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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Yearly Traffic Safety Analysis

747 CRASHES IN
ALABAMA
2014

All metrics benchmarked against2013

In 2014, there were 747 fatal crashes in Alabama, a 2.6% decrease from the 767 fatal crashes recorded in 2013. These incidents resulted in 820 fatalities in 2014, compared to 853 in the prior year. The most notable year-over-year shift was a significant increase in fatal crashes involving pedestrians, which rose from 59 in 2013 to 97 in 2014, a 64.4% increase.

747

-2.6%was 767

Total Crash Events

820

-3.9%was 853

Persons Killed

483

-10.9%was 542

Persons Injured

24

50.0%was 16

Hit-and-Run Crashes

Note: "Persons Killed" (820) counts individual fatalities across all crash events. "Fatal" in the severity table below (747) 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

Overall, the data indicates a downward trend in fatal traffic incidents. Fatal crashes decreased by 2.6% from 767 in 2013 to 747 in 2014. Similarly, the number of fatalities fell by 3.9% from 853 to 820, and total injuries in these crashes declined by 10.9% from 542 to 483.

24

Hit-and-Run Crashes — 2014

50.0% vs prior (16)

Fatal hit-and-run crashes trended upwards year-over-year. The absolute number of such incidents increased from 16 in 2013 to 24 in 2014. Consequently, the rate of fatal crashes classified as hit-and-run also increased, rising from 2.1% in 2013 to 3.2% in 2014.

Vulnerable Road User Casualties

96

Pedestrians Killed

Prior: 5962.7%

9

Cyclists Killed

Prior: 650.0%

714

Motorists Killed

Prior: 788-9.4%

1

Other Killed

Prior: 0%

12

Pedestrians Injured

Prior: 6100.0%

2

Cyclists Injured

Prior: 0%

469

Motorists Injured

Prior: 536-12.5%

0

Other Injured

Prior: 00.0%

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 remained largely consistent year-over-year. Saturday was the peak day for fatal crashes in both 2014 (156 crashes) and 2013 (141 crashes). The peak hour for these incidents was also stable, occurring at 5 p.m. in 2014 (48 crashes) and also being a peak in 2013 (46 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

Lighting conditions saw a notable shift between the two periods. While daylight remained the most common condition, fatal crashes during daylight hours decreased from 377 to 349. Conversely, fatal crashes on dark, unlighted roads increased from 221 in 2013 to 275 in 2014. Regarding weather, fatal crashes in clear conditions were dominant and increased from 495 to 523, while those occurring in rain decreased from 90 to 50.

Weather

Clear523 (70.3%)
5.7%prior 495
Cloudy159 (21.4%)
-1.9%prior 162
Rain50 (6.7%)
-44.4%prior 90
Fog, Smog, Smoke7 (0.9%)
-41.7%prior 12
Other2 (0.3%)
Snow2 (0.3%)
Sleet or Hail1 (0.1%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Weather condition at time of crash

Lighting

Daylight349 (47.0%)
-7.4%prior 377
Dark - Not Lighted275 (37.0%)
24.4%prior 221
Dark - Lighted87 (11.7%)
-37.9%prior 140
Dusk16 (2.2%)
60.0%prior 10
Dawn10 (1.3%)
66.7%prior 6
Dark - Unknown Lighting6 (0.8%)
-25.0%prior 8

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Lighting condition field

Vehicles & Demographics

The makes of vehicles involved in fatal crashes remained consistent, with Chevrolet (190) and Ford (167) being the top two in 2014, swapping places with Ford (192) and Chevrolet (177) from 2013. There was a notable demographic shift in the age of persons involved in fatal crashes; involvement for those aged 55-64 and 65+ increased, while it decreased for most younger and middle-aged groups.

