NHTSA FARS 1975–2023

Name: NHTSA FARS 1975–2023
Creator: ClarityStorm
License: https://www.claritystorm.com/license

US Fatal Crash Database — AI-Ready Structured Dataset

49 years of US fatal motor vehicle crash data from the NHTSA Fatality Analysis Reporting System. Every crash on a US public road resulting in a death within 30 days — cleaned, standardised, and structured for AI/ML workflows. Three relational tables covering ~990K crash events, ~1.5M vehicles, and ~2.8M persons.

Sample: Public DomainPaid: Commercial LicenseCSV + Parquet~5.3M records1975–2023

Why not just download it from NHTSA?

You can — it's public domain. Here's what we saved you:

✓ Harmonized 49 years of schema changes — NHTSA's column names, types, and coding schemes shifted repeatedly across decades
✓ Standardized crash_date and crash_time fields across every format variation NHTSA has used since 1975
✓ Added human-readable fields — state_name, day_of_week alongside the original FIPS codes
✓ Consistent join keys across all 3 tables (Accidents, Vehicles, Persons) using st_case + year
✓ Parquet output — NHTSA ships SAS format exports; we convert to columnar Parquet for fast queries

⏱ Skip ~4–6 hours of data archaeology. 49 annual releases, each in SAS format, each slightly different.

What you'd need to do yourself ↓

Download 49 annual zip files from the NHTSA FARS portal (each contains multiple tables)
Read SAS export format — requires SAS, R, or Python's pyreadstat to parse
Reconcile field names that changed across NHTSA annual releases
Handle coding scheme changes (e.g., state codes, restraint codes) that shifted over 5 decades
Merge into a consistent schema without breaking the Accident–Vehicle–Person join keys

~990K

Fatal Crashes

Years

States

Tables

Use Cases

Fatality Prediction Models

Train classifiers to predict crash severity from road, vehicle, and environmental features across 49 years of data.

Geospatial Hotspot Analysis

Cluster fatal crashes by lat/lon to identify high-risk corridors and intersections nationwide.

Long-Term Safety Trend Analysis

49 years of continuous data enables time-series modeling of fatality rates, drunk driving trends, and seatbelt adoption.

Drug & Alcohol Impairment Research

Detailed per-person and per-vehicle impairment indicators for public health and policy research.

Vehicle Safety Research

Link crash outcomes to vehicle type, model year, and restraint use to evaluate safety equipment effectiveness.

Insurance Actuarial Modeling

National-scale fatal crash data for risk scoring, underwriting models, and telematics calibration.

Schema

Three relational tables joining on st_case + year. Shown below: fars_accidents (primary table). Vehicles and Persons tables included in paid tiers.

Field	Type	Description
st_case	int	Unique case number (state + sequence)
year	int	Data year (1975–2023)
state	int	State FIPS code
state_name	string	State name
crash_date	string	Crash date (YYYY-MM-DD)
crash_time	string	Crash time (HH:MM)
day_of_week	string	Day name
fatals	int	Number of fatalities
drunk_drivers	int	Number of drunk drivers
ve_total	int	Total vehicles involved
latitude	float	Decimal degrees (post-1999)
longitude	float	Decimal degrees (post-1999)
weather	int	Weather condition code
lgt_cond	int	Light condition code
man_col	int	Manner of collision code

Quick Start

import pandas as pd

# Load accidents table
accidents = pd.read_parquet("fars_accidents.parquet")

# Fatalities by year
print(accidents.groupby("year")["fatals"].sum())

# Load all three tables
vehicles = pd.read_parquet("fars_vehicles.parquet")
persons  = pd.read_parquet("fars_persons.parquet")

# Join persons to accidents
merged = persons.merge(
    accidents[["st_case", "year", "state_name", "crash_date"]],
    on=["st_case", "year"]
)

Pricing

Sample

Free

1,000 rows (CSV) + schema docs

Public Domain

Download Sample

Complete

$99

All 3 tables (Accidents, Vehicles, Persons) — CSV + Parquet

Commercial License

Buy Complete

Annual

$249/yr

All files + annual updates when NHTSA releases new FARS data

Commercial License

Data Provenance

Source: National Highway Traffic Safety Administration (NHTSA), US Department of Transportation

Portal: NHTSA FARS Data Portal

License: FARS is a US federal government work and is in the public domain under 17 U.S.C. 105. The processed dataset inherits this public domain status. Paid tiers are licensed under the ClarityStorm Commercial Data License for internal use, covering our pipeline and enrichment work.

Attribution: “FARS data sourced from NHTSA Fatality Analysis Reporting System, processed by ClarityStorm Data.”

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