Fatal Crashes Only
This report covers fatal crashes only, from the NHTSA Fatality Analysis Reporting System — the federal census of every crash on a US public road that killed someone within 30 days. It does not include injury or property-damage-only crashes, and its totals are not comparable with the all-severity crash reports published elsewhere on this site.
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YEAR-OVER-YEAR CRASH REPORT · ALASKA · 2015
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/alaska/fatal/statewide/2015-annual-report
Yearly Traffic Safety Analysis
60 CRASHES IN
ALASKA
2015
In 2015, Alaska recorded 60 fatal crashes, an 11.8% decrease from the 68 fatal crashes recorded in 2014. This overall decline included fewer fatalities, injuries, and a notable drop in the number of two-vehicle fatal collisions. The most significant year-over-year shift was the increase in fatal motorcycle crashes, which rose from 7 in 2014 to 10 in 2015.
60
▼ -11.8%was 68
Total Crash Events
65
▼ -11.0%was 73
Persons Killed
55
▼ -16.7%was 66
Persons Injured
3
▼ -40.0%was 5
Hit-and-Run Crashes
Note: "Persons Killed" (65) counts individual fatalities across all crash events. "Fatal" in the severity table below (60) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for fatal traffic incidents in Alaska was downward in 2015 compared to the previous year. The number of fatal crashes decreased by 11.8% from 68 to 60, and the number of people killed fell by 11.0% from 73 to 65. The number of non-fatal injuries in these crashes also saw a 16.7% decline from 66 to 55.
3
Hit-and-Run Crashes — 2015
▼ -40.0% vs prior (5)
The number of fatal hit-and-run crashes decreased from 5 in 2014 to 3 in 2015. As a result, the rate of fatal hit-and-runs as a proportion of all fatal crashes also trended downward, falling from 7.4% in 2014 to 5.0% in 2015.
Vulnerable Road User Casualties
12
Pedestrians Killed
53
Motorists Killed
1
Pedestrians Injured
54
Motorists Injured
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 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
The timing of fatal crashes shifted between the two periods. In 2015, Saturday was the most frequent day for fatal crashes with 15 incidents, a change from 2014 when Wednesday was the peak day with 14 crashes. The peak hour also moved from the 6 p.m. evening slot in 2014 (7 crashes) to the mid-afternoon at 2 p.m. in 2015 (8 crashes).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)
Road & Environmental Conditions
The distribution of fatal crashes across lighting conditions remained broadly similar year-over-year, with daylight conditions accounting for roughly half of all incidents in both 2015 (31 crashes) and 2014 (33 crashes). In terms of weather, fatal crashes occurring in clear conditions increased from 30 in 2014 to 35 in 2015. Conversely, fatal crashes in rain and snow decreased from a combined 16 incidents in 2014 to 7 in 2015.
Weather
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Weather condition at time of crash
Lighting
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Lighting condition field
Vehicles & Demographics
In 2015, Ford vehicles were involved in the most fatal crashes (18), taking the top spot from Chevrolet, which was most frequent in 2014 (18 vehicles). The age demographics of persons involved also shifted; the 35-44 age group saw an increase from 15 people involved in 2014 to 29 in 2015. Meanwhile, the number of people from the 26-34 and 45-54 age groups involved in fatal crashes decreased.
Top Vehicle Makes (88 vehicles)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (149 persons with recorded sex)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Speed Limit Zones
Roads with 55 mph speed limits saw the most fatal crashes in 2015, with 18 incidents, an increase from 16 in 2014. Fatal crashes on 45 mph roads decreased from 16 in 2014 to 11 in 2015. The number of fatal crashes in 65 mph zones saw a slight decrease from 10 to 9 year-over-year.
Fatal crashes by zone: 15 mph: 1 of 1 (100%) · 20 mph: 2 of 2 (100%) · 25 mph: 6 of 6 (100%) · 30 mph: 3 of 3 (100%) · 40 mph: 4 of 4 (100%) · 45 mph: 11 of 11 (100%) · 50 mph: 2 of 2 (100%) · 55 mph: 18 of 18 (100%) · 60 mph: 1 of 1 (100%) · 65 mph: 9 of 9 (100%)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Posted speed limit at crash location
Manner of Collision
Single-vehicle crashes, categorized as "Not a Collision with Motor Vehicle In-Transport," were the predominant type of fatal incident in both periods, accounting for 41 crashes in 2015 and 42 in 2014. There was a notable decrease in fatal angle collisions, which dropped from 14 in 2014 to 6 in 2015. Fatal front-to-front collisions also decreased from 10 to 7 over the same period.
Manner of Collision
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Vehicle Type
In 2015, standard pickups were the most common vehicle type involved in fatal crashes (19 vehicles), followed by motorcycles (11) and compact utility vehicles (10). This contrasts with 2014, when compact utility vehicles were most frequent (20), followed by standard pickups (19). The number of motorcycles involved in fatal crashes increased from 10 in 2014 to 11 in 2015.
