Yearly Traffic Safety Analysis

2,358 CRASHES IN
IOWA, IA
2015

In 2015, Woodbury County recorded 2,358 total traffic crashes, which resulted in 13 fatalities and 820 injuries. These incidents involved 4,335 vehicles and 5,261 individuals. A notable finding from the data is the prevalence of multi-vehicle collisions, with rear-end crashes being the most common type, accounting for 26.3% of all incidents, and following too closely cited as the leading contributing factor in 11.5% of crashes.

2,358

Total Crash Events

13

Persons Killed

820

Persons Injured

12

Fatal Crash Events

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

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

Vulnerable Road User Casualties

In 2015, motorists constituted the largest group of casualties, with 12 fatalities and 762 injuries. Vulnerable road users also suffered significant harm. One pedestrian was killed and 26 were injured in crashes. Additionally, while no cyclists were killed, 28 sustained injuries.

1

Pedestrians Killed

0

Cyclists Killed

12

Motorists Killed

0

Other Killed

26

Pedestrians Injured

28

Cyclists Injured

762

Motorists Injured

4

Other Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 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 Woodbury County show a distinct peak during the work week, with Friday being the most frequent day for incidents, recording 411 crashes. The afternoon commute represents the time of highest risk, as the 4 p.m. hour had the most crashes with 207 incidents. While the majority of collisions occurred during daylight hours (1,585 crashes), a significant number, 515 crashes, happened in dark conditions, both on lighted and unlighted roadways.

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

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

Crash Severity Breakdown

Of the 2,358 crashes reported, 1,628 (69%) resulted in no injuries, involving only property damage. The remaining 31% of crashes involved some level of injury, including 486 with possible injuries, 193 with minor injuries, and 39 with serious injuries. Twelve of these crashes were fatal. The 12 fatal crashes resulted in a total of 13 fatalities, indicating that at least one incident involved multiple deaths.

Severity is per crash event (most severe injury). 12 fatal crash events resulted in 13 persons killed.

Outcome by Severity (Crash Events)

Fatal12fatal crashes0.5%
Serious Injury39serious injury crashes1.7%
Minor Injury193minor injury crashes8.2%
Possible Injury486possible injury crashes20.6%
No Injury1,628no injury crashes69%

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Analysis of contributing factors indicates that driver error is a primary cause of crashes. The most frequently cited factor was 'Followed too close,' attributed to 271 crashes, or 11.5% of the total. Failure to yield the right-of-way from a stop sign was the second-leading cause, noted in 204 incidents (8.7%), followed by running a traffic signal, which contributed to 149 crashes (6.3%).

Officer-Reported Primary Contributing Cause

Followed too close271 (11.5%)
FTYROW: From stop sign204 (8.7%)
Other (explain in narrative): Other162 (6.9%)
Ran Traffic Signal149 (6.3%)
Ran off road - left147 (6.2%)
Driving too fast for conditions140 (5.9%)
Animal135 (5.7%)
Lost Control115 (4.9%)
FTYROW: Making left turn104 (4.4%)
Ran Stop Sign85 (3.6%)

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

Road & Environmental Conditions

The majority of traffic crashes in 2015 occurred in ideal driving conditions. Data shows that 67.2% of crashes (1,585) happened in daylight, 64.6% (1,524) on dry road surfaces, and 58% (1,368) in clear weather. However, adverse conditions were also present in a notable number of incidents, with 352 crashes occurring on wet roads and 172 during rain. Another 144 crashes took place in snowy conditions.

Weather

Clear1,368 (61.6%)
Cloudy485 (21.9%)
Rain172 (7.8%)
Snow144 (6.5%)
Freezing rain/drizzle27 (1.2%)
Blowing Snow16 (0.7%)
Severe Winds3 (0.1%)
Fog, smoke, smog3 (0.1%)
Sleet, hail1 (0.0%)

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

Lighting

Daylight1,585 (71.1%)
Dark - roadway lighted389 (17.4%)
Dark - roadway not lighted121 (5.4%)
Dusk67 (3.0%)
Dawn63 (2.8%)
Dark - unknown roadway lighting5 (0.2%)

