Yearly Traffic Safety Analysis

1,931 CRASHES IN
IOWA, IA
2015

In 2015, Dubuque County recorded 1,931 traffic crashes, resulting in 3 fatalities and 592 injuries. A notable finding from the data is that running off the road was a primary contributing factor, with 440 crashes (22.8%) attributed to a vehicle running off the road to the left.

1,931

Total Crash Events

3

Persons Killed

592

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Motor vehicle occupants represented the largest group of casualties, with 2 motorists killed and 566 injured. One pedestrian was killed and 15 others were injured in collisions. While no bicyclists were killed, 10 sustained injuries during the year.

1

Pedestrians Killed

0

Cyclists Killed

2

Motorists Killed

0

Other Killed

15

Pedestrians Injured

10

Cyclists Injured

566

Motorists Injured

1

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

Crashes occurred most frequently on Fridays, with 372 incidents, and the peak time for collisions was the 12 p.m. hour, with 157 crashes. A significant majority of crashes, 1,272 or 65.9%, happened during daylight hours. The period from 12 p.m. to 5 p.m. saw the highest concentration of crashes throughout the day.

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

The majority of crashes, 76% (1,468 incidents), resulted in no injuries and involved only property damage. The remaining 24% of crashes resulted in an injury or fatality. This includes 3 fatal crashes, which led to a total of 3 deaths during the year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.2%
Serious Injury16serious injury crashes0.8%
Minor Injury132minor injury crashes6.8%
Possible Injury312possible injury crashes16.2%
No Injury1,468no injury crashes76%

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

The most common contributing factor cited was a vehicle running off the road to the left, which accounted for 440 crashes or 22.8% of the total. Collisions with an animal were the second-leading factor with 204 incidents (10.6%), followed by a driver losing control, which was cited in 123 crashes (6.4%).

Officer-Reported Primary Contributing Cause

Ran off road - left440 (22.8%)
Animal204 (10.6%)
Lost Control123 (6.4%)
Ran Traffic Signal105 (5.4%)
FTYROW: From stop sign91 (4.7%)
Ran Stop Sign88 (4.6%)
FTYROW: Making left turn79 (4.1%)
Followed too close68 (3.5%)
Made improper turn62 (3.2%)
Driving too fast for conditions61 (3.2%)

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

Road & Environmental Conditions

A majority of collisions occurred in ideal driving conditions, with 65.9% taking place in daylight and 65.1% on dry road surfaces. Similarly, 52.1% of crashes happened in clear weather. Crashes in adverse conditions included 134 in rain, 119 in snow, and 262 on wet roads.

Weather

Clear1,007 (57.2%)
Cloudy469 (26.6%)
Rain134 (7.6%)
Snow119 (6.8%)
Freezing rain/drizzle15 (0.9%)
Fog, smoke, smog9 (0.5%)
Blowing Snow4 (0.2%)
Blowing sand, soil, dirt2 (0.1%)
Sleet, hail1 (0.1%)
Severe Winds1 (0.1%)

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

Lighting

Daylight1,272 (72.1%)
Dark - roadway lighted288 (16.3%)
Dark - roadway not lighted126 (7.1%)
Dusk52 (2.9%)
Dawn22 (1.2%)
Dark - unknown roadway lighting4 (0.2%)

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

Road Surface

Dry1,258 (71.4%)
Wet262 (14.9%)
Snow150 (8.5%)
Ice/frost43 (2.4%)
Slush38 (2.2%)
Gravel8 (0.5%)
Other (explain in narrative)2 (0.1%)
Water (standing or moving)1 (0.1%)

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

Vehicles & Demographics

Among the 3,447 vehicles involved in crashes, the most frequent makes were Chevrolet (801), Ford (438), and Toyota (255). Analyzing the demographics of the 4,051 people involved, the 26-34 age group was the most represented with 637 individuals. The 45-54 age group (556 people) and the 16-20 age group (548 people) were also highly represented.

Top Vehicle Makes (3,447 vehicles)

1
CHEV491 (14.2%)
2
FORD438 (12.7%)
3
CHEVROLET310 (9%)
4
TOYT159 (4.6%)
5
JEEP151 (4.4%)
6
DODG137 (4%)
7
HOND124 (3.6%)
8
GMC103 (3%)
9
DODGE99 (2.9%)
10
TOYOTA96 (2.8%)

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

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

Sex Distribution (2,995 persons with recorded sex)

Male1,638 (54.7%)
Female1,357 (45.3%)

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 of crashes was a vehicle running off the road to the left, cited in 440 incidents (22.8%). Collisions involving an animal were the second-most common cause at 204 crashes (10.6%). The third-leading cause was a driver losing control of their vehicle, which accounted for 123 crashes (6.4%).

