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 · 2014
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/2014-annual-report
Yearly Traffic Safety Analysis
68 CRASHES IN
ALASKA
2014
In 2014, Alaska recorded 68 fatal crashes resulting in 73 fatalities, a significant increase from the 49 fatal crashes and 51 fatalities reported in 2013. This represents a 38.8% rise in fatal crashes and a 43.1% rise in persons killed year-over-year. One of the most notable shifts was in pedestrian-involved fatal crashes, which more than doubled from 5 in 2013 to 14 in 2014.
68
▲ 38.8%was 49
Total Crash Events
73
▲ 43.1%was 51
Persons Killed
66
▲ 69.2%was 39
Persons Injured
5
▲ 400.0%was 1
Hit-and-Run Crashes
Note: "Persons Killed" (73) counts individual fatalities across all crash events. "Fatal" in the severity table below (68) 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 · 2014-01-01 to 2014-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in fatal traffic incidents was upward in 2014 compared to the prior year. The number of fatal crashes increased by 38.8%, rising from 49 to 68. Correspondingly, the number of fatalities grew by 43.1% from 51 to 73, and the count of persons injured in these crashes rose by 69.2% from 39 to 66.
5
Hit-and-Run Crashes — 2014
▲ 400.0% vs prior (1)
Fatal hit-and-run crashes increased significantly, rising from 1 incident in 2013 to 5 in 2014. Consequently, the hit-and-run rate among fatal crashes trended upward, increasing from 2.0% in the prior year to 7.4% in the current year.
Vulnerable Road User Casualties
14
Pedestrians Killed
3
Cyclists Killed
56
Motorists Killed
0
Pedestrians Injured
0
Cyclists Injured
66
Motorists Injured
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of fatal crashes showed some shifts between the two periods. While Wednesday remained the peak day for fatal crashes in both years, the count on this day increased from 10 in 2013 to 14 in 2014. The peak hour for these incidents shifted from the early morning hours (12a and 2a) in 2013 to the 6 p.m. hour in 2014, which saw 7 fatal crashes.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash date field aggregated by weekday
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash time field aggregated by hour (0-23)
Road & Environmental Conditions
Fatal crashes in dark conditions, both lighted and unlighted, more than doubled, increasing from a combined 15 incidents in 2013 to 32 in 2014. While clear weather was the most common condition in both years, the number of fatal crashes during cloudy conditions saw a larger relative increase, rising from 11 in 2013 to 19 in 2014. Fatal crashes in the rain also increased from 5 to 9 incidents.
Weather
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Weather condition at time of crash
Lighting
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Lighting condition field
Vehicles & Demographics
Chevrolet and Ford vehicles were the most frequently involved in fatal crashes in both years, with Chevrolet's involvement increasing from 10 to 18 vehicles and Ford's from 13 to 17. The age demographics of persons involved also shifted; involvement of the 45-54 age group more than tripled from 10 individuals in 2013 to 33 in 2014. The 26-34 age group also saw a significant increase from 20 to 34 individuals.
Top Vehicle Makes (101 vehicles)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (173 persons with recorded sex)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Person-level records linked to crash events
Speed Limit Zones
In 2014, the highest number of fatal crashes occurred in 45 mph and 55 mph zones, with 16 incidents each. This marks a shift from 2013, when the 55 mph zone was the most common with 18 fatal crashes. Fatal crashes in 45 mph zones increased from 10 to 16, and those in 65 mph zones rose from 6 to 10 year-over-year.
Fatal crashes by zone: 20 mph: 1 of 1 (100%) · 25 mph: 7 of 7 (100%) · 30 mph: 1 of 1 (100%) · 35 mph: 4 of 4 (100%) · 40 mph: 4 of 4 (100%) · 45 mph: 16 of 16 (100%) · 50 mph: 4 of 4 (100%) · 55 mph: 16 of 16 (100%) · 65 mph: 10 of 10 (100%)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Posted speed limit at crash location
Manner of Collision
Single-vehicle crashes, categorized as "Not a Collision with Motor Vehicle In-Transport," were the dominant manner of collision in both periods, accounting for 42 incidents (61.8%) in 2014 and 32 incidents (65.3%) in 2013. While this type remained most frequent, its share of total fatal crashes decreased slightly. Fatal crashes involving an angle collision increased from 8 to 14, and front-to-front collisions grew from 6 to 10.