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

Road Surface

Dry1,524 (68.3%)
Wet352 (15.8%)
Snow175 (7.8%)
Ice/frost88 (3.9%)
Slush55 (2.5%)
Gravel19 (0.9%)
Mud, dirt12 (0.5%)
Water (standing or moving)3 (0.1%)
Other (explain in narrative)2 (0.1%)

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

Vehicles & Demographics

Among the 5,261 people involved in crashes, the 26-34 age group was the most represented, with 852 individuals. Analysis of the 4,335 vehicles involved shows that Chevrolet (896 vehicles), Ford (689 vehicles), and Dodge (341 vehicles) were the most frequent makes in collisions. Toyota (238 vehicles) and Honda (217 vehicles) were also commonly involved.

Top Vehicle Makes (4,335 vehicles)

1
FORD689 (15.9%)
2
CHEV482 (11.1%)
3
CHEVROLET414 (9.6%)
4
DODGE172 (4%)
5
GMC171 (3.9%)
6
DODG169 (3.9%)
7
TOYT140 (3.2%)
8
JEEP129 (3%)
9
NR127 (2.9%)
10
HOND114 (2.6%)

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

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

Sex Distribution (3,526 persons with recorded sex)

Male1,980 (56.2%)
Female1,546 (43.8%)

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

Major Cause

The leading major cause attributed to crashes was 'Followed too close,' cited in 271 incidents. Failure to yield the right-of-way from a stop sign was the second most common cause with 204 crashes. Other significant factors included running a traffic signal (149 crashes), running off the road to the left (147 crashes), and driving too fast for conditions (140 crashes).

Major Cause

1
Followed too close271 (12.4%)
2
FTYROW: From stop sign204 (9.3%)
3
Other (explain in narrative): Other162 (7.4%)
4
Ran Traffic Signal149 (6.8%)
5
Ran off road - left147 (6.7%)
6
Driving too fast for conditions140 (6.4%)
7
Animal135 (6.2%)
8
Lost Control115 (5.3%)
9
FTYROW: Making left turn104 (4.8%)

Showing top 9 of 49 reported. 40 additional (755 total) not shown: Ran Stop Sign, Ran off road - straight, Made improper turn, Improper or erratic lane changing, Operating vehicle in an reckless, erratic, careless, negligent manner, FTYROW: From driveway, Driver Distraction: Other interior distraction, FTYROW: Other (explain in narrative), Driver Distraction: Exterior distraction, Other (explain in narrative): No improper action, Exceeded authorized speed, Improper Backing, Swerving/Evasive Action, Failed to keep in proper lane, FTYROW: From parked position, Driver Distraction: Reaching for object(s)/fallen object(s), Driver Distraction: Inattentive/lost in thought, Ran off road - right, Passing: Other passing (explain in narrative), FTYROW: To pedestrian, FTYROW: At uncontrolled intersection, Traveling wrong way or on wrong side of road, Driver Distraction: Manual operation of an electronic communication device, Failed to yield to emergency vehicle, FTYROW: From yield sign, Crossed centerline (undivided), Driver Distraction: Adjusting devices (radio, climate), Passing: On wrong side, Operator inexperience, Passing: With insufficient distance/inadequate visibility, Driver Distraction: Unrestrained animal, Other (explain in narrative): Improper operation, Driver Distraction: Passenger, Other (explain in narrative): Vision obstructed, Passing: Through/around barrier, Illegally Parked/Unattended, Cargo/equipment loss or shift, Over correcting/over steering, Aggressive driving/road rage, FTYROW: Making right turn on red signal.

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

First Harmful Event

The most common first harmful event was a 'Collision with: Vehicle in traffic,' which accounted for 1,534 crashes, representing 65% of all incidents. Single-vehicle crashes frequently involved collisions with objects off the roadway. Notably, 133 crashes involved an animal, 53 involved a ditch, and 52 were overturns or rollovers.

