Monthly Traffic Safety Analysis

4,303 CRASHES IN
IOWA, IA
JULY 2015

In July 2015, Iowa recorded 4,303 motor vehicle crashes, resulting in 34 fatalities and 1,820 injuries. The most frequently cited contributing factor to these collisions was 'Followed too close,' which was attributed to 538 incidents, representing 12.5% of all crashes. Collisions involving animals were the second-leading cause, noted in 485 crashes.

4,303

Total Crash Events

34

Persons Killed

1,820

Persons Injured

30

Fatal Crash Events

Note: "Persons Killed" (34) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

During this period, 31 motorists were killed and 1,717 were injured in crashes. Vulnerable road users also suffered casualties, with 2 pedestrians killed and 36 injured. Additionally, 1 cyclist was killed and 59 were injured.

2

Pedestrians Killed

1

Cyclists Killed

31

Motorists Killed

0

Other Killed

36

Pedestrians Injured

59

Cyclists Injured

1,717

Motorists Injured

8

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequencies peaked on Friday, which saw 806 incidents, and the most common time for a crash was the 4 p.m. hour with 365 events. A significant majority of collisions, 3,167 or approximately 73.6%, occurred during daylight hours. The evening commute hours between 3 p.m. and 6 p.m. represented a sustained period of high crash activity.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 4,303 total crashes, 2,899 (67.4%) resulted in no injuries, being classified as property damage only. The remaining incidents involved some level of injury, including 137 serious injury crashes and 515 minor injury crashes. There were 30 distinct fatal crashes during this period, which resulted in a total of 34 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 34 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.7%
Serious Injury137serious injury crashes3.2%
Minor Injury515minor injury crashes12%
Possible Injury722possible injury crashes16.8%
No Injury2,899no injury crashes67.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor identified in crashes was 'Followed too close,' accounting for 538 incidents (12.5%). The second most common factor was the presence of an animal on the roadway, cited in 485 crashes (11.3%). Other significant factors included drivers losing control (265 crashes) and failing to yield the right-of-way from a stop sign (253 crashes).

Officer-Reported Primary Contributing Cause

Followed too close538 (12.5%)
Animal485 (11.3%)
Other (explain in narrative): Other272 (6.3%)
Lost Control265 (6.2%)
FTYROW: From stop sign253 (5.9%)
FTYROW: Making left turn216 (5%)
Ran off road - left197 (4.6%)
Ran Traffic Signal160 (3.7%)
Ran off road - straight150 (3.5%)
Ran Stop Sign118 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The vast majority of crashes occurred in ideal driving conditions, with 3,408 (79.2%) on dry roads and 2,817 (65.5%) in clear weather. Similarly, 3,167 crashes (73.6%) happened during daylight hours. Adverse conditions were less frequent, with rain reported in 309 crashes and crashes on wet road surfaces totaling 393.

Weather

Clear2,817 (71.8%)
Cloudy775 (19.7%)
Rain309 (7.9%)
Fog, smoke, smog20 (0.5%)
Freezing rain/drizzle2 (0.1%)
Sleet, hail2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Weather condition at time of crash

Lighting

Daylight3,167 (80.3%)
Dark - roadway not lighted324 (8.2%)
Dark - roadway lighted305 (7.7%)
Dusk76 (1.9%)
Dawn62 (1.6%)
Dark - unknown roadway lighting11 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Lighting condition field

Road Surface

Dry3,408 (86.7%)
Wet393 (10.0%)
Gravel113 (2.9%)
Sand5 (0.1%)
Mud, dirt4 (0.1%)
Other (explain in narrative)3 (0.1%)
Water (standing or moving)2 (0.1%)
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was the most represented, with 1,399 individuals, followed closely by the 16-20 age group with 1,351 individuals. Among the 7,538 vehicles involved, Chevrolet was the most frequent make with 1,482 vehicles, followed by Ford with 1,252. Toyota and Dodge vehicles were also commonly involved, with 548 and 523 vehicles respectively.

