Monthly Traffic Safety Analysis

5,352 CRASHES IN
IOWA, IA
DECEMBER 2015

In December 2015, Iowa recorded 5,352 traffic crashes, resulting in 24 fatalities and 1,570 injuries. These incidents involved 10,738 individuals and 9,018 vehicles across the state. A notable finding from the data is that collisions with animals were the single most cited contributing factor, accounting for 800 crashes, or nearly 15% of the total.

5,352

Total Crash Events

24

Persons Killed

1,570

Persons Injured

22

Fatal Crash Events

Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Of the individuals killed or seriously injured, motorists comprised the largest group, with 21 fatalities and 1,531 injuries. Vulnerable road users also suffered significant harm; 3 pedestrians were killed and 31 were injured. Additionally, 7 cyclists were injured in crashes during this period.

3

Pedestrians Killed

0

Cyclists Killed

21

Motorists Killed

0

Other Killed

31

Pedestrians Injured

7

Cyclists Injured

1,531

Motorists Injured

1

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash patterns in December 2015 showed a clear peak during the work week, with Thursday being the most frequent day for incidents, recording 1,061 crashes. The evening commute was the most hazardous time of day, as the hour between 5 p.m. and 6 p.m. saw the highest volume with 626 crashes. While incidents occurred around the clock, a majority of crashes (2,563, or 47.9%) happened during daylight hours.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 76.1% (4,071 incidents), resulted in no injuries. Injury-sustaining crashes, including those with possible, minor, or serious injuries, accounted for 23.5% of the total (1,259 incidents). A small fraction of crashes, 22 in total (0.4%), were fatal. These 22 fatal crashes led to the deaths of 24 individuals, as a single crash can result in multiple fatalities.

Severity is per crash event (most severe injury). 22 fatal crash events resulted in 24 persons killed.

Outcome by Severity (Crash Events)

Fatal22fatal crashes0.4%
Serious Injury71serious injury crashes1.3%
Minor Injury356minor injury crashes6.7%
Possible Injury832possible injury crashes15.5%
No Injury4,071no injury crashes76.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors reveals that environmental and driver behaviors were primary drivers of crashes. The leading reported factor was the presence of an animal on the roadway, cited in 800 crashes (14.9%). Driver errors followed, with 'Followed too close' listed in 478 incidents (8.9%) and 'Driving too fast for conditions' in 475 incidents (8.9%).

Officer-Reported Primary Contributing Cause

Animal800 (14.9%)
Followed too close478 (8.9%)
Driving too fast for conditions475 (8.9%)
Lost Control367 (6.9%)
Ran off road - left343 (6.4%)
Other (explain in narrative): Other309 (5.8%)
FTYROW: From stop sign266 (5%)
Ran off road - straight251 (4.7%)
FTYROW: Making left turn236 (4.4%)
Ran Traffic Signal160 (3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A substantial number of crashes occurred in seemingly ideal conditions, with 47.9% (2,563) happening in daylight and 47.6% (2,547) on dry road surfaces. However, adverse winter conditions played a significant role, as 658 crashes occurred in snow and 573 on snow-covered roads. An additional 886 crashes took place on wet road surfaces, and 1,113 incidents happened on lighted roadways after dark.

Weather

Clear2,070 (44.2%)
Cloudy1,270 (27.1%)
Snow658 (14.1%)
Rain364 (7.8%)
Freezing rain/drizzle150 (3.2%)
Fog, smoke, smog92 (2.0%)
Blowing Snow39 (0.8%)
Sleet, hail27 (0.6%)
Severe Winds5 (0.1%)
Blowing sand, soil, dirt3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight2,563 (54.6%)
Dark - roadway lighted1,113 (23.7%)
Dark - roadway not lighted708 (15.1%)
Dusk156 (3.3%)
Dawn135 (2.9%)
Dark - unknown roadway lighting21 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry2,547 (54.3%)
Wet886 (18.9%)
Snow573 (12.2%)
Ice/frost509 (10.9%)
Slush112 (2.4%)
Gravel42 (0.9%)
Other (explain in narrative)10 (0.2%)
Mud, dirt5 (0.1%)
Sand3 (0.1%)
Water (standing or moving)2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Among the 10,738 people involved in crashes, individuals in the 26-34 age group were the most represented, with 1,767 people. Analysis of the 9,018 vehicles involved shows a prevalence of domestic brands. Chevrolet was the most frequent make with 1,945 vehicles, followed by Ford with 1,484 and Dodge with 668 vehicles involved in collisions.

