Monthly Traffic Safety Analysis

5,857 CRASHES IN
IOWA, IA
NOVEMBER 2015

In November 2015, Iowa recorded 5,857 traffic crashes, resulting in 23 fatalities and 1,714 injuries. These incidents included 19 fatal crashes and 165 crashes involving a driver under the influence. A notable finding is that collisions with animals were the single most cited contributing factor, accounting for 1,524 crashes, or 26% of the total.

5,857

Total Crash Events

23

Persons Killed

1,714

Persons Injured

19

Fatal Crash Events

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

Of the total persons killed or seriously injured (KSI), motorists comprised the largest group with 21 fatalities and 1,643 injuries. Vulnerable road users also suffered significant harm; two pedestrians were killed and 44 were injured. Additionally, while there were no cyclist fatalities, 23 cyclists were injured in crashes during this period.

2

Pedestrians Killed

0

Cyclists Killed

21

Motorists Killed

0

Other Killed

44

Pedestrians Injured

23

Cyclists Injured

1,643

Motorists Injured

4

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · 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 Fridays being the most frequent day for incidents, recording 1,129 crashes. The daily peak occurred during the evening commute, with 708 crashes happening in the 5 p.m. hour. Overall, crashes were more prevalent during daylight hours, with the period from 6 a.m. to 6 p.m. accounting for a majority of the incidents.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 5,857 crashes, 76.1% (4,457) resulted in no injuries, being classified as property damage only. The remaining incidents involved some level of injury, including 879 possible injuries, 403 minor injuries, and 99 serious injuries. There were 19 distinct fatal crashes, which resulted in a total of 23 fatalities, as a single crash can involve more than one death.

Severity is per crash event (most severe injury). 19 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal19fatal crashes0.3%
Serious Injury99serious injury crashes1.7%
Minor Injury403minor injury crashes6.9%
Possible Injury879possible injury crashes15%
No Injury4,457no injury crashes76.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor cited in crashes was an animal, involved in 1,524 incidents (26%). Following this, common driver-related factors included 'Followed too close' with 521 crashes (8.9%), 'Driving too fast for conditions' with 397 crashes (6.8%), and 'Ran off road - left' with 332 crashes (5.7%). These top factors represent specific actions or circumstances identified by investigating officers.

Officer-Reported Primary Contributing Cause

Animal1,524 (26%)
Followed too close521 (8.9%)
Driving too fast for conditions397 (6.8%)
Ran off road - left332 (5.7%)
Lost Control309 (5.3%)
Other (explain in narrative): Other287 (4.9%)
FTYROW: Making left turn240 (4.1%)
FTYROW: From stop sign228 (3.9%)
Ran off road - straight199 (3.4%)
Ran Traffic Signal159 (2.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A significant portion of crashes occurred in adverse conditions, though clear weather was most common, present for 2,468 crashes. Daylight conditions were reported in 2,491 crashes (42.5%). However, 1,066 crashes occurred on lighted roadways after dark and 755 on unlighted dark roads. While dry pavement was the most frequent surface condition (2,738 crashes), a combined 1,819 crashes occurred on wet, snow, ice, or slush-covered roads.

Weather

Clear2,468 (53.4%)
Cloudy817 (17.7%)
Rain624 (13.5%)
Snow521 (11.3%)
Freezing rain/drizzle99 (2.1%)
Blowing Snow42 (0.9%)
Fog, smoke, smog24 (0.5%)
Severe Winds22 (0.5%)
Sleet, hail8 (0.2%)
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Weather condition at time of crash

Lighting

Daylight2,491 (53.7%)
Dark - roadway lighted1,066 (23.0%)
Dark - roadway not lighted755 (16.3%)
Dusk201 (4.3%)
Dawn96 (2.1%)
Dark - unknown roadway lighting32 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Lighting condition field

Road Surface

Dry2,738 (59.0%)
Wet1,015 (21.9%)
Snow484 (10.4%)
Ice/frost251 (5.4%)
Slush69 (1.5%)
Gravel67 (1.4%)
Mud, dirt9 (0.2%)
Other (explain in narrative)5 (0.1%)
Water (standing or moving)2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Road surface condition field

Vehicles & Demographics

Among the 11,298 people involved in crashes, the 26-34 age group was the most represented, with 1,925 individuals. Analysis of the 9,428 vehicles involved shows that Chevrolet (1,912 vehicles), Ford (1,570 vehicles), and Dodge (714 vehicles) were the most frequent makes recorded in crash reports. Toyota (641 vehicles) and Honda (437 vehicles) were also commonly involved.