Top Vehicle Makes (7,538 vehicles)

1
FORD1,252 (16.6%)
2
CHEV853 (11.3%)
3
CHEVROLET629 (8.3%)
4
TOYT336 (4.5%)
5
DODG281 (3.7%)
6
DODGE242 (3.2%)
7
HOND224 (3%)
8
GMC219 (2.9%)
9
TOYOTA212 (2.8%)
10
JEEP205 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Vehicle unit records

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

Sex Distribution (6,678 persons with recorded sex)

Male3,710 (55.6%)
Female2,968 (44.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Person-level records linked to crash events

Major Cause

The most frequently recorded major cause of crashes was 'Followed too close,' cited in 538 incidents. Collisions with animals were the second-leading cause, contributing to 485 crashes. Other primary causes included drivers losing control (265 crashes) and failing to yield right-of-way from a stop sign (253 crashes).

Major Cause

1
Followed too close538 (13.5%)
2
Animal485 (12.2%)
3
Other (explain in narrative): Other272 (6.8%)
4
Lost Control265 (6.7%)
5
FTYROW: From stop sign253 (6.4%)
6
FTYROW: Making left turn216 (5.4%)
7
Ran off road - left197 (4.9%)
8
Ran Traffic Signal160 (4%)
9
Ran off road - straight150 (3.8%)

Showing top 9 of 49 reported. 40 additional (1,448 total) not shown: Ran Stop Sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Made improper turn, Driver Distraction: Other interior distraction, Driving too fast for conditions, Improper or erratic lane changing, FTYROW: From driveway, Other (explain in narrative): No improper action, Swerving/Evasive Action, FTYROW: Other (explain in narrative), Improper Backing, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Exterior distraction, FTYROW: At uncontrolled intersection, Exceeded authorized speed, FTYROW: From yield sign, FTYROW: From parked position, Failed to keep in proper lane, FTYROW: To pedestrian, Driver Distraction: Reaching for object(s)/fallen object(s), Ran off road - right, Other (explain in narrative): Vision obstructed, Traveling wrong way or on wrong side of road, Passing: Other passing (explain in narrative), Driver Distraction: Adjusting devices (radio, climate), Operator inexperience, Crossed centerline (undivided), Driver Distraction: Passenger, Driver Distraction: Other electronic device activity, Failed to yield to emergency vehicle, Passing: With insufficient distance/inadequate visibility, Driver Distraction: Manual operation of an electronic communication device, FTYROW: Making right turn on red signal, Equipment failure, Driver Distraction: Talking on a hand-held device, Passing: On wrong side, Illegally Parked/Unattended, Driver Distraction: Unrestrained animal, Aggressive driving/road rage, Other (explain in narrative): Improper operation.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, which occurred in 2,589 crashes, or 60.2% of the total. Collisions with non-fixed objects, primarily animals, were the second most frequent event type with 469 incidents. Among collisions with fixed objects, striking a ditch was the most common, recorded in 201 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic2,589 (60.9%)
2
Collision with: Animal469 (11%)
3
Collision with fixed object: Ditch201 (4.7%)
4
Collision with: Parked motor vehicle181 (4.3%)
5
Non-collision events: Overturn/rollover169 (4%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)93 (2.2%)
7
Collision with fixed object: Utility pole/light support49 (1.2%)
8
Non-collision events: Other non-collision (explain in narrative)36 (0.8%)
9
Other (explain in narrative)35 (0.8%)

Showing top 9 of 46 reported. 37 additional (429 total) not shown: Miscellaneous events: Hit and run, Collision with: Re-entering roadway, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Tree, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Cable barrier, Collision with fixed object: Embankment, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Traffic sign support, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Ground, Non-collision events: Fell/jumped from vehicle, Non-collision events: Vehicle went airborne, Collision with fixed object: Guardrail - face, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Building, Collision with: Work zone maintenance equipment, Collision with fixed object: Other fixed object (explain in narrative), Collision with: Thrown or falling object, Collision with fixed object: Fence, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Guardrail - end, Non-collision events: Jackknife, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Traffic signal support, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Fire hydrant, Collision with fixed object: Mailbox, Collision with fixed object: Landscape/shrubbery, Miscellaneous events: Fire/explosion, Collision with fixed object: Wall, Collision with: Railway vehicle/train, Miscellaneous events: Vehicle out of gear/rolled, Collision with fixed object: Bridge pier or support.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Roadway Junction / Feature

