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U.S. Road Safety Intelligence 2.0 · on Jo Datasets

50 years of U.S. road-safety data, unified and ready to analyze.

About 1.87M fatal crashes from 1975–2024 and 328K+ NHTSA recall records, linked and ready to query.

1975 – 2024NHTSA sourcesReady to query
Dataset · linked modelVerified release
Crashes
Time, place, conditions, response
1.87M
Vehicles
Make, model year, body type, role
2.8M
People
Drivers, occupants, pedestrians, cyclists
4.85M
Recalls
30,438 campaigns, included
328,859
The problem · 01

The data is public. Making it usable takes months.

Federal road-safety data is split across 50 years of changing formats, codes and files, and recalls are published separately. Making it usable takes months of engineering before your team can ask its first question.

We've done that work once. You start at the query.

Source files1975 → 2024
Changing formatsChanging codesSeparate recall files
Normalized, linked, checked
One linked modelCrash → vehicle → person
What's inside · 02

Four record types, linked and ready.

Crashes, vehicles and people join on shared keys. Recall records ship in the same dataset.

01 · Crashes
1.87M

Crash records, 1975 to 2024, on one normalized schema.

02 · Vehicles
2.8M

Vehicle records, each tied to its crash.

03 · People
4.85M

Person records, each tied to its vehicle and crash.

04 · Recalls
328,859

Recall records across 30,438 campaigns.

Coverage
DistractionImpairmentViolationsPedestrians and cyclistsWeatherLocationCommercial and hazmat vehiclesEmergency response timing
Who it's for · 03

Three industries, one dataset, different questions.

Automotive, insurance and public-sector teams work from the same linked records. What changes is the question.

Automotive and mobility

Compare vehicles on real-world fatal-crash outcomes and study the scenarios driver-assist systems have to handle.

  • 01Vehicle safety benchmarking
  • 02Recall intelligence
  • 03ADAS scenario research

Insurance and fleet

Add 50 years of road-safety context to research, fleet programs and the risk models you already run.

  • 01Geographic safety intelligence
  • 02Fleet safety programs
  • 03Enriching risk models

Transportation and government

Find where fatal crashes concentrate, decide where to spend, and check what changed after a policy took effect.

  • 01Crash hotspot screening
  • 02Prioritizing infrastructure spend
  • 03Pedestrian and cyclist safety
  • 04Evaluating policies
Sample questions · 04

Questions you can answer on day one.

If your team is asking something like this, the data is already shaped for it.

Automotive

Which vehicle model years show the most rollover fatalities?

Government

Where do pedestrian deaths cluster at night?

Automotive

How many recall campaigns cover a given component, by manufacturer and model year?

Fleet

How do fatal crashes involving large trucks vary by time of day and road type?

Government

Which counties have the longest gap between crash time and EMS arrival?

Insurance

How does alcohol involvement in fatal crashes shift by hour, weekday and state?

Insurance

Which states see the highest share of fatal crashes in rain or snow?

Government

How has the number of cyclist deaths changed by state over the last decade?

Build vs. buy · 05

Why not build it yourself?

You can. Here is what that takes, next to what you get on day one.

Topic
Build it yourself
U.S. Road Safety Intelligence
Formats
Build it yourselfDownload and decode 50 years of formats
Road Safety IntelligenceNormalized from 1975 to 2024
Joins
Build it yourselfJoin crashes, vehicles and people by hand
Road Safety IntelligenceAlready linked by crash → vehicle → person keys
Recalls
Build it yourselfFind and prepare recall data separately
Road Safety IntelligenceRecall data included
Quality
Build it yourselfDo your own quality checks
Road Safety IntelligenceTotals checked against NHTSA's official numbers for 2010–2024
Time to first query
Build it yourselfMonths of engineering
Road Safety IntelligenceReady to query from day one
Data sources · 06

Official sources, every step documented.

Built only from NHTSA data. Nothing is estimated or blended in from other sources.

Source 01 · NHTSA

FARS

Fatality Analysis Reporting System. The source for every crash, vehicle and person record, 1975 to 2024.

Source 02 · NHTSA

Recall flat files

The source for all 328,859 recall records across 30,438 campaigns.

Every transformation documented

You can trace any field back to the source file it came from.

Original source codes kept

Normalized values sit next to the codes NHTSA published, so nothing is lost.

Totals checked against NHTSA

Counts match NHTSA's official numbers for 2010–2024.

NHTSA and Google do not endorse this product.

Access · 07

How access works.

One linked, verified dataset. Access by arrangement only.

  1. 01

    Request access

    Tell us who you are and what you want to answer.

  2. 02

    We arrange access

    We confirm terms and set up access for your team.

  3. 03

    Start querying

    Use SQL, your notebooks and your BI tools against the linked dataset.

What you get
Delivery
Linked, query-ready dataset
Access
By arrangement only
Release
One-time verified release
Refresh
No automatic refresh
What it isn't
No APINo dashboardNo real-time feedNo SLA

It's the data, linked and verified. If you need analytics or applications on top, we build those separately.

FAQ · 08

The limits, stated plainly.

What the dataset covers, and what it doesn't.

Does it include non-fatal crashes?

No. The dataset covers fatal crashes only.

Can insurers use it for pricing or underwriting?

We make no pricing or underwriting claims. Insurance use is for enrichment and research only.

Does the data show that a recall caused a crash?

No. Recall and crash records sit in the same dataset so you can study them side by side. Nothing in it establishes that a recall caused a crash.

How current is it?

Crash data runs from 1975 through 2024. This is a one-time verified release with no automatic refresh.

Is there an API, dashboard or SLA?

No. It's delivered as a dataset. There's no API, dashboard, real-time feed or SLA.

Can you build analysis on top of it for us?

Yes. That's a separate engagement, scoped to the questions your team needs answered.

Jo Datasets

The dataset is the start. We build the rest.

Access by arrangement · Custom intelligence on request