group with 323 individuals. The data also includes 36 pedestrians and 29 bicyclists involved in these incidents.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Person Injury Severity

Across all 8,037 individuals involved, 31 suffered fatal injuries (K). An additional 102 people sustained serious injuries (A), 463 had minor injuries (B), and 824 had possible injuries (C). The largest group of individuals, excluding those with no injury data, were those with possible injuries.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Crash-level records

Occupant Safety Equipment

Among the subset of participants where safety equipment use was documented, 919 individuals were recorded as using a shoulder and lap belt. In contrast, 126 individuals were recorded as having used no safety equipment. Child restraints, including forward-facing seats and boosters, were used by a total of 18 children.

Occupant Safety Equipment

"Other" combines 3 smaller categories (7 records): Child safety seat (rear-facing) (3), Shoulder belt only used (2), Helmet (other) (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · Person-level records linked to crash events

Vehicles Per Crash

The most common type of collision involved two vehicles, with 2,362 such incidents recorded. Single-vehicle crashes were the next most frequent, with 1,106 occurrences. Crashes involving three or more vehicles were less common, with 185 three-vehicle crashes and 22 four-vehicle crashes reported.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-04-01 to 2015-04-30 · 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: 2015-04-01 through 2015-04-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-04-01 through 2015-04-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,680
  • Total persons involved: 8,037
  • Total vehicles involved: 6,500

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: April 2015." Published September 9, 2026. Reporting period: 2015-04-01 to 2015-04-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/april-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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