Top Vehicle Makes (9,428 vehicles)

1
FORD1,570 (16.7%)
2
CHEV1,063 (11.3%)
3
CHEVROLET849 (9%)
4
DODG400 (4.2%)
5
TOYT367 (3.9%)
6
DODGE314 (3.3%)
7
JEEP284 (3%)
8
TOYOTA274 (2.9%)
9
GMC267 (2.8%)
10
HOND248 (2.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Vehicle unit records

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

Sex Distribution (8,333 persons with recorded sex)

Male4,648 (55.8%)
Female3,685 (44.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Person-level records linked to crash events

Major Cause

According to the Iowa DOT's major cause coding, collisions with an animal were the leading factor, attributed to 1,524 crashes. The next most common causes were driver behaviors, including 'Followed too close' (521 crashes), 'Driving too fast for conditions' (397 crashes), and 'Lost Control' (309 crashes). Failure to yield when making a left turn was also a significant factor, cited in 240 incidents.

Major Cause

1
Animal1,524 (27.6%)
2
Followed too close521 (9.4%)
3
Driving too fast for conditions397 (7.2%)
4
Ran off road - left332 (6%)
5
Lost Control309 (5.6%)
6
Other (explain in narrative): Other287 (5.2%)
7
FTYROW: Making left turn240 (4.4%)
8
FTYROW: From stop sign228 (4.1%)
9
Ran off road - straight199 (3.6%)

Showing top 9 of 49 reported. 40 additional (1,477 total) not shown: Ran Traffic Signal, Ran Stop Sign, Made improper turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Other interior distraction, Improper or erratic lane changing, Other (explain in narrative): No improper action, FTYROW: From driveway, Driver Distraction: Exterior distraction, Driver Distraction: Inattentive/lost in thought, FTYROW: Other (explain in narrative), Swerving/Evasive Action, Improper Backing, Exceeded authorized speed, FTYROW: At uncontrolled intersection, Ran off road - right, Driver Distraction: Reaching for object(s)/fallen object(s), Failed to keep in proper lane, Passing: Other passing (explain in narrative), FTYROW: From yield sign, Other (explain in narrative): Vision obstructed, Driver Distraction: Adjusting devices (radio, climate), Driver Distraction: Passenger, Crossed centerline (undivided), FTYROW: To pedestrian, Traveling wrong way or on wrong side of road, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Talking on a hand-held device, FTYROW: Making right turn on red signal, Passing: Through/around barrier, FTYROW: From parked position, Driver Distraction: Other electronic device activity, Illegally Parked/Unattended, Aggressive driving/road rage, Over correcting/over steering, Failed to yield to emergency vehicle, Equipment failure, Cargo/equipment loss or shift, Other (explain in narrative): Improper operation, Disregarded RR Signal.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

First Harmful Event

The most common first harmful event was a 'Collision with: Vehicle in traffic,' which occurred in 2,831 crashes. The second-leading event was a 'Collision with: Animal,' accounting for 1,504 incidents. Single-vehicle events were also prominent, including 'Overturn/rollover' (208 crashes) and collisions with fixed objects like a 'Ditch' (206 crashes) or a 'Utility pole/light support' (108 crashes).

First Harmful Event

1
Collision with: Vehicle in traffic2,831 (48.7%)
2
Collision with: Animal1,504 (25.9%)
3
Collision with: Parked motor vehicle220 (3.8%)
4
Non-collision events: Overturn/rollover208 (3.6%)
5
Collision with fixed object: Ditch206 (3.5%)
6
Collision with fixed object: Utility pole/light support108 (1.9%)
7
Collision with: Non-motorist (see non-motorist section - NOT a unit)66 (1.1%)
8
Collision with fixed object: Cable barrier58 (1%)
9
Collision with fixed object: Curb/island/raised median51 (0.9%)

Showing top 9 of 46 reported. 37 additional (564 total) not shown: Miscellaneous events: Hit and run, Other (explain in narrative), Collision with: Re-entering roadway, Collision with fixed object: Guardrail - face, Collision with fixed object: Tree, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Traffic sign support, Collision with: Struck/struck by object/cargo/person from other vehicle, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Fence, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Embankment, Non-collision events: Jackknife, Collision with fixed object: Fire hydrant, Non-collision events: Vehicle went airborne, Collision with fixed object: Building, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Wall, Collision with fixed object: Mailbox, Collision with: Thrown or falling object, Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Traffic signal support, Collision with: Railway vehicle/train, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Ground, Collision with fixed object: Snow bank, Collision with fixed object: Bridge overhead structure, Collision with: Work zone maintenance equipment, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Guardrail - end, Miscellaneous events: Fire/explosion, Miscellaneous events: Vehicle out of gear/rolled, Miscellaneous events: Immersion.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Roadway Junction / Feature