First Harmful Event

1
Collision with: Vehicle in traffic1,534 (65.2%)
2
Collision with: Parked motor vehicle223 (9.5%)
3
Collision with: Animal133 (5.6%)
4
Collision with: Non-motorist (see non-motorist section - NOT a unit)56 (2.4%)
5
Collision with fixed object: Ditch53 (2.3%)
6
Non-collision events: Overturn/rollover52 (2.2%)
7
Collision with fixed object: Utility pole/light support37 (1.6%)
8
Collision with fixed object: Curb/island/raised median34 (1.4%)
9
Other (explain in narrative)23 (1%)

Showing top 9 of 45 reported. 36 additional (209 total) not shown: Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Tree, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Guardrail - face, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fence, Collision with fixed object: Embankment, Collision with: Other non-fixed object (explain in narrative), Miscellaneous events: Eluding law enforcement, Collision with fixed object: Traffic sign support, Collision with fixed object: Building, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Wall, Collision with fixed object: Fire hydrant, Collision with fixed object: Traffic signal support, Collision with: Re-entering roadway, Collision with fixed object: Ground, Collision with fixed object: Bridge pier or support, Miscellaneous events: Hit and run, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with: Thrown or falling object, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Bridge overhead structure, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with: Work zone maintenance equipment, Non-collision events: Fell/jumped from vehicle, Non-collision events: Vehicle went airborne, Collision with fixed object: Mailbox, Collision with fixed object: Cable barrier, Collision with: Railway vehicle/train, Collision with fixed object: Guardrail - end, Collision with fixed object: Culvert/pipe opening, Miscellaneous events: Immersion, Collision with fixed object: Snow bank.

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

Roadway Junction / Feature

The road network location of crashes was split between intersections and non-intersection segments. Approximately 49.7% of crashes (1,171) occurred at or were related to an intersection, with four-way intersections being the most common type (883 crashes). Non-junction roadway segments accounted for 845 crashes, or 35.8% of the total, while another 72 were related to driveway access.

Roadway Junction / Feature

1
Intersection: Four-way intersection883 (39.5%)
2
Non-intersection: Non-junction/no special feature845 (37.8%)
3
Intersection: T-intersection202 (9%)
4
Non-intersection: Driveway access (related, not in)72 (3.2%)
5
Intersection: Intersection with ramp59 (2.6%)
6
Interchange-related: On-ramp merge area31 (1.4%)
7
Intersection: Other intersection (explain in narrative)21 (0.9%)
8
Non-intersection: Other non-intersection (explain in narrative)20 (0.9%)
9
Interchange-related: Off-ramp, diverge area18 (0.8%)

Showing top 9 of 21 reported. 12 additional (87 total) not shown: Non-intersection: Driveway access (within), Non-intersection: Alley, Interchange-related: Off-ramp, Interchange-related: On-ramp, Non-intersection: Railroad grade crossing, Interchange-related: Mainline, between ramps, Non-intersection: Crossover-related, Intersection: L-intersection, Intersection: Y-intersection, Non-intersection: Bike lanes, Intersection: Traffic circle, Interchange-related: Other interchange (explain in narrative).

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

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 2,027 of the 4,335 vehicles. Sport utility vehicles were the second most frequent type with 1,002 vehicles, followed by four-tire light trucks and pickups with 729 vehicles. Commercial vehicles were also involved, including 83 tractor-trailers, while 33 motorcycles were recorded in crashes.

Vehicle Type

"Other" combines 17 smaller categories (88 records): Cargo/panel van (21), Single-unit truck (>= 3 axles) (19), School bus (seats > 15) (9), Other bus (seats > 15) (9), Truck tractor (bobtail) (7), Truck/trailer (4), Passenger van (seats 9-15) (4), Maintenance/construction vehicle (3), Other light truck (<=10000 lbs) (2), Farm equipment (explain in narrative) (2), Motor home/recreational vehicle (2), 3-wheeled, enclosed (1), Other (explain in narrative) (1), Train (1), Moped (1), Farm tractor (1), All-terrain vehicle (ATV) (1).

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

Traffic Control Device

Data on traffic controls present for the 4,335 vehicles involved shows that a majority, 2,312 vehicles (53.3%), were in areas with no traffic controls present. For vehicles where controls were a factor, traffic signals were the most common, governing 1,115 vehicles. Stop signs were the next most frequent control type, affecting 555 vehicles involved in crashes.

