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 · ALABAMA · 2016
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/alabama/fatal/statewide/2016-annual-report
Yearly Traffic Safety Analysis
979 CRASHES IN
ALABAMA
2016
In 2016, Alabama recorded 979 fatal crashes, resulting in 1,083 fatalities, a significant 24.9% increase from the 784 fatal crashes recorded in 2015. This upward trend was observed across most metrics. One of the most notable year-over-year shifts was a 61.8% increase in fatal crashes involving a motorcycle, which rose from 68 in 2015 to 110 in 2016.
979
▲ 24.9%was 784
Total Crash Events
1,083
▲ 27.4%was 850
Persons Killed
685
▲ 10.7%was 619
Persons Injured
19
▼ -51.3%was 39
Hit-and-Run Crashes
Note: "Persons Killed" (1,083) counts individual fatalities across all crash events. "Fatal" in the severity table below (979) 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 · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety trends in Alabama worsened from 2015 to 2016, with a significant increase in fatal incidents. The number of fatal crashes rose by 24.9%, from 784 to 979. Correspondingly, the number of people killed in these crashes increased by 27.4%, from 850 to 1,083.
19
Hit-and-Run Crashes — 2016
▼ -51.3% vs prior (39)
The number of fatal crashes classified as hit-and-run saw a significant decrease between the two periods. In 2016, there were 19 fatal hit-and-run crashes, down from 39 in 2015. This represents a drop in the hit-and-run rate from 5.0% of fatal crashes in 2015 to 1.9% in 2016.
Vulnerable Road User Casualties
120
Pedestrians Killed
3
Cyclists Killed
958
Motorists Killed
2
Other Killed
8
Pedestrians Injured
0
Cyclists Injured
671
Motorists Injured
6
Other Injured
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Saturday remained the deadliest day of the week for fatal crashes in both 2015 and 2016, with the count increasing from 134 to 172. The daily peak hour for fatal crashes shifted later into the evening, moving from 5 p.m. in 2015 (51 crashes) to the 8 p.m. hour in 2016 (56 crashes). Fatal crashes on Sunday also saw a notable increase from 126 to 157.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)
Road & Environmental Conditions
The majority of fatal crashes in both years occurred in clear weather and during daylight hours. Fatal crashes in clear weather increased from 528 to 738, while those in daylight rose from 373 to 483. The proportion of fatal crashes occurring in darkness without streetlights also grew, increasing from 279 incidents in 2015 to 324 in 2016.
Weather
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Weather condition at time of crash
Lighting
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Lighting condition field
Vehicles & Demographics
Chevrolet (232 vehicles) and Ford (224 vehicles) remained the top two vehicle makes involved in fatal crashes in 2016, both showing an increase from the prior year. An analysis of persons involved in fatal crashes shows a demographic shift, with the 26-34 age group becoming the most represented in 2016 with 392 individuals, a substantial increase from 268 in 2015. This displaced the 35-44 age group, which was the largest in the prior year.
Top Vehicle Makes (1,416 vehicles)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Vehicle unit records
67 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,266 persons with recorded sex)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Person-level records linked to crash events
Speed Limit Zones
Fatal crashes increased across most posted speed zones year-over-year. The highest number of fatal crashes occurred in 55 mph zones, rising from 231 in 2015 to 299 in 2016. Similarly, fatal crashes in 45 mph zones increased from 193 to 258, and those in 70 mph zones grew from 68 to 97.
Fatal crashes by zone: 15 mph: 2 of 2 (100%) · 25 mph: 21 of 21 (100%) · 30 mph: 26 of 26 (100%) · 35 mph: 92 of 92 (100%) · 40 mph: 48 of 48 (100%) · 45 mph: 258 of 258 (100%) · 50 mph: 36 of 36 (100%) · 55 mph: 299 of 299 (100%) · 60 mph: 18 of 18 (100%) · 65 mph: 73 of 73 (100%) · 70 mph: 97 of 97 (100%)
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · 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 collision type in both years and saw a substantial increase from 480 incidents in 2015 to 635 in 2016. This type accounted for 64.9% of all fatal crashes in 2016, up from 61.2% in the prior year. Angle collisions were the second most frequent type, increasing from 141 to 149.
Manner of Collision
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Vehicle Type
Four-door sedans were the most common vehicle type in fatal crashes in both years, with involvement increasing from 370 vehicles in 2015 to 396 in 2016. A significant change was observed in motorcycle involvement, which jumped from 64 in 2015 to 111 in 2016. The number of truck-tractors in fatal crashes also rose from 83 to 90.