Top Vehicle Makes (9,018 vehicles)

1
FORD1,484 (16.5%)
2
CHEV1,192 (13.2%)
3
CHEVROLET753 (8.3%)
4
DODG388 (4.3%)
5
TOYT381 (4.2%)
6
GMC298 (3.3%)
7
DODGE280 (3.1%)
8
JEEP264 (2.9%)
9
TOYOTA255 (2.8%)
10
HOND240 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Vehicle unit records

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

Sex Distribution (7,943 persons with recorded sex)

Male4,419 (55.6%)
Female3,524 (44.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The leading major cause attributed to crashes in Iowa during this period was the presence of an animal, cited in 800 incidents. Following this, common driver errors were prominent, including 'Followed too close' which was a factor in 478 crashes, and 'Driving too fast for conditions' noted in 475 crashes. Losing control of the vehicle was also a significant factor, contributing to 367 crashes.

Major Cause

1
Animal800 (16%)
2
Followed too close478 (9.5%)
3
Driving too fast for conditions475 (9.5%)
4
Lost Control367 (7.3%)
5
Ran off road - left343 (6.8%)
6
Other (explain in narrative): Other309 (6.2%)
7
FTYROW: From stop sign266 (5.3%)
8
Ran off road - straight251 (5%)
9
FTYROW: Making left turn236 (4.7%)

Showing top 9 of 49 reported. 40 additional (1,490 total) not shown: Ran Traffic Signal, Ran Stop Sign, Driver Distraction: Other interior distraction, Operating vehicle in an reckless, erratic, careless, negligent manner, Improper or erratic lane changing, Made improper turn, FTYROW: From driveway, Swerving/Evasive Action, Improper Backing, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Exterior distraction, FTYROW: Other (explain in narrative), Other (explain in narrative): No improper action, FTYROW: At uncontrolled intersection, Exceeded authorized speed, Failed to keep in proper lane, Ran off road - right, Driver Distraction: Reaching for object(s)/fallen object(s), FTYROW: From yield sign, Driver Distraction: Adjusting devices (radio, climate), FTYROW: From parked position, Other (explain in narrative): Vision obstructed, Traveling wrong way or on wrong side of road, Driver Distraction: Passenger, Driver Distraction: Manual operation of an electronic communication device, Illegally Parked/Unattended, FTYROW: Making right turn on red signal, Aggressive driving/road rage, Driver Distraction: Talking on a hand-held device, FTYROW: To pedestrian, Passing: Other passing (explain in narrative), Crossed centerline (undivided), Driver Distraction: Other electronic device activity, Equipment failure, Passing: With insufficient distance/inadequate visibility, Operator inexperience, Cargo/equipment loss or shift, Other (explain in narrative): Improper operation, Passing: Through/around barrier, Over correcting/over steering.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a 'Collision with: Vehicle in traffic,' which occurred in 2,866 crashes. Collisions with animals were the second most frequent event, accounting for 790 incidents. Single-vehicle events were also common, with 'Overturn/rollover' being the first harmful event in 255 crashes and collisions with a ditch in 269 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic2,866 (54%)
2
Collision with: Animal790 (14.9%)
3
Collision with fixed object: Ditch269 (5.1%)
4
Non-collision events: Overturn/rollover255 (4.8%)
5
Collision with: Parked motor vehicle241 (4.5%)
6
Collision with fixed object: Utility pole/light support113 (2.1%)
7
Collision with fixed object: Cable barrier72 (1.4%)
8
Collision with fixed object: Curb/island/raised median51 (1%)
9
Collision with fixed object: Guardrail - face45 (0.8%)

Showing top 9 of 47 reported. 38 additional (607 total) not shown: Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Re-entering roadway, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Traffic sign support, Collision with fixed object: Tree, Collision with: Struck/struck by object/cargo/person from other vehicle, Miscellaneous events: Hit and run, Other (explain in narrative), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Embankment, Collision with fixed object: Other post/pole/support (explain in narrative), Non-collision events: Jackknife, Collision with fixed object: Fence, Collision with fixed object: Other fixed object (explain in narrative), Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Mailbox, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Guardrail - end, Collision with fixed object: Fire hydrant, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Culvert/pipe opening, Non-collision events: Vehicle went airborne, Collision with fixed object: Building, Collision with fixed object: Ground, Collision with fixed object: Bridge pier or support, Miscellaneous events: Eluding law enforcement, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Snow bank, Collision with: Thrown or falling object, Collision with fixed object: Traffic signal support, Collision with fixed object: Landscape/shrubbery, Miscellaneous events: Immersion, Miscellaneous events: Vehicle out of gear/rolled, Collision with: Railway vehicle/train, Collision with fixed object: Wall, Collision with fixed object: Impact attenuator/crash cushion, Miscellaneous events: Fire/explosion.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