Traffic Control Device

"Other" combines 5 smaller categories (38 records): Warning sign (13), No Passing Zone (marked) (9), Railway crossing device (8), Inoperative (not functioning properly) (4), Traffic director (person) (4).

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

Most Damaged Area

Analysis of vehicle damage indicates that frontal impacts are the most common. The front was the most damaged area for 1,135 vehicles, while the rear was the primary point of damage for 563 vehicles, consistent with the high number of rear-end collisions. Side impacts were also prevalent, with the driver's side middle (252 vehicles) and passenger's side middle (202 vehicles) being common damage locations.

Most Damaged Area

"Other" combines 9 smaller categories (917 records): Passenger side - middle (202), Driver side - rear (168), Rear - driver side corner (163), Passenger side - rear (145), Rear - passenger side corner (86), Other (explain in narrative) (72), Top (46), Non-collision/no damage (18), Undercarriage (17).

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

Impairment (Alcohol / Drugs)

Impairment was suspected in 84 crashes, representing 3.6% of all incidents in 2015. Among the 88 instances of impairment recorded at the vehicle level, alcohol was the primary factor in 83 cases. Drugs were suspected in 3 cases, and a combination of alcohol and drugs was noted in 2 instances.

Crashes by City

The distribution of crashes across municipalities shows a heavy concentration in Sioux City, which accounted for 2,027 of the county's 2,358 total crashes. Far smaller volumes were recorded in other communities, with Sergeant Bluff seeing 64 crashes. The towns of Moville and Sloan each recorded 14 crashes.

Crashes by City

1
SIOUX CITY2,027 (92.5%)
2
SERGEANT BLUFF64 (2.9%)
3
MOVILLE14 (0.6%)
4
SLOAN14 (0.6%)
5
CORRECTIONVILLE12 (0.5%)
6
SALIX9 (0.4%)
7
SMITHLAND8 (0.4%)
8
ANTHON8 (0.4%)
9
HORNICK7 (0.3%)

Showing top 9 of 15 reported. 6 additional (28 total) not shown: LAWTON, BRONSON, PIERSON, DANBURY, CUSHING, OTO.

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

Paved vs Unpaved Road

The vast majority of crashes occurred on paved roadways, which accounted for 2,287 incidents. Crashes on unpaved surfaces like gravel or dirt were less common, with 56 such incidents reported. This represents approximately 2.4% of the crashes where road surface type was specified.

Paved vs Unpaved Road

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

Roadway Contributing Factor

While most crashes did not have a roadway factor cited, 'Surface condition (e.g. wet, icy)' was the most noted contributor, playing a role in 245 crashes. Work zones were the second most common roadway factor, contributing to 109 crashes. Other less frequent factors included slippery or worn surfaces (13 crashes) and traffic backups (7 crashes).

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)245 (61.7%)
2
Work Zone (roadway-related)109 (27.5%)
3
Slippery, loose or worn surface13 (3.3%)
4
Traffic backup, regular congestion7 (1.8%)
5
Ruts/holes/bumps4 (1%)
6
Shoulders (none, low, soft, high)3 (0.8%)
7
Debris3 (0.8%)
8
Non-highway work3 (0.8%)
9
Traffic backup, prior crash3 (0.8%)

Showing top 9 of 13 reported. 4 additional (7 total) not shown: Obstruction in roadway, Traffic backup, prior non-recurring incident, Traffic control obscured, Disabled vehicle.

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, being under the influence of alcohol was the most cited, with 116 instances. Driver fatigue or falling asleep was noted for 16 drivers, and a medical condition such as a seizure was also recorded for 16 drivers. An emotional state, such as anger or depression, was documented for 14 drivers.

Driver Condition

1
Under the influence of alcohol116 (64.1%)
2
Medical condition (seizure, reaction)16 (8.8%)
3
Asleep/fatigued16 (8.8%)
4
Emotional (e.g. depressed, angry)14 (7.7%)
5
Illness/fainted6 (3.3%)
6
Under the influence of drugs/meds5 (2.8%)
7
Physical impairment3 (1.7%)
8
Walks with a cane/crutches2 (1.1%)
9
Paraplegic/wheelchair restricted2 (1.1%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Hearing impaired/deaf.