Major Cause

1
Ran off road - left440 (23.5%)
2
Animal204 (10.9%)
3
Lost Control123 (6.6%)
4
Ran Traffic Signal105 (5.6%)
5
FTYROW: From stop sign91 (4.9%)
6
Ran Stop Sign88 (4.7%)
7
FTYROW: Making left turn79 (4.2%)
8
Followed too close68 (3.6%)
9
Made improper turn62 (3.3%)

Showing top 9 of 49 reported. 40 additional (613 total) not shown: Driving too fast for conditions, Improper or erratic lane changing, Driver Distraction: Other interior distraction, FTYROW: From driveway, Ran off road - straight, Other (explain in narrative): Other, Improper Backing, Driver Distraction: Inattentive/lost in thought, Other (explain in narrative): No improper action, Exceeded authorized speed, Driver Distraction: Exterior distraction, Ran off road - right, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Reaching for object(s)/fallen object(s), FTYROW: From parked position, Driver Distraction: Adjusting devices (radio, climate), Failed to keep in proper lane, Driver Distraction: Passenger, FTYROW: Other (explain in narrative), Passing: Other passing (explain in narrative), Swerving/Evasive Action, FTYROW: From yield sign, Traveling wrong way or on wrong side of road, Driver Distraction: Other electronic device activity, Passing: With insufficient distance/inadequate visibility, FTYROW: To pedestrian, Driver Distraction: Talking on a hand-held device, FTYROW: At uncontrolled intersection, Failed to yield to emergency vehicle, Aggressive driving/road rage, Driver Distraction: Manual operation of an electronic communication device, Passing: On wrong side, Passing: Through/around barrier, Traveling on prohibited traffic way, Other (explain in narrative): Vision obstructed, FTYROW: Making right turn on red signal, Cargo/equipment loss or shift, Passing: Where prohibited by signs/markings, Crossed centerline (undivided), Illegally Parked/Unattended.

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

First Harmful Event

The most common initial event in a crash was a collision with another vehicle in traffic, which occurred in 1,249 incidents (64.7%). The second-most frequent event was a collision with an animal, accounting for 198 crashes. Collisions with fixed objects were also common, including impacts with ditches (73), utility poles (40), and curbs (36).

First Harmful Event

1
Collision with: Vehicle in traffic1,249 (65%)
2
Collision with: Animal198 (10.3%)
3
Collision with: Parked motor vehicle83 (4.3%)
4
Collision with fixed object: Ditch73 (3.8%)
5
Non-collision events: Overturn/rollover43 (2.2%)
6
Collision with fixed object: Utility pole/light support40 (2.1%)
7
Collision with fixed object: Curb/island/raised median36 (1.9%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)24 (1.2%)
9
Collision with fixed object: Fire hydrant14 (0.7%)

Showing top 9 of 40 reported. 31 additional (162 total) not shown: Non-collision events: Other non-collision (explain in narrative), Collision with: Re-entering roadway, Collision with fixed object: Tree, Collision with fixed object: Embankment, Collision with fixed object: Traffic sign support, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Guardrail - face, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Traffic signal support, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fence, Other (explain in narrative), Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Other fixed object (explain in narrative), Non-collision events: Jackknife, Miscellaneous events: Hit and run, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Mailbox, Collision with fixed object: Building, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Impact attenuator/crash cushion, Collision with fixed object: Guardrail - end, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Wall, Collision with fixed object: Ground, Collision with: Thrown or falling object, Miscellaneous events: Vehicle out of gear/rolled, Non-collision events: Fell/jumped from vehicle, 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

Over half of the crashes (54.8%) occurred at non-intersection locations, with 929 of these happening on straight or curved road segments. Approximately 34.9% of crashes took place at intersections, where four-way intersections were the most common type, accounting for 445 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature929 (52.7%)
2
Intersection: Four-way intersection445 (25.2%)
3
Intersection: T-intersection165 (9.4%)
4
Non-intersection: Driveway access (related, not in)64 (3.6%)
5
Intersection: Other intersection (explain in narrative)37 (2.1%)
6
Non-intersection: Driveway access (within)33 (1.9%)
7
Non-intersection: Other non-intersection (explain in narrative)18 (1%)
8
Interchange-related: On-ramp merge area14 (0.8%)
9
Intersection: Y-intersection14 (0.8%)

Showing top 9 of 21 reported. 12 additional (45 total) not shown: Interchange-related: On-ramp, Non-intersection: Crossover-related, Non-intersection: Alley, Interchange-related: Off-ramp, diverge area, Intersection: Five points or more, Intersection: Intersection with ramp, Intersection: Traffic circle, Interchange-related: Mainline, between ramps, Interchange-related: Other interchange (explain in narrative), Intersection: L-intersection, Interchange-related: Off-ramp, Non-intersection: Railroad grade crossing.