Crashes were more likely to occur on non-intersection roadway segments, which accounted for 1,976 incidents. Four-way intersections were the most common type of junction for crashes, with 1,081 incidents occurring at these locations. T-intersections were the site of another 286 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature1,976 (50.1%)
2
Intersection: Four-way intersection1,081 (27.4%)
3
Intersection: T-intersection286 (7.2%)
4
Non-intersection: Driveway access (related, not in)166 (4.2%)
5
Intersection: Other intersection (explain in narrative)68 (1.7%)
6
Non-intersection: Other non-intersection (explain in narrative)52 (1.3%)
7
Non-intersection: Driveway access (within)48 (1.2%)
8
Intersection: Intersection with ramp43 (1.1%)
9
Interchange-related: Off-ramp41 (1%)

Showing top 9 of 24 reported. 15 additional (184 total) not shown: Interchange-related: On-ramp merge area, Interchange-related: Off-ramp, diverge area, Non-intersection: Crossover-related, Non-intersection: Alley, Intersection: Y-intersection, Interchange-related: On-ramp, Interchange-related: Mainline, between ramps, Non-intersection: Railroad grade crossing, Interchange-related: Other interchange (explain in narrative), Intersection: Roundabout, Intersection: Five points or more, Intersection: L-intersection, Non-intersection: Bike lanes, Intersection: Shared use path or trail, Intersection: Traffic circle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 3,592 of the 7,538 vehicles. Sport utility vehicles (1,506) and four-tire light trucks or pickups (1,198) were the next most frequent types. Commercial vehicles and motorcycles represented a smaller but notable share, with 205 tractor/semi-trailers and 182 motorcycles involved in collisions.

Vehicle Type

"Other" combines 21 smaller categories (239 records): Single-unit truck (>= 3 axles) (60), Cargo/panel van (57), Passenger van (seats 9-15) (19), Farm tractor (16), Moped (13), Motor home/recreational vehicle (10), All-terrain vehicle (ATV) (9), Truck tractor (bobtail) (8), Truck/trailer (7), Farm equipment (explain in narrative) (5), School bus (seats > 15) (5), Other (explain in narrative) (5), Other bus (seats > 15) (5), Other small bus (seats 9-15) (4), Tractor/doubles (4), Golf cart (4), Train (4), Other light truck (<=10000 lbs) (1), Street legal, low-speed vehicle (1), Maintenance/construction vehicle (1), Other heavy truck (> 10000 lbs) (cannot classify) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Vehicle unit records

Traffic Control Device

For a majority of vehicles involved in crashes, no traffic controls were present; this was the case for 4,338 vehicles. Where traffic controls were a factor, traffic signals were the most common, governing 1,671 vehicles involved in crashes. Stop signs were the next most frequent control device, noted for 782 vehicles.

Traffic Control Device

"Other" combines 5 smaller categories (82 records): No Passing Zone (marked) (35), Warning sign (26), Inoperative (not functioning properly) (10), Railway crossing device (10), Traffic director (person) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · 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 1,959 vehicles. This suggests a high prevalence of head-on or front-to-object collisions. The rear of the vehicle was the second most-damaged area, noted in 1,020 cases, which aligns with the high number of rear-end collisions.

Most Damaged Area

"Other" combines 10 smaller categories (1,630 records): Passenger side - front (313), Driver side - rear (288), Passenger side - rear (246), Rear - driver side corner (237), Rear - passenger side corner (188), Top (149), Other (explain in narrative) (112), Non-collision/no damage (52), Undercarriage (38), Cargo loss (7).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

Driver impairment was suspected or confirmed in 176 crashes, representing 4.1% of all incidents. Of these, alcohol was the sole impairing substance in 154 cases. Drugs were cited in 18 cases, and a combination of alcohol and drugs was noted in 4 cases.

Crashes by County

Crash distribution was concentrated in the state's most populous counties, with Polk County reporting the highest number at 802 incidents. Scott County followed with 310 crashes, Linn County with 271, and Johnson County with 202. These top four counties alone accounted for approximately 37% of all crashes statewide.

