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 · 2013
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/2013-annual-report
Yearly Traffic Safety Analysis
49 CRASHES IN
ALASKA
2013
In 2013, there were 49 fatal crashes, representing a 9.3% decrease from the 54 fatal crashes recorded in 2012. Despite the overall decline in fatal incidents, the number of speeding-related fatal crashes increased significantly, rising from 13 in 2012 to 20 in 2013. This increase in speeding involvement occurred even as total fatalities dropped from 59 to 51 year-over-year.
49
▼ -9.3%was 54
Total Crash Events
51
▼ -13.6%was 59
Persons Killed
39
▼ -29.1%was 55
Persons Injured
1
Hit-and-Run Crashes
Note: "Persons Killed" (51) counts individual fatalities across all crash events. "Fatal" in the severity table below (49) 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 · 2013-01-01 to 2013-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The data indicates a downward trend in fatal traffic incidents between 2012 and 2013. The number of fatal crashes decreased by 9.3%, from 54 to 49. Similarly, total fatalities fell from 59 to 51, and the number of people injured in these crashes declined from 55 to 39.
1
Hit-and-Run Crashes — 2013
2.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
6
Pedestrians Killed
1
Cyclists Killed
44
Motorists Killed
0
Pedestrians Injured
0
Cyclists Injured
39
Motorists Injured
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns of fatal crashes shifted between the two periods. In 2013, Wednesday was the most frequent day for fatal crashes with 10 incidents, a change from 2012 when Friday saw the most crashes (11). The peak time also moved from the 9 p.m. hour in 2012 (6 crashes) to the early morning hours of 12 a.m. and 2 a.m. in 2013 (5 crashes each).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash date field aggregated by weekday
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash time field aggregated by hour (0-23)
Road & Environmental Conditions
The majority of fatal crashes in both periods occurred in favorable conditions. In 2013, 53% of fatal crashes happened in clear weather, nearly identical to the 56% in 2012. Likewise, fatal crashes in daylight conditions represented 57% of the total in 2013, a slight decrease from 61% in the previous year, indicating no major shift in the role of lighting or weather conditions.
Weather
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Weather condition at time of crash
Lighting
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Lighting condition field
Vehicles & Demographics
The most common vehicle makes involved in fatal crashes remained consistent. Ford and Chevrolet led in both years, with Ford's involvement decreasing from 15 vehicles in 2012 to 13 in 2013, and Chevrolet's from 12 to 10. Yamaha became the third-most frequent make in 2013 with 6 vehicles involved, replacing Dodge which held the third position in 2012 with 8 vehicles.
Top Vehicle Makes (67 vehicles)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (110 persons with recorded sex)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of fatal crashes across speed zones remained stable between the two periods. The 55 mph zone was the most common location for fatal crashes in both 2013 and 2012, accounting for 18 fatal crashes each year. The 45 mph zone was the second-most common, with 10 fatal crashes in 2013 and 12 in 2012. There was no notable shift in fatal crash occurrences towards higher or lower speed limit zones.
Fatal crashes by zone: 15 mph: 1 of 1 (100%) · 20 mph: 1 of 1 (100%) · 25 mph: 2 of 2 (100%) · 35 mph: 4 of 4 (100%) · 40 mph: 3 of 3 (100%) · 45 mph: 10 of 10 (100%) · 55 mph: 18 of 18 (100%) · 65 mph: 6 of 6 (100%)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Posted speed limit at crash location
Manner of Collision
In both periods, the dominant manner of collision for fatal crashes involved single vehicles, categorized as "Not a Collision with Motor Vehicle In-Transport." This type accounted for 32 of 49 fatal crashes (65%) in 2013, an increase in proportion from 31 of 54 fatal crashes (57%) in 2012. The second most common type, angle collisions, saw a decrease from 11 incidents in 2012 to 8 in 2013.
Manner of Collision
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash-level records
Vehicle Type
Light trucks and passenger cars were the most common vehicle types in fatal crashes for both years. In 2013, standard pickups (11) and compact utility vehicles (10) were the most frequent, a change from 2012 when 4-door sedans (15) and standard pickups (14) led. Notably, the number of motorcycles involved in fatal crashes decreased from 6 in 2012 to 2 in 2013. The involvement of large trucks (truck-tractors) was unchanged, with 2 vehicles recorded in each period.