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

Vehicle Type

Passenger cars were the most prevalent vehicle type, involved in 1,844 instances, followed by sport utility vehicles (733) and light trucks or pickups (434). Tractor/semi-trailers were involved in 60 crashes, and motorcycles were involved in 42 crashes.

Vehicle Type

"Other" combines 18 smaller categories (73 records): Cargo/panel van (23), Single-unit truck (>= 3 axles) (12), Passenger van (seats 9-15) (6), Other bus (seats > 15) (5), Moped (3), Farm tractor (3), School bus (seats > 15) (3), Other small bus (seats 9-15) (3), Other (explain in narrative) (3), Other light truck (<=10000 lbs) (2), Truck tractor (bobtail) (2), Maintenance/construction vehicle (2), 3-wheeled, unenclosed (1), Golf cart (1), Small school bus (seats 9-15) (1), Snowmobile (1), Farm equipment (explain in narrative) (1), Truck/trailer (1).

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

Traffic Control Device

A majority of vehicles involved in crashes (58%) were in areas with no traffic controls present. Where traffic controls were a factor, traffic signals were the most common device, present for 824 vehicles involved in collisions. Stop signs were the second-most common control, present for 349 vehicles.

Traffic Control Device

"Other" combines 3 smaller categories (8 records): Work zone sign (4), Flashing traffic control signal (3), Railway crossing device (1).

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

Most Damaged Area

The front of the vehicle was the most frequently damaged area, recorded for 887 vehicles. The rear of the vehicle was the second-most common point of impact with 430 instances, indicating a high proportion of rear-end collisions. Side impacts were also frequent, distributed across various points on the driver and passenger sides.

Most Damaged Area

"Other" combines 9 smaller categories (732 records): Driver side - rear (159), Driver side - middle (157), Rear - driver side corner (112), Passenger side - rear (107), Rear - passenger side corner (74), Top (45), Other (explain in narrative) (39), Non-collision/no damage (25), Undercarriage (14).

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

Impairment (Alcohol / Drugs)

A total of 58 crashes, representing 3% of all incidents, were recorded as involving an impaired driver. Among the 63 drivers identified as being under the influence, alcohol was the primary substance in 54 cases. Drugs were a factor for 6 drivers, and a combination of alcohol and drugs was noted for 3 drivers.

Crashes by City

Within the county, the City of Dubuque experienced the highest volume of traffic incidents, with 1,477 crashes reported in 2015. Dyersville had the second-highest count with 49 crashes, followed by Sageville with 16 crashes. These three municipalities represent the top locations for crashes in the region.

Crashes by City

1
DUBUQUE1,477 (91.3%)
2
DYERSVILLE49 (3%)
3
SAGEVILLE16 (1%)
4
ASBURY15 (0.9%)
5
PEOSTA11 (0.7%)
6
CASCADE9 (0.6%)
7
FARLEY8 (0.5%)
8
RICKARDSVILLE6 (0.4%)
9
NEW VIENNA5 (0.3%)

Showing top 9 of 19 reported. 10 additional (22 total) not shown: WORTHINGTON, EPWORTH, BERNARD, ZWINGLE, CENTRALIA, LUXEMBURG, DURANGO, SHERRILL, GRAF, BALLTOWN.

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

Paved vs Unpaved Road

The overwhelming majority of crashes, 1,919 in total, occurred on paved roadways. In contrast, only 11 crashes, representing approximately 0.6% of the total, were recorded on unpaved surfaces such as gravel or dirt roads.

Paved vs Unpaved Road

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

Roadway Contributing Factor

When a roadway factor was identified as a contributor to a crash, adverse surface conditions like wet or icy pavement were the leading cause, cited in 206 incidents. Other noted factors included a slippery or worn surface in 10 crashes and the presence of a work zone in 8 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)206 (88.4%)
2
Slippery, loose or worn surface10 (4.3%)
3
Work Zone (roadway-related)8 (3.4%)
4
Debris3 (1.3%)
5
Traffic backup, regular congestion3 (1.3%)
6
Shoulders (none, low, soft, high)2 (0.9%)
7
Traffic backup, prior crash1 (0.4%)

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

Driver Condition

Among drivers recorded with a condition other than 'apparently normal,' the most frequent was being under the influence of alcohol, noted for 65 drivers. Driver fatigue or falling asleep was the next most common condition, recorded for 20 drivers, followed by a pre-existing medical condition for 14 drivers.