Manner of Collision
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records
Vehicle Type
Compact utility vehicles (20) and standard pickups (19) were the most common vehicle types involved in fatal crashes in 2014, both seeing their numbers roughly double from 10 and 11, respectively, in 2013. The involvement of motorcycles in fatal crashes also saw a notable increase, rising from 2 vehicles in 2013 to 10 in 2014. Involvement of 4-door sedans also doubled from 7 to 14 vehicles.
Vehicle Type
Showing top 9 of 21 reported. 12 additional (17 total) not shown: 3-door/2-door hatchback, Large utility (ANSI D16.1 Utility Vehicle Categories and "Full Size" and "Large"), Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Single-unit straight truck or Cab-Chassis (GVWR > 26,000 lbs.), Truck-tractor (Cab only, or with any number of trailing unit; any weight), Unknown van type, 5-door/4-door hatchback, 3-door coupe, Unknown body type, Unknown medium/heavy truck type, Cross Country/Intercity Bus, Construction equipment other than trucks (includes graders).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Vehicle unit records
Rural vs Urban
Fatal crashes increased in both rural and urban settings in 2014. The number of fatal crashes in urban areas nearly doubled, rising from 17 in 2013 to 31 in 2014. Despite this sharp increase, rural areas continued to account for the majority of fatal crashes, with 37 incidents in 2014 compared to 32 in the prior year.
Rural vs Urban
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records
Roadway Functional Class
Interstates accounted for the highest number of fatal crashes in 2014 with 18 incidents, a stable figure compared to 17 in 2013. Significant increases were observed on other road types, with fatal crashes on Principal Arterials increasing from 8 to 13 and on Major Collectors from 7 to 11. This indicates a growing number of fatal incidents on non-interstate arterial and collector routes.
Roadway Functional Class
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records
Person Type
Drivers were the largest category of persons involved in fatal crashes in both years, with their numbers increasing from 66 in 2013 to 101 in 2014. The number of pedestrians involved more than doubled from 6 to 14, and passengers involved increased from 40 to 61. The number of bicyclists involved also rose from 1 to 3.
Person Type
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records
Person Injury Severity
In 2014, 73 of the 179 people involved in fatal crashes sustained fatal injuries (K), an increase from 51 fatalities among 114 people in 2013. The number of individuals receiving serious injuries (A) doubled from 12 to 24 year-over-year. The number of uninjured persons (O) involved in these fatal crashes also increased from 24 to 40.
Person Injury Severity
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records
Occupant Safety Equipment
The number of occupants involved in fatal crashes who were not using any safety equipment increased from 21 in 2013 to 31 in 2014. For motorcyclists, the number recorded with 'No Helmet' rose from 6 to 11. Concurrently, the number of occupants reported as using a shoulder and lap belt also increased from 57 to 69.
Occupant Safety Equipment
"Other" combines 3 smaller categories (4 records): Helmet, Unknown if DOT Compliant (2), Booster Seat (1), Child Restraint System - Rear Facing (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Person-level records linked to crash events
Point of Impact
Frontal impacts ('12 Clock Point') were the most frequent point of impact, increasing from 34 incidents in 2013 to 52 in 2014. This represented the primary impact point in 51.5% of vehicles in 2014, up from 50.7% in the prior year. 'Non-Collision' events, such as rollovers, were the second most common category, remaining relatively stable with 9 events in 2014 compared to 11 in 2013.
Point of Impact
"Other" combines 8 smaller categories (15 records): 2 Clock Point (3), 3 Clock Point (3), Left-Back Side (2), 9 Clock Point (2), 6 Clock Point (2), Left-Front Side (1), Right-Back Side (1), 8 Clock Point (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Vehicle unit records
Vehicles Per Crash
Single-vehicle incidents remained the most common type of fatal crash, increasing from 31 in 2013 to 41 in 2014 and accounting for 60.3% of all fatal crashes in the current period. The number of two-vehicle fatal crashes also grew from 17 to 24. Additionally, 2014 included one fatal crash involving six vehicles, a large multi-vehicle event not present in the 2013 data.
Vehicles Per Crash
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · 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: 2014-01-01 through 2014-12-31
- Report generated: August 5, 2026
Data Coverage
- Reporting period: 2014-01-01 through 2014-12-31 (365 days)
- Geographic scope: Alaska
- Total crash records analyzed: 68
- Total persons involved: 179
- Total vehicles involved: 101
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: 2014." Published August 5, 2026. Reporting period: 2014-01-01 to 2014-12-31. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/alaska/fatal/statewide/2014-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: 2014-01-01 – 2014-12-31
Generated: August 5, 2026 · All rights reserved
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