Top Vehicle Makes (1,066 vehicles)

1
CHEVROLET190 (17.8%)
7.3%prior 177
2
FORD167 (15.7%)
-13.0%prior 192
3
TOYOTA89 (8.3%)
-9.2%prior 98
4
DATSUN/NISSAN65 (6.1%)
12.1%prior 58
5
HONDA63 (5.9%)
-7.4%prior 68
6
DODGE54 (5.1%)
1.9%prior 53
7
GMC34 (3.2%)
-15.0%prior 40
8
BUICK / OPEL27 (2.5%)
22.7%prior 22
9
FREIGHTLINER24 (2.3%)
-17.2%prior 29
10
JEEP / KAISER-JEEP / WILLYS- JEEP23 (2.2%)
-17.9%prior 28

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Vehicle unit records

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

Sex Distribution (1,667 persons with recorded sex)

Male1,072 (64.3%)
-2.0%prior 1,094
Female595 (35.7%)
-7.0%prior 640

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

The distribution of fatal crashes across speed zones was similar in both years, with the highest concentrations on roads with 45 mph and 55 mph limits. In 2014, there were more fatal crashes in 45 mph zones (208) than in 55 mph zones (206). This is a slight shift from 2013, when 55 mph zones saw the most fatal crashes (229), followed by 45 mph zones (194).

Fatal crashes by zone: 15 mph: 1 of 1 (100%) · 20 mph: 2 of 2 (100%) · 25 mph: 23 of 23 (100%) · 30 mph: 17 of 17 (100%) · 35 mph: 74 of 74 (100%) · 40 mph: 42 of 42 (100%) · 45 mph: 208 of 208 (100%) · 50 mph: 37 of 37 (100%) · 55 mph: 206 of 206 (100%) · 60 mph: 13 of 13 (100%) · 65 mph: 59 of 59 (100%) · 70 mph: 58 of 58 (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

The most common type of fatal crash in both periods was 'Not a Collision with Motor Vehicle In-Transport', which includes rollovers and collisions with fixed objects or pedestrians. This type accounted for 503 fatal crashes in 2014, up from 493 in 2013. While angle collisions (101 vs. 137) and front-to-front collisions (75 vs. 88) decreased, fatal front-to-rear collisions saw a notable increase from 27 in 2013 to 50 in 2014.

Manner of Collision

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records

Vehicle Type

Passenger cars and light trucks were the most common vehicles involved in fatal crashes in both years. In 2014, 328 4-door sedans were involved, compared to 353 in 2013. The involvement of vehicles in high-fatality categories saw a decrease; motorcycle involvement dropped from 85 in 2013 to 62 in 2014, and truck-tractors decreased from 80 to 60 over the same period.

Vehicle Type

1
4-door sedan, hardtop328 (30.8%)
2
Standard pickup (GVWR 4,500 to 10,00 lbs.)(Jeep Pickup, Comanche, Ram Pickup, D100-D350,....)177 (16.6%)
3
Compact Utility (Utility Vehicle Categories "Small" and "Midsize")130 (12.2%)
4
Compact pickup (GVWR <4,500 lbs.) (D50,Colt P/U, Ram 50, Dakota, Arrow Pickup [foreign], Ranger, ..)64 (6%)
5
Motorcycle62 (5.8%)
6
Truck-tractor (Cab only, or with any number of trailing unit; any weight)60 (5.6%)
7
Large utility (ANSI D16.1 Utility Vehicle Categories and "Full Size" and "Large")55 (5.2%)
8
2-door sedan,hardtop,coupe52 (4.9%)
9
Station Wagon (excluding van and truck based)23 (2.2%)

Showing top 9 of 31 reported. 22 additional (115 total) not shown: Minivan (Chrysler Town and Country, Caravan, Grand Caravan, Voyager, Voyager, Honda-Odyssey, ...), ATV/ATC [All-Terrain Cycle], Unknown body type, Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), 3-door/2-door hatchback, Convertible(excludes sun-roof,t-bar), 5-door/4-door hatchback, Single-unit straight truck or Cab-Chassis (GVWR > 26,000 lbs.), Utility station wagon (includes suburban limousines, Suburban, Travellall, Grand Wagoneer), Single-unit straight truck or Cab-Chassis (10,000 lbs. < GVWR < or = 19,500 lbs.), Transit Bus (City Bus), Single-unit straight truck or Cab-Chassis (19,500 lbs. < GVWR < or = 26,000 lbs.), Medium/heavy Pickup (>10,000 lbs. GVWR), School Bus, Golf Cart, Camper or motorhome, unknown truck type, Moped (motorized bicycle), Cab Chassis Based (includes Rescue Vehicle, Light Stake, Dump, and Tow Truck), Off-road Motorcycle, Other or Unknown automobile type, Farm equipment other than trucks, Three-wheel Motorcycle (2 Rear Wheels).