Vehicle Type
Showing top 9 of 21 reported. 12 additional (17 total) not shown: Station Wagon (excluding van and truck based), 2-door sedan,hardtop,coupe, Unknown body type, Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Other motored cycle type (mini-bikes, motor scooters, pocket motorcycles, "pocket bikes"), Pickup with slide-in camper, Single-unit straight truck or Cab-Chassis (GVWR unknown), Snowmobile, 5-door/4-door hatchback, Medium/heavy truck based motorhome, Cross Country/Intercity Bus, Other Bus Type.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Vehicle unit records
Rural vs Urban
There was a significant shift in the location of fatal crashes from rural to urban areas. In 2014, rural roads accounted for 37 fatal crashes compared to 31 on urban roads. In 2015, this pattern nearly inverted, with 30 fatal crashes occurring in urban areas and 29 in rural areas, marking a 21.6% decrease in rural fatal crashes.
Rural vs Urban
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Functional Class
Interstate highways saw an increase in fatal crashes, rising from 18 incidents in 2014 to 22 in 2015, making it the road class with the most fatal incidents. Fatal crashes on Principal Arterial roads remained constant at 13 in both years. There was a combined decrease in fatal crashes on collector and minor arterial roads, falling from 28 incidents in 2014 to 20 in 2015.
Roadway Functional Class
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Ownership
In 2015, roadways owned by the State Highway Agency were the site of the vast majority of fatal crashes, accounting for 48 incidents. City or Municipal Highway Agency roads saw 6 fatal crashes, and County Highway Agency roads saw 5. Data for the prior year was not available for comparison.
Roadway Ownership
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Person Type
Drivers constituted the largest group of individuals involved in fatal crashes in both years, though their numbers decreased from 101 in 2014 to 88 in 2015. The number of passengers and pedestrians involved also saw slight declines. Notably, 3 bicyclists were involved in fatal crashes in 2014, whereas none were in 2015.
Person Type
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
In 2015, 65 of the 158 people involved in fatal crashes were fatally injured (41.1%), a similar proportion to 2014 when 73 of 179 people were fatally injured (40.8%). The number of people sustaining serious injuries (A) in these crashes decreased from 24 in 2014 to 16 in 2015. The number of uninjured individuals (O) also decreased from 40 to 38.
Person Injury Severity
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Crash-level records
Occupant Safety Equipment
The number of occupants reported as using no restraints decreased significantly, from 31 in 2014 to 18 in 2015. The use of shoulder and lap belts was the most frequently reported safety measure in both periods, though the count fell from 69 occupants in 2014 to 61 in 2015. For motorcyclists, the number reported as wearing no helmet decreased from 11 to 9.
Occupant Safety Equipment
"Other" combines 6 smaller categories (8 records): Child Restraint System - Rear Facing (2), Restraint Used - Type Unknown (2), Unknown if Helmet Worn (1), Child Restraint Type Unknown (1), Shoulder Belt Only Used (1), Booster Seat (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Point of Impact
Frontal impacts, recorded as "12 Clock Point," remained the most common point of impact in both years, though the number of vehicles with this impact type decreased from 52 in 2014 to 46 in 2015. "Non-Collision" events, which include rollovers, were the second most common category and remained stable with 9 incidents in both periods.
Point of Impact
"Other" combines 8 smaller categories (9 records): 3 Clock Point (2), Left-Back Side (1), Left-Front Side (1), 10 Clock Point (1), Other Objects Set-In-Motion (1), Right-Front Side (1), Undercarriage (1), 4 Clock Point (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2015-01-01 to 2015-12-31 · Vehicle unit records
Vehicles Per Crash
Single-vehicle fatal crashes remained the most common type, with an identical count of 41 incidents in both 2015 and 2014. However, there was a sharp decline in two-vehicle fatal crashes, which fell by 45.8% from 24 in 2014 to 13 in 2015. This shifted the proportion of single-vehicle incidents from 60.3% of all fatal crashes in 2014 to 68.3% in 2015.
Vehicles Per Crash
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 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 NHTSA FARS (Fatal Crashes), accessed programmatically via the NHTSA FARS 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: NHTSA FARS 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: August 5, 2026
Data Coverage
- Reporting period: 2015-01-01 through 2015-12-31 (365 days)
- Geographic scope: Alaska
- Total crash records analyzed: 60
- Total persons involved: 158
- Total vehicles involved: 88
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). "Alaska Crash Intelligence Report: 2015." Published August 5, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/alaska/fatal/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: NHTSA FARS (Fatal Crashes) · NHTSA FARS
Period: 2015-01-01 – 2015-12-31
Generated: August 5, 2026 · All rights reserved
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