Like it or not, autonomous vehicles (AVs) are coming and all of us on the roads are part of the experiment.
In the US, how safe are AVs?
The US leader in autonomy, Waymo, a Google/Alphabet-backed venture, periodically releases safety data that provides a window into their AV’s safety.
The other big news maker in US AVs, Tesla, doesn’t release detailed data on its advanced driver-assist safety and does not yet have AVs (unsupervised) on public roads (instead they are testing a small fleet with humans in the vehicle who supervise the AI driving).
Waymo has AVs that are rider-only (robot drives the car without human supervision) on city roads (no highways yet) in Phoenix, San Fran, LA and Austin.
After about 96 million miles, Waymo had about 304 fewer injury crashes, 80% lower, than a human driver benchmark.
Hmmm, as I am due, after today, to renew my DL, I wonder if one is needed if you own an AV? You aren’t driving, just a passenger, it would be like taking an Uber, Lyft or taxi!
Great news, Londoners! We’re bringing our fully autonomous ride-hailing service across the pond, where we intend to offer rides – with no human behind the wheel – in 2026.
Waymo’s expansion, current and planned (interesting times).
Currently, 11 cities have true autonomous driving and 6 have current commercial service and 4 (testing now) are planned to have commercial service by end of 2025. One city (testing now) has service planned for 2026.
Waymo plans for at least a total of 17 cities to have commercial service by the end of 2026.
Driverless is true autonomy (unsupervised by a human).
Supervised is human responsible for the driving even if AI/robot is driving, which is used to test the AI driver.
Commercial driverless operations:
San Francisco [and Bay Area: San Mateo, Redwood City, Palo Alto, San Jose]
Los Angeles
Phoenix
Atlanta
Austin
Miami (began Nov 18)
Driverless testing, commercial service expected in 2026:
Dallas - end of 2025
Houston - end of 2025
San Antonio - end of 2025
Orlando - end of 2025
San Diego - in 2026
Supervised testing, commercial service expected in 2026:
Las Vegas
Denver
Detroit
Nashville
Washington DC
London
Supervised testing for service in 2026 or beyond (aka, no confirmed launch timeline):
Safety data release from Waymo, now with robotaxis in 10 metro areas and 170 million autonomous miles as of December 2025 and accumulating 4 million autonomous miles per week.
Waymo is the only robotaxi deployed at anything near this scale in the US, so no meaningful robotaxi competition at the moment (although many companies are making announcements and running very small deployments).
I’ve now seen them in two cities, but have not ridden.
I crossed the street in front of one and it did not run me over.
There is a lot of information in the links, including very technical details on how they try to do apples-to-apples statistical comparison to human drivers.
This is not experimental data like a clinical trial, so the results are even more dependent on the assumptions in their statistical model (this is not good or bad, just the state of the art).
Waymo has released new data indicating that the Waymo Driver continues to make roads safer in the places in which we operate.
A new analysis covers over 170 million fully autonomous miles—an equivalent of 200 human lifetimes of driving. The data shows that regardless of fault, the Waymo Driver was involved in 92% fewer crashes that cause serious or fatal injuries than human drivers in the same driving conditions. Our Driver was also involved in 83% fewer crashes where airbags are deployed, and 82% fewer crashes involving any injuries at all.
At our current scale, driving over 4 million miles weekly, our analysis suggests the Waymo Driver is preventing approximately one serious-injury crash every 8 days.
Recent interview with Waymo co-CEO that provides a window into their AI capabilities (long interview, summary further below as well).
(At 4 million miles per week, Waymo is on pace to more than double their cumulative miles this year to go from 170 to over 400 million. At 500,000 rides per week, they average 8 miles per ride. To continue their scaling across more metro areas, they need to not be at fault for a bad accident.)
One of the most significant technical revelations is how Waymo has moved beyond simple modular systems to a sophisticated foundation-model-driven approach:
Offboard Foundation Model: Waymo starts with a massive offboard model that understands the physical and social aspects of the world [07:31].
The Three Teachers: This foundation is specialized into three high-capacity “teacher” models:
The Waymo Driver: The core intelligence that handles driving.
The Simulator: A generative model that creates realistic, closed-loop synthetic environments for training [08:15].
The Critic: An opinionated model that identifies interesting events and judges whether a behavior was “good” or “bad” [09:18].
Distillation: These large teacher models are then “distilled” into smaller, highly efficient “student” models that can run real-time inference on the vehicle’s onboard computer [09:50].
Generalizability & “Zero-Shot” Learning
Dolgov emphasizes that Waymo is no longer in the “research” phase but in a “global scaling” phase, enabled by AI that generalizes across domains [23:57].
Inheriting World Knowledge: By hooking the Waymo Driver into VLMs, the system inherits general world knowledge. This allows for “zero-shot” or “few-shot” learning, where the car can understand new environments or signs without needing specific training data for every new city [25:30].
The “Tick-Tock” Cycle: Waymo’s scaling strategy mimics a hardware/software “tick-tock” cycle. Generation 6 features a brand-new custom vehicle and sensor stack (the “tick”), while keeping the software relatively consistent (the “tock”) to prove generalizability across different vehicle platforms [36:04].