Analysis of crash locations shows that more incidents occurred on non-intersection road segments than at intersections. Crashes at 'Non-junction/no special feature' locations accounted for 2,550 incidents. In comparison, traditional 'Four-way intersections' were the site of 1,192 crashes, making them the most common type of junction for collisions.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature2,550 (54.1%)
2
Intersection: Four-way intersection1,192 (25.3%)
3
Intersection: T-intersection353 (7.5%)
4
Non-intersection: Driveway access (related, not in)176 (3.7%)
5
Intersection: Other intersection (explain in narrative)76 (1.6%)
6
Non-intersection: Driveway access (within)68 (1.4%)
7
Non-intersection: Other non-intersection (explain in narrative)48 (1%)
8
Interchange-related: On-ramp merge area41 (0.9%)
9
Intersection: Intersection with ramp40 (0.8%)

Showing top 9 of 23 reported. 14 additional (169 total) not shown: Interchange-related: Off-ramp, Non-intersection: Alley, Interchange-related: Off-ramp, diverge area, Interchange-related: On-ramp, Non-intersection: Crossover-related, Intersection: Y-intersection, Non-intersection: Railroad grade crossing, Interchange-related: Mainline, between ramps, Intersection: Five points or more, Intersection: Roundabout, Intersection: L-intersection, Interchange-related: Other interchange (explain in narrative), Non-intersection: Bike lanes, Intersection: Traffic circle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 4,274 of the 9,018 vehicles. Sport utility vehicles were the second most frequent type with 1,960 vehicles, followed by four-tire light trucks and pickups at 1,545. Commercial vehicles also had a notable presence, with 238 tractor/semi-trailers involved in incidents.

Vehicle Type

"Other" combines 19 smaller categories (155 records): Single-unit truck (>= 3 axles) (55), School bus (seats > 15) (15), Passenger van (seats 9-15) (15), Farm tractor (11), Other bus (seats > 15) (9), Maintenance/construction vehicle (8), Truck tractor (bobtail) (7), Truck/trailer (7), Other light truck (<=10000 lbs) (5), Tractor/doubles (5), Motorcycle (4), Motor home/recreational vehicle (3), Farm equipment (explain in narrative) (3), Train (2), All-terrain vehicle (ATV) (2), 3-wheeled, enclosed (1), Other (explain in narrative) (1), Moped (1), Other heavy truck (> 10000 lbs) (cannot classify) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

A majority of vehicles involved in crashes were in areas with no traffic controls present, accounting for 5,180 vehicles. For crashes where traffic controls were a factor, traffic signals were the most common, with 1,935 vehicles involved in incidents at signalized locations. Stop signs were the next most frequent traffic control device, present for 901 vehicles involved in crashes.

Traffic Control Device

"Other" combines 4 smaller categories (48 records): Warning sign (21), Railway crossing device (14), Work zone sign (8), Inoperative (not functioning properly) (5).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · 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 2,291 vehicles. This suggests a high prevalence of head-on or front-corner collisions. The rear of the vehicle was the most damaged area in 1,139 cases, which aligns with the high number of rear-end collisions reported.

Most Damaged Area

"Other" combines 10 smaller categories (1,896 records): Passenger side - front (363), Driver side - rear (313), Rear - driver side corner (307), Passenger side - rear (302), Rear - passenger side corner (222), Top (209), Other (explain in narrative) (89), Non-collision/no damage (48), Undercarriage (35), Cargo loss (8).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

Driver impairment was suspected or confirmed in 151 crashes, representing 2.8% of all incidents. Alcohol was the most frequently cited substance, involved in 138 of these crashes. Drugs were a factor in 11 crashes, and a combination of alcohol and drugs was noted in 2 incidents.

Crashes by County

Crash distribution was concentrated in Iowa's most populous counties. Polk County, home to Des Moines, recorded the highest number of incidents with 934 crashes, representing 17.5% of the statewide total. Scott and Linn counties followed, each reporting 333 crashes, with Black Hawk County recording 244 crashes.