Crashes by County

1
POLK802 (20.7%)
2
SCOTT310 (8%)
3
LINN271 (7%)
4
JOHNSON202 (5.2%)
5
POTTAWATTAMIE180 (4.7%)
6
WOODBURY168 (4.3%)
7
DUBUQUE164 (4.2%)
8
BLACK HAWK147 (3.8%)
9
STORY119 (3.1%)

Showing top 9 of 50 reported. 41 additional (1,506 total) not shown: DALLAS, DES MOINES, CERRO GORDO, CLINTON, WEBSTER, LEE, WARREN, WAPELLO, MARSHALL, MARION, JASPER, WINNESHIEK, MUSCATINE, HAMILTON, BUENA VISTA, SIOUX, BREMER, WASHINGTON, DICKINSON, BOONE, CEDAR, JONES, IOWA, BUCHANAN, PLYMOUTH, CLAYTON, POWESHIEK, HARDIN, HARRISON, HENRY, CARROLL, CLAY, JEFFERSON, JACKSON, MAHASKA, PAGE, DELAWARE, CRAWFORD, FAYETTE, APPANOOSE, BENTON.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Crashes by City

Des Moines recorded the highest number of crashes among all cities with 415 incidents. Davenport had the second-highest volume with 237 crashes, followed by Cedar Rapids with 150. Many crashes, particularly in rural areas, occur outside of municipal boundaries and are not included in this city-specific ranking.

Crashes by City

1
DES MOINES415 (16.1%)
2
DAVENPORT237 (9.2%)
3
CEDAR RAPIDS150 (5.8%)
4
SIOUX CITY146 (5.7%)
5
COUNCIL BLUFFS139 (5.4%)
6
DUBUQUE129 (5%)
7
IOWA CITY105 (4.1%)
8
WEST DES MOINES102 (4%)
9
WATERLOO94 (3.7%)

Showing top 9 of 50 reported. 41 additional (1,056 total) not shown: ANKENY, AMES, URBANDALE, MASON CITY, BURLINGTON, FORT DODGE, CLINTON, MARION, BETTENDORF, CORALVILLE, CLIVE, CEDAR FALLS, OTTUMWA, ALTOONA, MARSHALLTOWN, STORM LAKE, MUSCATINE, KEOKUK, OSKALOOSA, FORT MADISON, CARROLL, GRIMES, DECORAH, WEBSTER CITY, HIAWATHA, CLEAR LAKE, PLEASANT HILL, NORWALK, PELLA, MOUNT VERNON, LE MARS, WAUKEE, JOHNSTON, MONTICELLO, FAIRFIELD, WASHINGTON, INDIANOLA, BOONE, SPENCER, WINDSOR HEIGHTS, DE WITT.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 4,049 incidents, occurred on paved roadways. However, a notable number of crashes, 233 or approximately 5.4% of the total with known surface type, took place on unpaved surfaces such as gravel or dirt roads. This reflects the state's extensive secondary road network.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Roadway Contributing Factor

Among the small percentage of crashes where a roadway factor was cited, poor surface conditions such as wet or icy pavement were the leading contributor, noted in 91 incidents. Work zone-related factors were the second most common, contributing to 81 crashes. Debris in the roadway was a factor in 14 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)91 (34.1%)
2
Work Zone (roadway-related)81 (30.3%)
3
Slippery, loose or worn surface19 (7.1%)
4
Traffic backup, prior crash16 (6%)
5
Debris14 (5.2%)
6
Traffic backup, regular congestion10 (3.7%)
7
Obstruction in roadway9 (3.4%)
8
Ruts/holes/bumps7 (2.6%)
9
Traffic backup, prior non-recurring incident6 (2.2%)

Showing top 9 of 13 reported. 4 additional (14 total) not shown: Disabled vehicle, Shoulders (none, low, soft, high), Non-highway work, Traffic control obscured.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Driver Condition

In cases where a driver's condition was noted as other than 'apparently normal,' being under the influence of alcohol was the most frequent, recorded for 187 drivers. Driver fatigue or falling asleep was the second most common condition, cited for 79 drivers. Emotional states like anger or depression were noted in 37 instances.

Driver Condition

1
Under the influence of alcohol187 (51.7%)
2
Asleep/fatigued79 (21.8%)
3
Emotional (e.g. depressed, angry)37 (10.2%)
4
Medical condition (seizure, reaction)33 (9.1%)
5
Illness/fainted8 (2.2%)
6
Under the influence of drugs/meds6 (1.7%)
7
Paraplegic/wheelchair restricted4 (1.1%)
8
Physical impairment4 (1.1%)
9
Walks with a cane/crutches2 (0.6%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Hearing impaired/deaf, Visually impaired.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Crashes by Iowa DOT District

The distribution of crashes across Iowa's DOT districts shows a concentration in the state's primary population and travel corridors. District 1, which includes the Des Moines metro area, had the highest number of crashes with 1,236. District 6, covering eastern Iowa including Cedar Rapids and Davenport, followed closely with 1,199 crashes.