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

Property Damage

The estimated cost of property damage was most frequently in the '$1,500 - $7,500' range, which applied to 1,779 crashes, or 75.4% of the total. A smaller number of crashes resulted in more severe financial loss, with 423 incidents causing damage between $7,500 and $25,000. High-damage crashes, with costs exceeding $25,000, were relatively rare, accounting for 35 incidents (1.5%).

Property Damage

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

Manner of Collision

Rear-end collisions were the most frequent type of crash, accounting for 620 incidents or 26.3% of the total. Broadside, or front-to-side, collisions were also very common, with 541 crashes (22.9%). Single-vehicle incidents, classified as non-collisions, made up 21.7% of the total with 511 crashes.

Manner of Collision

"Other" combines 3 smaller categories (94 records): Sideswipe, opposite direction (49), Other (explain in narrative) (39), Rear to rear (6).

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

Pre-Crash Driver Action

The majority of vehicles involved in crashes were engaged in normal driving maneuvers immediately prior to the incident. Of the 4,335 vehicles, 2,585 were moving straight ahead. Turning left was the second most common pre-crash action, recorded for 397 vehicles, followed by vehicles that were legally parked (296 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight2,585 (61.8%)
2
Turning left397 (9.5%)
3
Legally Parked296 (7.1%)
4
Slowing/stopping (deceleration)200 (4.8%)
5
Stopped in traffic173 (4.1%)
6
Turning right152 (3.6%)
7
Backing90 (2.2%)
8
Other (explain in narrative)78 (1.9%)
9
Changing lanes75 (1.8%)

Showing top 9 of 18 reported. 9 additional (138 total) not shown: Negotiating a curve, Entering traffic lane (merging), Overtaking/passing, Illegally Parked/Unattended, Making U-turn, Leaving traffic lane, Accelerating in road, Leaving a parked position, Starting in road.

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

Pedestrian/Cyclist Action

For the 59 non-motorists involved in crashes, the most common action at the time of the collision was entering or crossing the roadway, which was reported for 40 individuals. All other specified actions, such as being on the sidewalk or approaching a vehicle, were reported in much smaller numbers.

Pedestrian/Cyclist Action

1
Entering or crossing roadway40 (67.8%)
2
Other7 (11.9%)
3
Movement: On sidewalk3 (5.1%)
4
Approaching or leaving vehicle2 (3.4%)
5
Movement: Along roadway against traffic2 (3.4%)
6
Movement: Along roadway with traffic2 (3.4%)
7
Going to/coming from school1 (1.7%)
8
Entering/exiting vehicle1 (1.7%)
9
Working in trafficway1 (1.7%)

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

Person Type

Of the 5,261 people involved in crashes, the vast majority were drivers, accounting for 5,007 individuals (95.2%). Passengers made up the next largest group with 195 individuals. The data also includes 28 bicyclists and 27 pedestrians who were involved in collisions.

Person Type

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

Person Injury Severity

Among all persons involved in crashes where an injury status was recorded, 13 suffered fatal injuries and 44 sustained serious injuries. A larger number experienced less severe outcomes, with 229 people receiving minor injuries and 547 people having possible injuries. A total of 93 individuals were confirmed to have no injuries.

Person Injury Severity

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

Occupant Safety Equipment

Among the 694 occupants for whom safety equipment use was documented, 611 were reported to have used a shoulder and lap belt. However, 47 individuals were recorded as using no restraint at all. Child safety seats were used by 13 occupants, including 10 in forward-facing seats.

Occupant Safety Equipment

"Other" combines 2 smaller categories (3 records): Other (2), Child safety seat (rear-facing) (1).

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

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 1,665 crashes, or 70.6% of all incidents. Single-vehicle crashes were the next most frequent type, with 550 incidents, making up 23.3% of the total. Multi-vehicle pile-ups involving three or more vehicles were less common, with 120 crashes involving three vehicles and 20 involving four.

Vehicles Per Crash

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

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,358
  • Total persons involved: 5,261
  • Total vehicles involved: 4,335

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