Vehicle Type
Showing top 9 of 22 reported. 13 additional (15 total) not shown: Medium/heavy Pickup (>10,000 lbs. GVWR), Motorcycle, Utility station wagon (includes suburban limousines, Suburban, Travellall, Grand Wagoneer), 3-door/2-door hatchback, 5-door/4-door hatchback, Convertible(excludes sun-roof,t-bar), Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Medium/heavy truck based motorhome, Minivan (Chrysler Town and Country, Caravan, Grand Caravan, Voyager, Voyager, Honda-Odyssey, ...), Other vehicle type (includes go-cart, fork-lift, city street sweeper dunes/swamp buggy), Station Wagon (excluding van and truck based), Unknown body type, Unknown (pickup style) light conventional truck type.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Vehicle unit records
Rural vs Urban
A significant majority of fatal crashes occurred on rural roadways in both periods. In 2013, 32 of the 49 fatal crashes (65%) were in rural areas, a figure consistent with 2012, when 35 of 54 fatal crashes (65%) were rural. This persistent concentration is notable, as rural roads often have higher fatality rates due to factors like higher speeds and longer emergency response times. The urban-rural distribution of fatal crashes showed no change between the two years.
Rural vs Urban
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash-level records
Roadway Functional Class
Interstate highways accounted for the largest number of fatal crashes in both years, with 17 incidents in 2013, down from 20 in 2012. Arterial roads (Principal and Minor) collectively saw 14 fatal crashes in 2013, the same number as in 2012. Fatal crashes on Major Collector roads decreased from 11 in 2012 to 7 in 2013, while incidents on local roads increased slightly from 4 to 6.
Roadway Functional Class
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash-level records
Person Type
Drivers were the largest group of individuals involved in fatal crashes in both periods, with 66 drivers recorded in 2013, down from 83 in 2012. The number of passengers involved also decreased from 52 to 40. There was a decrease in pedestrian involvement from 8 individuals in 2012 to 6 in 2013, while one bicyclist was involved in each of the two years.
Person Type
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash-level records
Person Injury Severity
The number of people killed (K) in fatal crashes decreased from 59 in 2012 to 51 in 2013. In addition to the fatalities, the number of people sustaining non-fatal injuries also declined, with serious injuries (A) falling from 18 to 12 and minor injuries (B) from 24 to 17. The number of individuals who were involved in these fatal crashes but sustained no injuries (O) also decreased, from 31 to 24.
Person Injury Severity
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Crash-level records
Occupant Safety Equipment
The data shows a decrease in the absolute number of occupants involved in fatal crashes, both with and without safety equipment. The number of occupants reported as using no restraints fell from 33 in 2012 to 21 in 2013. Despite this drop, the share of occupants not using restraints remained significant, representing 27% of those with a known status in 2013, compared to 29% in 2012.
Occupant Safety Equipment
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Person-level records linked to crash events
Point of Impact
The front of the vehicle ("12 Clock Point") was the most common point of impact in both years, though its frequency decreased. In 2013, 34 vehicles sustained frontal impacts, down from 54 in 2012. Meanwhile, the number of vehicles involved in "Non-Collision" events, such as rollovers, increased from 8 in 2012 to 11 in 2013, suggesting a proportional shift away from frontal impacts.
Point of Impact
"Other" combines 5 smaller categories (8 records): 3 Clock Point (2), 4 Clock Point (2), 11 Clock Point (2), Undercarriage (1), 2 Clock Point (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · Vehicle unit records
Vehicles Per Crash
Single-vehicle incidents constituted the majority of fatal crashes in both periods, and their share increased year-over-year. In 2013, 31 of 49 fatal crashes (63%) involved a single vehicle, up from 29 of 54 fatal crashes (54%) in 2012. Consequently, fatal crashes involving multiple vehicles became less frequent, with two-vehicle crashes decreasing from 19 to 17 and three-vehicle crashes dropping from 6 to 1.
Vehicles Per Crash
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2013-01-01 to 2013-12-31 · 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: 2013-01-01 through 2013-12-31
- Report generated: August 5, 2026
Data Coverage
- Reporting period: 2013-01-01 through 2013-12-31 (365 days)
- Geographic scope: Alaska
- Total crash records analyzed: 49
- Total persons involved: 114
- Total vehicles involved: 67
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: 2013." Published August 5, 2026. Reporting period: 2013-01-01 to 2013-12-31. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/alaska/fatal/statewide/2013-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: 2013-01-01 – 2013-12-31
Generated: August 5, 2026 · All rights reserved
Someone you love in this data? We’ll help you find out if you have a case.
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