Crashes by Iowa DOT District

1
District 11,236 (28.7%)
2
District 61,199 (27.9%)
3
District 5512 (11.9%)
4
District 3468 (10.9%)
5
District 2461 (10.7%)
6
District 4427 (9.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Property Damage

The most common estimated property damage cost was in the '$1,500 - $7,500' range, which applied to 3,061 crashes, or 71.1% of the total. A smaller number of incidents resulted in severe damage, with 102 crashes (2.4%) estimated to have costs exceeding $25,000. Only 203 crashes were estimated to have damage under $1,500.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events such as running off the road were the most common crash type, accounting for 1,257 incidents (29.2%). Rear-end collisions were the second most frequent manner of collision, with 1,108 incidents (25.7%). Together, these two categories represent more than half of all crashes.

Manner of Collision

"Other" combines 3 smaller categories (170 records): Sideswipe, opposite direction (78), Head-on (front to front) (76), Rear to rear (16).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was 'Movement essentially straight,' recorded for 4,182 vehicles. Turning left was the next most frequent action, noted for 749 vehicles. A significant number of vehicles were either slowing or stopped in traffic prior to being involved in a collision, with 459 and 388 vehicles in these respective categories.

Pre-Crash Driver Action

1
Movement essentially straight4,182 (57.8%)
2
Turning left749 (10.3%)
3
Slowing/stopping (deceleration)459 (6.3%)
4
Stopped in traffic388 (5.4%)
5
Legally Parked361 (5%)
6
Turning right295 (4.1%)
7
Backing176 (2.4%)
8
Other (explain in narrative)156 (2.2%)
9
Changing lanes154 (2.1%)

Showing top 9 of 19 reported. 10 additional (318 total) not shown: Negotiating a curve, Entering traffic lane (merging), Overtaking/passing, Leaving traffic lane, Making U-turn, Illegally Parked/Unattended, Starting in road, Leaving a parked position, Accelerating in road, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Vehicle unit records

Pedestrian/Cyclist Action

For non-motorists involved in crashes, the most frequently recorded action was 'Entering or crossing roadway,' which was noted in 62 instances. A smaller number of incidents occurred while the non-motorist was moving along the roadway, either with traffic (12) or against it (4). These actions describe the circumstances for both pedestrians and bicyclists.

Pedestrian/Cyclist Action

1
Entering or crossing roadway62 (61.4%)
2
Movement: Along roadway with traffic12 (11.9%)
3
Other11 (10.9%)
4
Movement: On sidewalk5 (5%)
5
Movement: Along roadway against traffic4 (4%)
6
Approaching or leaving vehicle3 (3%)
7
Movement: On shoulder/median2 (2%)
8
Playing on or working on vehicle1 (1%)
9
Disabled vehicle-related/pushing vehicle1 (1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Non-motorist records linked to crash events

Person Type

Of the 9,481 individuals involved in crashes, the vast majority, 8,930 people (94.2%), were drivers. Passengers constituted the next largest group with 445 individuals. A total of 98 vulnerable road users were involved, including 60 bicyclists and 38 pedestrians.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Person Injury Severity

Among the 9,481 people involved in crashes, 1,820 sustained some level of injury and 34 suffered fatal injuries. The most common injury classification was 'Possible Injury,' with 948 individuals, followed by 'Minor Injury' with 708 individuals. A total of 164 people sustained 'Serious' injuries.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Occupant Safety Equipment

Based on available data for 1,385 occupants, 1,146 (82.7%) were recorded as using a shoulder and lap belt. However, 156 occupants, representing 11.3% of this subset, were reportedly not using any safety equipment. Helmets were used by 29 motorcycle riders.

Occupant Safety Equipment

"Other" combines 3 smaller categories (8 records): Booster seat (3), Helmet (other) (3), Child safety seat (rear-facing) (2).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common type of crash, accounting for 2,686 incidents or 62.4% of the total. Single-vehicle crashes were the next most frequent, with 1,363 incidents (31.7%). Multi-vehicle pile-ups involving three or more vehicles were less common, with 252 such events recorded.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-07-01 to 2015-07-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2015-07-01 through 2015-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-07-01 through 2015-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,303
  • Total persons involved: 9,481
  • Total vehicles involved: 7,538

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: July 2015." Published September 9, 2026. Reporting period: 2015-07-01 to 2015-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-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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