Crashes by County

1
POLK934 (19.7%)
2
LINN333 (7%)
3
SCOTT333 (7%)
4
WOODBURY247 (5.2%)
5
BLACK HAWK244 (5.1%)
6
JOHNSON212 (4.5%)
7
POTTAWATTAMIE199 (4.2%)
8
STORY182 (3.8%)
9
DUBUQUE165 (3.5%)

Showing top 9 of 50 reported. 41 additional (1,889 total) not shown: DALLAS, CERRO GORDO, CLINTON, MARSHALL, WEBSTER, LEE, DES MOINES, JASPER, PLYMOUTH, MUSCATINE, WARREN, FAYETTE, CEDAR, WAPELLO, CARROLL, MARION, HARRISON, BOONE, HAMILTON, WINNESHIEK, FLOYD, SIOUX, CLAYTON, JONES, CLAY, BREMER, BUENA VISTA, IOWA, ALLAMAKEE, BENTON, BUCHANAN, POWESHIEK, DICKINSON, ADAIR, HENRY, DELAWARE, MILLS, CASS, TAMA, CRAWFORD, APPANOOSE.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Crashes by City

Iowa's major cities saw the highest concentration of crashes within municipal boundaries. Des Moines led with 495 crashes, significantly more than any other city. Following Des Moines were Davenport with 246 crashes, Cedar Rapids with 214, and Sioux City with 213 incidents.

Crashes by City

1
DES MOINES495 (16.1%)
2
DAVENPORT246 (8%)
3
CEDAR RAPIDS214 (7%)
4
SIOUX CITY213 (6.9%)
5
COUNCIL BLUFFS139 (4.5%)
6
WATERLOO139 (4.5%)
7
WEST DES MOINES133 (4.3%)
8
DUBUQUE119 (3.9%)
9
IOWA CITY106 (3.5%)

Showing top 9 of 50 reported. 41 additional (1,266 total) not shown: AMES, ANKENY, CEDAR FALLS, MASON CITY, URBANDALE, CORALVILLE, CLINTON, MARSHALLTOWN, FORT DODGE, BETTENDORF, BURLINGTON, CLIVE, MARION, MUSCATINE, OTTUMWA, CARROLL, NEWTON, PLEASANT HILL, GRIMES, FORT MADISON, WAUKEE, SPENCER, LE MARS, HIAWATHA, BOONE, KEOKUK, JOHNSTON, ALTOONA, ALGONA, OSCEOLA, STORM LAKE, CRESTON, CHARLES CITY, INDIANOLA, WINDSOR HEIGHTS, DENISON, WAUKON, MOUNT PLEASANT, ANAMOSA, SPIRIT LAKE, PERRY.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 5,125 incidents, occurred on paved roadways. However, Iowa's extensive secondary road network was also a factor, with 208 crashes, or 3.9% of the total where surface type was known, taking place on unpaved surfaces like gravel or dirt.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

Among crashes where a roadway factor was noted, adverse surface conditions were the leading contributor, cited in 1,047 incidents. This includes wet, icy, or snow-covered roads. A slippery or worn surface was a factor in an additional 54 crashes, while work zone-related roadway issues contributed to 24 incidents.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)1,047 (88.9%)
2
Slippery, loose or worn surface54 (4.6%)
3
Work Zone (roadway-related)24 (2%)
4
Traffic backup, prior crash17 (1.4%)
5
Traffic backup, regular congestion10 (0.8%)
6
Debris7 (0.6%)
7
Traffic backup, prior non-recurring incident4 (0.3%)
8
Non-highway work4 (0.3%)
9
Shoulders (none, low, soft, high)3 (0.3%)

Showing top 9 of 13 reported. 4 additional (8 total) not shown: Obstruction in roadway, Ruts/holes/bumps, Disabled vehicle, Traffic control obscured.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Driver Condition

While most drivers were recorded as 'Apparently normal,' several other conditions were noted as potential factors. Among these, 'Under the influence of alcohol' was the most common, recorded for 168 drivers. Driver fatigue was also a notable factor, with 54 drivers reported as 'Asleep/fatigued,' and 39 drivers were noted as being in an emotional state.

Driver Condition

1
Under the influence of alcohol168 (53%)
2
Asleep/fatigued54 (17%)
3
Emotional (e.g. depressed, angry)39 (12.3%)
4
Medical condition (seizure, reaction)26 (8.2%)
5
Under the influence of drugs/meds11 (3.5%)
6
Illness/fainted5 (1.6%)
7
Walks with a cane/crutches4 (1.3%)
8
Paraplegic/wheelchair restricted4 (1.3%)
9
Visually impaired3 (0.9%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Physical impairment, Impaired due to previous injury, Hearing impaired/deaf.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Crashes by Iowa DOT District

Crash distribution across Iowa's six DOT districts shows a concentration in the state's primary population and traffic corridors. District 1 (Central Iowa/Des Moines) had the highest volume with 1,519 crashes. District 6 (Eastern Iowa/Cedar Rapids) was second with 1,353 crashes, and together these two districts accounted for over half of all incidents.

