Analysis & Deep Dives
Data journalism and investigative analysis of autonomous vehicle safety. Every article uses real numbers from the NHTSA incident database.
📊 Our Analysis Methodology
Every analysis article on AutoPilotWatch follows a rigorous, data-first methodology. We start with the raw data — NHTSA SGO incident reports, consumer complaints, recall records, and investigation filings — and apply statistical analysis to identify patterns, trends, and anomalies.
Our analysis principles:
- Data-driven: Every claim is backed by specific numbers from official sources.
- Transparent: We show our work. Data sources and methodology are documented.
- Contextualized: Raw numbers without context are misleading. We always account for fleet size, reporting thresholds, and other confounding factors.
- Independent: We have no financial relationship with any manufacturer. Our analysis is based solely on public data.
For full details on how we process and classify data, see our methodology page. All underlying data is available on our downloads page.
Side-by-side comparisons of manufacturers, technologies, and safety records using real data.
AV vs Human Driver: The Real Comparison
The definitive data comparison between autonomous vehicles and human drivers using Waymo, Tesla, and NHTSA FARS data — crash rates, injury rates, and critical caveats.
Waymo vs Tesla vs Cruise: The AV Safety Scoreboard
Head-to-head comparison of the top 3 AV companies on every metric — incidents, fatalities, injury rates, ADS share, and computed safety grades.
Waymo vs. Tesla: A Safety Comparison by the Numbers
1,729 incidents vs 3,092. 2 fatalities vs 56. The data paints a stark picture of two very different approaches to automated driving.
Tesla Model Y vs Model 3: Which Is Safer?
Nearly identical incident counts — 1,295 vs 1,289 — but the Model 3 has 61% more fatalities. We dig into crash types, severity, and what separates these two.
Topics We Cover
🔴 Manufacturer Safety
Deep dives into specific manufacturers' safety records, including Tesla, Waymo, Cruise, and emerging AV companies.
📈 Trend Analysis
Year-over-year trends in incidents, fatalities, and injuries. Are autonomous vehicles getting safer over time?
🗺️ Geographic Patterns
Where crashes happen and why. State-level regulation, urban vs. suburban patterns, and climate effects.
⚙️ Technology Comparisons
Camera-only vs. lidar, ADS vs. ADAS, and how different technology approaches affect real-world safety.
📋 Regulatory Analysis
How NHTSA, state regulators, and international bodies are responding to autonomous vehicle safety challenges.
🔍 Incident Investigations
Detailed examinations of specific crashes, including contributing factors, system behavior, and aftermath.
Frequently Asked Questions
What kind of analysis does AutoPilotWatch publish?
We publish 34 articles spanning data deep dives, investigations, comparisons, explainers, and policy analysis. Every article uses real numbers from the NHTSA incident database — we never rely on anecdotal evidence or unverified claims.
How are analysis articles different from the data pages?
Data pages (like Incidents, Manufacturers, States) present raw data in searchable, filterable formats. Analysis articles interpret that data — identifying patterns, testing hypotheses, comparing manufacturers, and drawing evidence-based conclusions that raw tables can't convey.
Can I use AutoPilotWatch analysis in my research or reporting?
Absolutely. All our analysis is based on publicly available NHTSA data and is free to cite. We ask that you credit AutoPilotWatch and link back to the original article. If you're a journalist working on a story, we're happy to provide additional data and context.
How often are new articles published?
We publish new analysis articles as significant data updates, trends, or events warrant. Major NHTSA data releases, recalls, and policy changes often trigger new analysis. Subscribe to our newsletter for notifications.
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