Vehicle Type
Showing top 9 of 30 reported. 21 additional (192 total) not shown: Station Wagon (excluding van and truck based), 3-door/2-door hatchback, Single-unit straight truck or Cab-Chassis (GVWR > 26,000 lbs.), Cab Chassis Based (includes Rescue Vehicle, Light Stake, Dump, and Tow Truck), Single-unit straight truck or Cab-Chassis (GVWR unknown), ATV/ATC [All-Terrain Cycle], 5-door/4-door hatchback, Unknown body type, Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Utility station wagon (includes suburban limousines, Suburban, Travellall, Grand Wagoneer), Convertible(excludes sun-roof,t-bar), Medium/heavy Pickup (>10,000 lbs. GVWR), Single-unit straight truck or Cab-Chassis (19,500 lbs. < GVWR < or = 26,000 lbs.), Single-unit straight truck or Cab-Chassis (10,000 lbs. < GVWR < or = 19,500 lbs.), Farm equipment other than trucks, Other vehicle type (includes go-cart, fork-lift, city street sweeper dunes/swamp buggy), Other motored cycle type (mini-bikes, motor scooters, pocket motorcycles, "pocket bikes"), Medium/heavy truck based motorhome, Pickup with slide-in camper, Unknown (pickup style) light conventional truck type, School Bus.
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Vehicle unit records
Rural vs Urban
Fatal crashes on rural roadways were far more common than on urban roads and saw a significant increase, rising from 533 in 2015 to 715 in 2016. Consequently, the share of fatal crashes occurring in rural areas grew from 68.0% to 73.0% year-over-year. This highlights the disproportionate and growing risk on rural transportation networks.
Rural vs Urban
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Roadway Functional Class
Arterial roadways accounted for the majority of fatal crashes in both periods. Fatal crashes on Principal Arterials increased from 210 to 259, while those on Minor Arterials grew from 185 to 218. Major Collector roads also saw a rise in fatal crashes, from 153 to 196, indicating that these primary and secondary thoroughfares became more dangerous year-over-year.
Roadway Functional Class
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Roadway Ownership
Roadways owned by the State Highway Agency were the site of most fatal crashes, with the number increasing from 439 in 2015 to 569 in 2016. County-owned roads accounted for the second-highest number, rising from 232 to 268 fatal crashes. Fatal crashes on city or municipal roads also increased, from 111 to 141.
Roadway Ownership
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Person Type
Drivers constituted the largest group of individuals involved in fatal crashes, with their numbers increasing from 1,181 in 2015 to 1,411 in 2016. The number of passengers involved also grew from 567 to 716. Pedestrians involved in fatal crashes increased from 111 to 128, while bicyclists saw a decrease from 12 to 3.
Person Type
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Person Injury Severity
The number of persons killed (Fatal 'K' injuries) in crashes increased by 27.4%, from 850 in 2015 to 1,083 in 2016. The total number of individuals involved in these fatal crashes, including survivors, grew from 1,881 to 2,281. The count of uninjured persons ('O') also rose from 412 to 513.
Person Injury Severity
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Crash-level records
Occupant Safety Equipment
While the number of occupants using a shoulder and lap belt increased from 929 to 1,066, the number of occupants reported with no safety equipment used also grew substantially. The count of individuals using no restraint in a fatal crash rose from 548 in 2015 to 687 in 2016. This indicates a growing number of unbelted individuals involved in fatal incidents.
Occupant Safety Equipment
"Other" combines 5 smaller categories (39 records): Helmet, Unknown if DOT Compliant (11), Child Restraint System - Rear Facing (10), Shoulder Belt Only Used (10), Booster Seat (7), Restraint Used - Type Unknown (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Person-level records linked to crash events
Point of Impact
Frontal impacts ('12 Clock Point') were the most common point of initial impact in both years, increasing from 697 vehicles in 2015 to 818 in 2016. Rear impacts ('6 Clock Point') were the second-most frequent for collisions, though far less common, increasing from 78 to 92. The data consistently shows frontal collisions as the leading impact type in fatal crashes.
Point of Impact
"Other" combines 10 smaller categories (157 records): 1 Clock Point (46), 2 Clock Point (29), 7 Clock Point (23), 8 Clock Point (20), 4 Clock Point (15), 5 Clock Point (9), Undercarriage (6), Top (5), Other Objects Set-In-Motion (3), Right (1).
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · Vehicle unit records
Vehicles Per Crash
Single-vehicle crashes were the most frequent type of fatal incident, increasing from 446 in 2015 to 591 in 2016. This raised the share of single-vehicle crashes from 56.9% to 60.4% of all fatal crashes. Two-vehicle fatal crashes also increased, rising from 287 to 329 incidents year-over-year.
Vehicles Per Crash
Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2016-01-01 to 2016-12-31 · 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: 2016-01-01 through 2016-12-31
- Report generated: August 5, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-12-31 (366 days)
- Geographic scope: Alabama
- Total crash records analyzed: 979
- Total persons involved: 2,281
- Total vehicles involved: 1,416
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). "Alabama Crash Intelligence Report: 2016." Published August 5, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/alabama/fatal/statewide/2016-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: 2016-01-01 – 2016-12-31
Generated: August 5, 2026 · All rights reserved
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