Novel Technical Insights
“X-Ray” Vision through Multi-Modal Fusion: Dolgov shares a striking example where a Waymo vehicle “saw” a pedestrian through a bus. It wasn’t magic or literally seeing through metal; rather, the AI detected extremely noisy peripheral LiDAR reflections bouncing under the bus off the pedestrian’s feet. The models were sophisticated enough to interpret those few noisy bits as a human and predict their path [45:11].
Cloud vs. Local Inference: While all driving-critical inference happens locally on the car, Waymo uses the cloud for “nice-to-have” tasks. For example, after a ride, an offboard model checks the car for left-behind items or messes to decide if it needs to go to a cleaning depot [06:13].
Generative Simulation vs. Pixels: Dolgov explains the debate over “end-to-end” (pixels-to-actions) systems. He argues that while pure end-to-end is impressive (the “talking horse” effect), it is too inefficient for safety at scale. Waymo uses an augmented architecture that maintains intermediate representations (concepts like “roads” and “signs”) because they provide the “knobs” necessary to run efficient simulations and specify reward functions for the “Critic” [18:53].
Hardware: The 6th Generation & Cost Reduction
Custom Vehicle Design: The upcoming 6th generation is a custom-designed vehicle (not a derivative of a consumer car like the Jaguar I-PACE) featuring sliding doors, a flat floor, and a living-room-like interior [32:43].
Drastic Cost Reduction: The Gen 6 sensor stack is a “fraction of the cost” of previous versions, bringing the price of a fully autonomous hardware suite down to a level comparable to high-end consumer Driver Assist (ADAS) systems [35:40].
Sensor Strengths: He clarifies why LiDAR and Radar are both essential: while LiDAR provides fine-grained mapping, imaging radar is critical for high-speed freeway driving in dense fog because its physics allow it to see through particulates that blind cameras and LiDAR [39:13].
Operational Efficiency
The “Autonomous Dance”: Waymo depots are now highly automated. Cars automatically navigate to depots for charging or cleaning, use icons on their “sensor dome” to signal staff what they need (e.g., a cleaning emoji), and self-orchestrate their movements within the facility [52:14].
Global Expansion: As of the recording, Waymo is operating in 11 U.S. cities (with Nashville being the most recent “ghost city” launch) and is preparing to launch in * London and Tokyo [24:42].
Waymo published an update on the safety of its autonomous robotaxis.
Waymo tries to compare the safety of its vehicles to a human benchmark driving under the same scenarios (city, time of day, route, etc) to attempt an apples-to-apples comparison.
Lots of interesting data and charts.
One statistic: Waymo says their injury rate is 82% lower than a human driving under comparable scenarios.
The data are based on 220 million autonomous miles through March 2026. Their December report was based on 170 million miles, so looks like they are accruing 50 million miles in 3 months, or 200 million miles per year.
Having ridden waymo several times this month, a couple observations come to mind:
Local capacity of the waymo fleet is inflexible. As a result, wait times for a car can exceed 40 minutes, despite indication prior to booking that that arrival at destination is likely within 20 minutes. Routing, scheduling and planning for rideshares is not straight forward. I tried to address this by walking more than 10 blocks to a point which was significantly far away from my original request only to see that this is a grid scale capacity problem during peak times (this was 4pm on a Thursday in San Francisco). Dynamic pricing is present, but can’t help reduce demand sufficiently enough to encourage other potential riders to drop.
Waiting at stops can be longer than other ride share services. Other human drivers take advantage of autonomous vehicles at stop lights, signs and in traffic trains. Other drivers KNOW waymo rides will yield and will take advantage of it. In spite of MANY drivers pulling out DIRECTLY in front of the waymo along these trips, there was relatively little discomfort in the cabin, since the car starts reacting to it as soon as it’s reasonable that a person will do this. A few extra minutes can be planned for in advance(unless #1 is also present).
Waymo awareness. It is truly impressive to see what the system sees along the right. Videos above show it, but it’s even more impressive in person.
Ride customization. Having complete control (and no other human in the loop) has it’s perks. Seating arrangement, leg room, climate control, music or other ambient noise, auto unlock, etc. really make the experience anxiety free.
I’m looking forward to more and more of these services to be available - everywhere. Still more expensive than having a car (even a rental) if you don’t have to worry about parking. Dramatically safer than trusting a random stranger (even one with 5 stars on Uber, Lyft or taxi service)
Waymo is now providing commercial service to riders in 14 metro areas.
Today, we’ll begin welcoming our first public riders in Denver, San Diego, and Tampa, marking 14 cities where we’re providing riders fully autonomous trips.
The thing that is kind of maddening about the Tesla fast roll out narrative it is that it never made any sense.
The service areas need to be mapped, regulatory approval is needed from federal down to local in some cases, fleet service depots need to be constructed, remote monitors hired, etc. And of course, the technology needs to be improved.
All of those things can happen, but they need to happen (and are happening) in a slow deliberate manner. The notion thousands of cybercabs will be operating all over the country with a flick of the wrist is a fairy tale.