Driver Condition

1
Under the influence of alcohol65 (52.4%)
2
Asleep/fatigued20 (16.1%)
3
Medical condition (seizure, reaction)14 (11.3%)
4
Illness/fainted6 (4.8%)
5
Physical impairment6 (4.8%)
6
Emotional (e.g. depressed, angry)5 (4%)
7
Paraplegic/wheelchair restricted4 (3.2%)
8
Under the influence of drugs/meds3 (2.4%)
9
Walks with a cane/crutches1 (0.8%)

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

Property Damage

The most common range for estimated property damage was between $1,500 and $7,500, which applied to 1,470 crashes. A small fraction of incidents, 21 crashes or 1.1% of the total, resulted in severe damage estimated at over $25,000.

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 512 incidents or 26.5% of all crashes. Single-vehicle, non-collision events, such as running off the road, were the second-most common type with 478 incidents (24.8%). Broadside collisions were the third-most frequent, with 323 incidents (16.7%).

Manner of Collision

"Other" combines 3 smaller categories (66 records): Head-on (front to front) (38), Rear to side (27), Rear to rear (1).

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

Pre-Crash Driver Action

The most common action of vehicles immediately before a crash was moving straight ahead, which was the case for 1,905 of the 3,447 vehicles involved (55.3%). Turning left was the second-most frequent pre-crash action, recorded for 334 vehicles (9.7%), followed by slowing or stopping for 216 vehicles (6.3%).

Pre-Crash Driver Action

1
Movement essentially straight1,905 (57.6%)
2
Turning left334 (10.1%)
3
Slowing/stopping (deceleration)216 (6.5%)
4
Legally Parked212 (6.4%)
5
Turning right161 (4.9%)
6
Stopped in traffic148 (4.5%)
7
Changing lanes68 (2.1%)
8
Other (explain in narrative)61 (1.8%)
9
Backing53 (1.6%)

Showing top 9 of 19 reported. 10 additional (152 total) not shown: Negotiating a curve, Entering traffic lane (merging), Overtaking/passing, Leaving a parked position, Accelerating in road, Illegally Parked/Unattended, Starting in road, Leaving traffic lane, Making U-turn, Entering a parked position.

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

Pedestrian/Cyclist Action

For the 26 crashes involving pedestrians or bicyclists where an action was specified, the most common behavior was entering or crossing the roadway. This action was recorded in 19 instances, accounting for the majority of these vulnerable user incidents.

Pedestrian/Cyclist Action

1
Entering or crossing roadway19 (73.1%)
2
Movement: On sidewalk2 (7.7%)
3
Movement: Along roadway with traffic1 (3.8%)
4
Playing on or working on vehicle1 (3.8%)
5
Entering/exiting vehicle1 (3.8%)
6
Working in trafficway1 (3.8%)
7
Movement: Along roadway against traffic1 (3.8%)

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

Person Type

Drivers comprised the vast majority of individuals involved in crashes, accounting for 3,908 of the 4,051 people recorded (96.5%). Passengers were the next largest group with 116 individuals. The remaining persons involved included 16 pedestrians and 10 bicyclists.

Person Type

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

Person Injury Severity

Of the 4,051 people involved in crashes, a total of 595 were either injured or killed. This included 3 fatalities, 18 serious injuries, 158 minor injuries, and 416 possible injuries. The remaining individuals were not recorded as having sustained an injury.

Person Injury Severity

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

Occupant Safety Equipment

In the subset of 447 vehicle occupants for whom safety equipment use was recorded, 401 (89.7%) were using a shoulder and lap belt. Twenty-six individuals in this group, or 5.8%, were noted as not using any safety restraint at the time of the collision.

Occupant Safety Equipment

"Other" combines 2 smaller categories (2 records): Child safety seat (type unknown) (1), 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 crash configuration, accounting for 1,259 incidents (65.2% of the total). Single-vehicle crashes were the second-most frequent type with 553 incidents (28.6%). Crashes involving three or more vehicles were less common, making up the remaining 6.2% of incidents.

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: 1,931
  • Total persons involved: 4,051
  • Total vehicles involved: 3,447

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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