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Vehicle unit records

Rural vs Urban

The distribution of fatal crashes between rural and urban areas remained stable, with rural roads accounting for a disproportionate majority of incidents. In 2014, there were 495 fatal crashes in rural areas and 251 in urban areas, a split of 66.3% rural. This is almost identical to 2013, which saw 502 rural and 260 urban fatal crashes, a 65.9% rural share.

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

Fatal crashes were most prevalent on arterial and collector roads in both periods, rather than on Interstates or local roads. In 2014, Major Collector roads saw 179 fatal crashes, Principal Arterials had 177, and Minor Arterials had 148. This represents a shift from 2013, when Principal Arterials (194) and Minor Arterials (185) had more fatal crashes than Major Collectors (151). Fatal crashes on Interstates remained steady, with 94 in 2014 compared to 90 in 2013.

Roadway Functional Class

1
Major Collector179 (24%)
2
Principal Arterial - Other177 (23.7%)
3
Minor Arterial148 (19.8%)
4
Local111 (14.9%)
5
Interstate94 (12.6%)
6
Minor Collector34 (4.6%)
7
Principal Arterial - Other Freeways and Expressway3 (0.4%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2014-01-01 to 2014-12-31 · Crash-level records

Person Type

Drivers were the most numerous person type involved in fatal crashes in both years, though their numbers decreased from 1,114 in 2013 to 1,055 in 2014. The most significant change was among vulnerable road users; the number of pedestrians involved in these fatal incidents increased substantially from 66 in 2013 to 108 in 2014, and the number of bicyclists increased from 6 to 11.

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, a total of 1,687 persons were involved in fatal crashes, resulting in 820 fatalities (K) and 228 serious injuries (A). This was a decrease from 2013, when 1,755 involved persons included 853 fatalities and 280 serious injuries. The number of uninjured persons (O) involved in these fatal crashes increased slightly from 360 in 2013 to 384 in 2014.

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

A significant share of occupants involved in fatal crashes were not using safety equipment in both periods. The number of individuals reported with 'None Used' was nearly identical, with 518 in 2014 compared to 519 in 2013. Meanwhile, the count of those using a 'Shoulder and Lap Belt' decreased from 880 in 2013 to 816 in 2014.

Occupant Safety Equipment

"Other" combines 6 smaller categories (23 records): Child Restraint System - Rear Facing (7), Shoulder Belt Only Used (6), Booster Seat (4), Other (3), Unknown if Helmet Worn (2), Child Restraint Type Unknown (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

The primary point of impact on vehicles involved in fatal crashes was overwhelmingly frontal. In 2014, the '12 Clock Point' was recorded for 620 vehicles, a figure nearly identical to the 621 recorded in 2013. The distribution across other impact points, such as rear ('6 Clock Point') and non-collision events, also remained very stable year-over-year.

Point of Impact

"Other" combines 11 smaller categories (119 records): 1 Clock Point (33), Undercarriage (22), 2 Clock Point (22), 8 Clock Point (13), 4 Clock Point (10), 7 Clock Point (8), 5 Clock Point (5), Other Objects Set-In-Motion (3), Right-Front Side (1), Top (1), Right (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 constituted the majority of fatal crashes in both years, and their share increased. In 2014, there were 476 single-vehicle fatal crashes, accounting for 63.7% of the total, an increase from 456 single-vehicle crashes (59.4%) in 2013. Correspondingly, two-vehicle fatal crashes decreased from 268 in 2013 to 224 in 2014.

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: Alabama
  • Total crash records analyzed: 747
  • Total persons involved: 1,687
  • Total vehicles involved: 1,066

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: 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/alabama/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

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