Crashes by Iowa DOT District

1
District 11,519 (28.4%)
2
District 61,353 (25.3%)
3
District 2711 (13.3%)
4
District 3647 (12.1%)
5
District 4581 (10.9%)
6
District 5541 (10.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Property Damage

The majority of crashes resulted in moderate property damage, with 3,964 incidents having an estimated cost between $1,500 and $7,500. A smaller but significant number, 1,170 crashes, fell into the $7,500 to $25,000 range. There were 97 crashes that resulted in severe property damage estimated at over $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Manner of Collision

Single-vehicle crashes, categorized as 'Non-collision,' were the most frequent type of incident, accounting for 2,025 crashes or 37.8% of the total. Among multi-vehicle incidents, rear-end collisions were the most common, with 1,236 crashes (23.1%). Broadside collisions were the next most frequent type, occurring in 858 crashes (16.0%).

Manner of Collision

"Other" combines 3 smaller categories (208 records): Other (explain in narrative) (98), Rear to side (95), Rear to rear (15).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The most common action for vehicles immediately prior to a crash was 'Movement essentially straight,' recorded for 5,261 vehicles. Actions related to intersections or turning were also frequent, with 776 vehicles turning left and 330 turning right. Additionally, 486 vehicles were stopped in traffic at the time of the collision.

Pre-Crash Driver Action

1
Movement essentially straight5,261 (61.7%)
2
Turning left776 (9.1%)
3
Stopped in traffic486 (5.7%)
4
Slowing/stopping (deceleration)477 (5.6%)
5
Legally Parked432 (5.1%)
6
Turning right330 (3.9%)
7
Backing188 (2.2%)
8
Changing lanes181 (2.1%)
9
Other (explain in narrative)96 (1.1%)

Showing top 9 of 19 reported. 10 additional (298 total) not shown: Negotiating a curve, Overtaking/passing, Entering traffic lane (merging), Leaving traffic lane, Illegally Parked/Unattended, Starting in road, Making U-turn, Accelerating in road, Leaving a parked position, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Vehicle unit records

Pedestrian/Cyclist Action

For the 34 pedestrian-involved crashes where an action was recorded, the vast majority of individuals were 'Entering or crossing roadway' at the time of the collision. This action was noted for 30 of the pedestrians involved in crashes.

Pedestrian/Cyclist Action

1
Entering or crossing roadway30 (71.4%)
2
Other4 (9.5%)
3
Movement: Along roadway with traffic3 (7.1%)
4
Working in trafficway2 (4.8%)
5
Movement: Along roadway (direction unknown)1 (2.4%)
6
Movement: On shoulder/median1 (2.4%)
7
Movement: Along roadway against traffic1 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Non-motorist records linked to crash events

Person Type

Of the 10,738 individuals involved in crashes, the overwhelming majority were drivers, accounting for 10,303 people. Passengers made up the next largest group with 393 individuals. The data also includes 34 pedestrians and 7 bicyclists who were involved in collisions.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 10,738 individuals involved in crashes, 24 people sustained fatal injuries and 1,570 suffered some level of injury. This includes 88 serious injuries, 468 minor injuries, and 1,014 possible injuries. The majority of people involved did not have a reported injury.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Based on the limited data available for safety equipment usage, 1,137 occupants were reported to have used a shoulder and lap belt. In contrast, 100 individuals were recorded as using no safety restraint at the time of the crash. Child safety seats of various types were used by 25 occupants.

Occupant Safety Equipment

"Other" combines 2 smaller categories (2 records): Helmet (DOT compliant) (1), Child safety seat (type unknown) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 2,981 crashes. Single-vehicle crashes were also very frequent, with 2,060 incidents reported. Multi-vehicle pile-ups involving three or more vehicles were less common, with 267 crashes involving three vehicles and 33 crashes involving four.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-12-01 to 2015-12-31 · 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: 2015-12-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-12-01 through 2015-12-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,352
  • Total persons involved: 10,738
  • Total vehicles involved: 9,018

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: December 2015." Published September 9, 2026. Reporting period: 2015-12-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/december-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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