Crashes were most frequently located away from intersections, with 2,559 incidents occurring at 'Non-junction' locations. Four-way intersections were the most common type of junction for crashes, accounting for 1,174 incidents. T-intersections were the site of another 322 crashes, indicating that intersections collectively represent a significant point of conflict.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature2,559 (55.1%)
2
Intersection: Four-way intersection1,174 (25.3%)
3
Intersection: T-intersection322 (6.9%)
4
Non-intersection: Driveway access (related, not in)171 (3.7%)
5
Intersection: Other intersection (explain in narrative)67 (1.4%)
6
Non-intersection: Driveway access (within)54 (1.2%)
7
Non-intersection: Other non-intersection (explain in narrative)44 (0.9%)
8
Intersection: Intersection with ramp42 (0.9%)
9
Interchange-related: On-ramp merge area39 (0.8%)

Showing top 9 of 24 reported. 15 additional (175 total) not shown: Interchange-related: Off-ramp, diverge area, Interchange-related: Off-ramp, Non-intersection: Crossover-related, Non-intersection: Alley, Non-intersection: Railroad grade crossing, Interchange-related: On-ramp, Intersection: Y-intersection, Interchange-related: Mainline, between ramps, Intersection: Five points or more, Intersection: L-intersection, Intersection: Roundabout, Interchange-related: Other interchange (explain in narrative), Non-intersection: Bike lanes, Intersection: Shared use path or trail, Intersection: Traffic circle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 4,538 vehicles. Sport utility vehicles (1,991 vehicles) and four-tire light trucks or pickups (1,540 vehicles) were the next most frequent. Commercial vehicles were also represented, with 255 tractor/semi-trailers involved in incidents, while 37 motorcycles were recorded in crashes.

Vehicle Type

"Other" combines 21 smaller categories (211 records): Cargo/panel van (44), Motorcycle (37), Farm tractor (17), School bus (seats > 15) (16), Passenger van (seats 9-15) (14), Maintenance/construction vehicle (12), Other bus (seats > 15) (12), Truck/trailer (12), Motor home/recreational vehicle (7), Truck tractor (bobtail) (6), Tractor/doubles (6), Farm equipment (explain in narrative) (5), Other light truck (<=10000 lbs) (4), Train (4), All-terrain vehicle (ATV) (3), Other (explain in narrative) (3), Snowmobile (2), Other small bus (seats 9-15) (2), Other heavy truck (> 10000 lbs) (cannot classify) (2), Moped (2), Small school bus (seats 9-15) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Vehicle unit records

Traffic Control Device

The majority of crashes occurred where no traffic controls were present, with this category accounting for 5,152 incidents. Where controls were in place, traffic signals were the most common, associated with 1,888 crashes. Stop signs were the next most frequent traffic control device, present at the scene of 818 crashes.

Traffic Control Device

"Other" combines 7 smaller categories (67 records): Work zone sign (23), Warning sign (16), Railway crossing device (14), Inoperative (not functioning properly) (6), Traffic director (person) (5), School zone signs (2), Traffic sign missing (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · 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 2,316 vehicles. The rear of the vehicle was the second most frequent point of damage, with 1,133 instances, suggesting a high prevalence of rear-end collisions. Damage to the driver-side (456 middle, 409 front) and passenger-side (370 middle, 341 front) indicate a significant number of angle or sideswipe collisions.

Most Damaged Area

"Other" combines 10 smaller categories (1,709 records): Passenger side - front (341), Driver side - rear (306), Rear - driver side corner (258), Passenger side - rear (245), Top (179), Rear - passenger side corner (174), Other (explain in narrative) (109), Non-collision/no damage (54), Undercarriage (39), Cargo loss (4).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Vehicle unit records

Impairment (Alcohol / Drugs)

A total of 149 crashes were flagged for driver impairment, representing 2.5% of all crashes. Of these, alcohol was the sole factor in 138 cases, drugs were the factor in 8 cases, and a combination of alcohol and drugs was noted in 3 cases. These figures should be considered a minimum, as impairment is often difficult to determine at the scene.

Crashes by County

Crash distribution was heavily concentrated in Iowa's most populous counties. Polk County recorded the highest number of incidents with 922 crashes, followed by Scott County with 387 and Linn County with 317. Together, these three counties accounted for 1,626 crashes, representing 27.8% of the statewide total for the month.

