Primary sources first
Our starting point is the original data from organizations such as IIHS, HLDI, NHTSA FARS, Euro NCAP, ANCAP, and peer-reviewed research—not copied rankings or dealership claims.
Research library
Independent Vehicle Safety Research
We turn primary crash-test, fatality, insurance, and safety data into plain-English answers to the vehicle-safety questions that matter most.
Library updated August 10, 2026. Every analysis identifies its sources, explains what the data can and cannot prove, and links to the underlying methodology.
What makes this research different
A five-star crash test is useful, but it is not the whole story. We connect controlled tests to real-world outcomes and make the uncertainty visible instead of hiding it behind a single score.
Lab tests + real roads
We compare crash-test ratings with driver death rates, insurance losses, and fatality data to surface places where laboratory results and lived outcomes agree—or diverge.
Transparent trade-offs
Vehicle safety is not one-dimensional. We document assumptions, show limitations, and distinguish model-specific evidence from class- and brand-level context.
Start with a question
These are substantial analyses, not generic buying guides. Each page explains the question, the evidence, and the practical takeaway.
New · Micromort economics
How Much Is a Safer Car Worth?
Convert driver death-rate differences into micromorts, dollars, and a break-even used-car price premium.
Written · Updated Sources: U.S. DOT value of statistical life and IIHS driver death rates Interactive fatal-crash censusWhat Happened—and Who Was Harmed?
Search vehicle nameplates across every final FARS release from 2020–2024 without treating raw counts as risk rates.
Written · Updated Source: NHTSA FARS crash, vehicle, person, and event tables Original comparisonCrash Tests vs. Real-World Death Rates
Explore where top laboratory performance tracks actual outcomes—and where it does not.
Written · Updated Sources: IIHS crash tests and driver-death-rate data Public safetyRisk to Other Road Users
Examine how vehicle size and design affect other drivers and people walking or biking.
Written · Updated Sources: IIHS and NHTSA evidence Methods explainedTesla FSD Safety Statistics
Separate Tesla's collision-frequency report from independent evidence and the limits of public crash reporting.
Written · Updated Sources: Tesla, NHTSA, and IIHS Methods explainedWhy Newer Crash Tests Changed the Rankings
Understand the tougher IIHS front and side tests and why rear-seat protection now matters more.
Written · Updated Source: IIHS testing protocols and ratings Evidence reviewThe Tesla Safety Paradox
Four competing explanations for excellent crash tests alongside above-average brand-level death rates.
Written · Updated Sources: IIHS, NHTSA, and published research Insurance dataHardest Cars to Steal
HLDI theft claim frequency by model: the vehicles thieves leave alone, and why the most-stolen list looks different.
Written · Updated Source: HLDI insurance-loss data Practical safetyTire Safety: Wear, Weather, and Risk
Learn how tire condition, climate, and stopping distance change the safety margin of any vehicle.
Written · Updated Sources: NHTSA, AAA, and climate data Counterintuitive findingsDoes All-Wheel Drive Make You Safer?
Compare evidence on traction, driver behavior, and the difference between avoiding a crash and surviving one.
Written · Updated Sources: IIHS and Swedish road-safety researchCommunity data discussions
Informed for Life also publishes original visualizations and answers methodology questions on Reddit as u/informed-for-life. Those discussions are a supplement to this library—not a substitute for the source links, methods, and corrections maintained here.
View original Reddit postsHow we work
1. Frame a real decision.We start with a question a driver or family can act on—not a keyword to target.
2. Trace the evidence.We prefer original reports and datasets, then link to them so readers can check the work.
3. Separate facts from interpretation.Measured results, assumptions, and editorial conclusions are kept distinct.
4. Publish limitations and corrections.Data gaps, demographic effects, and model-year changes are part of the analysis, not footnotes to ignore.
Need the formula or want to challenge a conclusion?
Read the complete methodology, learn who is behind the site on the About page, or send a correction or source. Independent scrutiny makes this work better.