Crashes by County

1
POLK922 (18%)
2
SCOTT387 (7.5%)
3
LINN317 (6.2%)
4
WOODBURY266 (5.2%)
5
BLACK HAWK262 (5.1%)
6
JOHNSON229 (4.5%)
7
POTTAWATTAMIE207 (4%)
8
STORY183 (3.6%)
9
DUBUQUE167 (3.3%)

Showing top 9 of 50 reported. 41 additional (2,190 total) not shown: CERRO GORDO, DALLAS, LEE, WARREN, CLINTON, MARSHALL, WEBSTER, DES MOINES, JASPER, BREMER, MARION, CEDAR, SIOUX, BUENA VISTA, BOONE, IOWA, MUSCATINE, WINNESHIEK, WAPELLO, BUCHANAN, HENRY, CLAYTON, TAMA, PLYMOUTH, DELAWARE, HAMILTON, HARRISON, GRUNDY, JONES, FLOYD, POWESHIEK, JEFFERSON, HARDIN, CLAY, FAYETTE, CASS, MAHASKA, ADAIR, BENTON, WASHINGTON, LOUISA.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Crashes by City

Among municipalities, Des Moines experienced the highest volume of crashes with 494 incidents. Davenport followed with 298 crashes, and Sioux City recorded 218 crashes. These figures highlight that a substantial portion of traffic incidents occur within the state's primary urban areas, as many rural crashes happen outside of any city's jurisdiction.

Crashes by City

1
DES MOINES494 (16.1%)
2
DAVENPORT298 (9.7%)
3
SIOUX CITY218 (7.1%)
4
CEDAR RAPIDS170 (5.5%)
5
WATERLOO158 (5.1%)
6
WEST DES MOINES134 (4.4%)
7
COUNCIL BLUFFS125 (4.1%)
8
DUBUQUE124 (4%)
9
IOWA CITY122 (4%)

Showing top 9 of 50 reported. 41 additional (1,232 total) not shown: AMES, ANKENY, CEDAR FALLS, URBANDALE, FORT DODGE, MASON CITY, BURLINGTON, CORALVILLE, CLINTON, BETTENDORF, MARSHALLTOWN, MARION, CLIVE, STORM LAKE, ALTOONA, OTTUMWA, MUSCATINE, FORT MADISON, NEWTON, OSKALOOSA, INDIANOLA, BOONE, CHARLES CITY, SPENCER, CLEAR LAKE, HIAWATHA, GRIMES, JOHNSTON, CARROLL, KEOKUK, WAUKEE, WAVERLY, PELLA, ALGONA, NEVADA, FAIRFIELD, DENISON, PLEASANT HILL, CENTERVILLE, MONTICELLO, GRINNELL.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 5,621, occurred on paved roadways. However, 210 crashes were recorded on unpaved surfaces such as gravel or dirt. These unpaved road crashes represent 3.6% of incidents where the surface type was specified, reflecting the risk present on Iowa's extensive secondary road network.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Roadway Contributing Factor

In a minority of crashes, a roadway factor was identified as a contributor. The most cited factor was 'Surface condition (e.g.wet, icy),' noted in 786 crashes. Work zones were a contributing factor in 54 crashes, while debris in the roadway was cited in 11 incidents.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)786 (84.7%)
2
Work Zone (roadway-related)54 (5.8%)
3
Slippery, loose or worn surface32 (3.4%)
4
Traffic backup, prior crash13 (1.4%)
5
Debris11 (1.2%)
6
Ruts/holes/bumps8 (0.9%)
7
Traffic backup, regular congestion7 (0.8%)
8
Obstruction in roadway6 (0.6%)
9
Disabled vehicle3 (0.3%)

Showing top 9 of 12 reported. 3 additional (8 total) not shown: Shoulders (none, low, soft, high), Traffic backup, prior non-recurring incident, Non-highway work.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Driver Condition

While most drivers were recorded as 'Apparently normal,' several other conditions were noted by officers. 'Under the influence of alcohol' was the most common condition, recorded for 176 drivers. Other notable conditions included 'Asleep/fatigued' for 58 drivers and 'Emotional' for 37 drivers, suggesting that driver state plays a role in a subset of crashes.

Driver Condition

1
Under the influence of alcohol176 (53.5%)
2
Asleep/fatigued58 (17.6%)
3
Emotional (e.g. depressed, angry)37 (11.2%)
4
Medical condition (seizure, reaction)25 (7.6%)
5
Under the influence of drugs/meds18 (5.5%)
6
Illness/fainted4 (1.2%)
7
Physical impairment3 (0.9%)
8
Paraplegic/wheelchair restricted3 (0.9%)
9
Visually impaired3 (0.9%)

Showing top 9 of 10 reported. 1 additional (2 total) not shown: Walks with a cane/crutches.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Crashes by Iowa DOT District

Crashes were most prevalent in the Iowa DOT's District 1, which includes the Des Moines metro area, with 1,607 incidents. District 6, covering eastern Iowa including Cedar Rapids and Davenport, recorded the second-highest number with 1,474 crashes. These two districts combined accounted for over half (52.6%) of all crashes in the state.

Crashes by Iowa DOT District

1
District 11,607 (27.4%)
2
District 61,474 (25.2%)
3
District 2781 (13.3%)
4
District 5733 (12.5%)
5
District 3705 (12%)
6
District 4557 (9.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Property Damage

The most common estimated property damage cost per crash fell within the '$1,500 - $7,500' range, which applied to 4,389 incidents. A smaller but significant number of crashes resulted in higher costs, with 1,222 incidents causing damage between $7,500 and $25,000. Crashes with severe damage estimated at over $25,000 accounted for 110 events.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Manner of Collision

The most frequent type of crash was a 'Non-collision (single vehicle)' event, such as running off the road or an overturn, accounting for 2,558 incidents (43.7%). Among multi-vehicle crashes, rear-end collisions were the most common, with 1,252 incidents (21.4%). Broadside collisions were also frequent, occurring in 771 crashes (13.2%).

Manner of Collision

"Other" combines 3 smaller categories (195 records): Other (explain in narrative) (93), Rear to side (90), Rear to rear (12).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was 'Movement essentially straight,' recorded for 5,369 vehicles. Other frequent actions preceding a collision included 'Turning left' (802 vehicles) and 'Slowing/stopping (deceleration)' (488 vehicles). These actions highlight common driving maneuvers that result in conflicts.

Pre-Crash Driver Action

1
Movement essentially straight5,369 (63%)
2
Turning left802 (9.4%)
3
Slowing/stopping (deceleration)488 (5.7%)
4
Stopped in traffic449 (5.3%)
5
Legally Parked367 (4.3%)
6
Turning right323 (3.8%)
7
Changing lanes154 (1.8%)
8
Backing152 (1.8%)
9
Other (explain in narrative)119 (1.4%)

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

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Vehicle unit records

Pedestrian/Cyclist Action

For the 46 pedestrians involved in crashes where an action was recorded, the most common behavior was 'Entering or crossing roadway,' which was noted in 44 instances. This indicates that pedestrians are most vulnerable while actively navigating traffic lanes. Another 8 incidents involved pedestrians going to or from school.

Pedestrian/Cyclist Action

1
Entering or crossing roadway44 (61.1%)
2
Going to/coming from school8 (11.1%)
3
Other5 (6.9%)
4
Movement: Along roadway with traffic5 (6.9%)
5
Approaching or leaving vehicle2 (2.8%)
6
Entering/exiting vehicle2 (2.8%)
7
Movement: On sidewalk2 (2.8%)
8
Movement: On shoulder/median1 (1.4%)
9
Waiting to cross roadway1 (1.4%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Movement: Along roadway against traffic, Movement: Along roadway (direction unknown).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Non-motorist records linked to crash events

Person Type

Of the 11,298 individuals involved in crashes, the vast majority were drivers, accounting for 10,829 persons. Passengers made up the next largest group with 396 individuals. Vulnerable road users were also involved, including 46 pedestrians and 23 bicyclists.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Person Injury Severity

Among all persons involved in crashes, 23 suffered fatal injuries and 117 sustained serious injuries. An additional 526 people had minor injuries and 1,071 had possible injuries. The data shows that while a minority of individuals are injured in any given crash, the potential for severe outcomes is present.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Crash-level records

Occupant Safety Equipment

Based on available data, 1,222 individuals were recorded as using a shoulder and lap belt. In contrast, 109 people were documented as using no safety equipment at the time of the crash. Additionally, 16 children were secured in a forward-facing child safety seat.

Occupant Safety Equipment

"Other" combines 3 smaller categories (5 records): Other (2), Helmet (other) (2), Booster seat (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle crashes were the most common scenario, accounting for 2,957 incidents. Single-vehicle crashes were also very frequent, with 2,615 incidents recorded. Crashes involving three or more vehicles were less common, with 249 three-vehicle crashes and 30 four-vehicle crashes reported.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-11-01 to 2015-11-30 · 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: 2015-11-01 through 2015-11-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-11-01 through 2015-11-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,857
  • Total persons involved: 11,298
  • Total vehicles involved: 9,428

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: November 2015." Published September 9, 2026. Reporting period: 2015-11-01 to 2015-11-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/november-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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