November 14, 2025 • 11 mins
Waymo now offers fully driverless Level 4 robotaxi rides on freeways in San Francisco, Los Angeles, and Phoenix, and it connects San Francisco to San Jose with curbside pickup at SJC. This expansion enables faster airport trips and cross metro rides without a safety driver and brings autonomous service to everyday commuter use cases.
Learn how highway driving, availability, safety protocols, pricing pressure, and competition from Uber, Tesla, and Zoox will shape self driving car adoption in 2025 across California and Arizona. Keywords to help discovery include robotaxi, autonomous vehicles, driverless rides, freeway routes, airport pickup, SJC, SF to San Jose, LA, Phoenix, reliability, and scale.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:03):
Your ultimate authority for daily Elon Musk news.
Exploring the world's biggest ideas with your host Will
Walden. There's something new every day.
So Waymo just switched on fully driverless freeway rides for
(00:23):
paying passengers in San Francisco, Los Angeles and
Phoenix. In the expansion connects SF to
San Jose with curbside access and Minita San Jose
International Airport. Now, is this the moment
robotaxis move from the city streets to true region to region
transportation that everyday riders will actually use?
(00:44):
Tesla does not do this yet. And freeways are the backbone of
how people travel in these metroareas.
So letting the service take the fastest route changes the value
of a robo taxi trip. Riders who were limited to
surface streets can now do airport runs, crosstown commutes
and city to suburb hops without a human being behind the wheel.
(01:06):
And the company says this rollout follows a steady safety
record in city driving. And it is extending that
approach to higher speeds and more complex merges.
Now freeway access is the unlockthat turns the novelty into a
network. The post break picture here is
simple. Then it gets nuanced.
(01:27):
First the capability. Vehicles can enter and exit
freeways, keep pace with traffic, and choose the route
that actually gets people there faster when the limited access
Rd. is best. Then this step arrives after
years of restricting service zones and gradual expansions in
the Bay Area and Phoenix, and after months of controlled roll
(01:49):
outs in Los Angeles neighborhoods.
What matters now is how the service scales across corridors
that millions of people rely on,and how Tesla responds.
And in practical terms, riders in the Bay Area can book trips
that include freeway segments between San Francisco and San
Jose, and they can get dropped curbside at the San Jose
(02:11):
airport. That removes one of the most
obvious gaps in earlier service maps where airport access and
cross peninsula travel forced route compromises.
LA riders should see more directrouting between neighborhoods
split by wide interstates, and Phoenix riders already familiar
with driverless trips can now use freeways when that is
(02:32):
objectively the quickest option.Now the company positions this
as a proof of generalization. The driver handled dense
downtown's first, then complex suburban arterioles, and now it
steps into sustained high speed traffic with more lane changes,
(02:53):
merges, and incident handling. The claim is not that freeways
are easier or safer by default, but that the system's perception
prediction in planning stack hasmatured enough to operate at
freeway speeds while maintainingits conservative margins.
You know the internal message isexpansion methodically, not a
(03:16):
single headline moment. They're not looking to grab
attention here. They are working to make a robo
taxi that can drive you from network to network, from city to
city, from state to state, all across the United States.
Now, this roll out also relies on clear playbooks for awkward
(03:39):
edge cases. And if a vehicle defects on the
freeway, it'll pull over safely.A response protocol in
coordination with Highway Patrolwill then avoid secondary
incidents. Those procedures exist in city
service, where cars can stop at curbs with freeway shoulders.
Ramps and interchanges demand different timing and
(04:02):
communication. Now.
The team says it has worked withauthorities on the scenarios,
and that collaboration will matter if the service is to keep
public confidence as miles accumulate.
Now scale is the other story, and the numbers point to a
service that has moved beyond pilots.
Public reporting from recent weeks describes more than 1500
(04:24):
vehicles in the fleet, with steady weekly ride counts in the
hundreds of thousands. And the mix is still anchored by
electric crossovers equipped with prioritary lidar, cameras,
radar, and onboard compute designed for redundancy.
Now, hardware matters here because freeway driving brings
sustained vibration, higher closing speeds, and the need to
(04:48):
read both lane level markings and long range signals well
enough to plan several 100 meters ahead.
And competitors know freeway credibility is the threshold
that you have to cross to Uber plans to treat field driverless
taxis in San Francisco use and lucid gravity SU VS with
(05:09):
autonomous technology from Nero moving beyond a booking
partnership into direct competition on those same
streets. And the interim goal is to build
toward more than 100 vehicles during the ramp.
And if schedule holds, Bay Area riders will compare 2 driverless
services next year and also Tesla.
And that will be coming up. And the deciding factors will be
(05:31):
reliability, pick up, latency, trip time and, of course, price.
Tesla is pushing a different path, though that still requires
an attentive human ready to steer or brake at any moment for
now. And the company markets the
experience with a robot taxi label in its app.
But the underlying system today is supervised driver assistance,
(05:52):
not a completely driverless service.
And that distinction matters on a highway, because a service
that requires human fall back cannot offer the same value
proposition as a fully unattended ride, and it cannot
claim the safety or availabilityprofile of a Level 4 fleet.
Now Amazon is in this, too. Zoox is expanding its own
(06:14):
footprint with free rides aroundthe Las Vegas Strip, and those
deployments will keep pressure on all players to show smooth
autonomy and complex traffic. But the bar for freeways is
completely different. It is not enough to handle
predictable loops. A driverless service has to
merge in heavy traffic, navigateunpredictable human behavior at
(06:34):
on ramps and off ramps, and keepsituational awareness across
multiple lanes at 55 to 70 mph. That is why this particular
expansion is seen as a marker oftechnical maturity rather than a
simple map update. And the policy backdrop is
moving in parallel. City and state officials are
trying to balance the promise offewer crashes and lower
(06:56):
emissions with reasonable guardrails for new risks.
Some local proposals would require a human operator and any
autonomous vehicle, which would collapse the economics that make
driverless service compelling. Others focus on incident
reporting, data sharing and coordination with first
responders, which can improve transparency without freezing
the technology in place. How those choices land will
(07:19):
shape where and how quickly freeway service rolls out next.
Safety investigations are part of the learning curve, too, and
everyone in the sector is dealing with them.
Reports or unexpected driving behavior have drawn federal
attention, and the result is a more formal feedback loop
between regulators and companies.
The outcome the public should watch for is not the absence of
(07:40):
scrutiny, but the presence of clear fixes, lower incident
rates over time, and better explanations of how the systems
are tested before features turn on.
For the general public and for riders, the litmus test is
simple. Does the car show up when the
app says it will pick a route that makes sense and complete
the trip without odd pauses or last minute reroutes?
(08:02):
Freeway access improves all three because a service can't
avoid fragile Surface St. shortcuts and take the obvious,
faster straight line path. It also enables more convincing
airport trips and cross metro rides that felt unnatural when
the car refused to enter on the highway and the business.
If a driver of this fleet can handle freeways reliability, it
(08:26):
can spread fixed costs across more miles, use vehicles more
hours per day, and price trips more competitively against ride
hail with human drivers. That is where the competitive
dynamic tightens. The player that proves it can do
this safely at scale with predictable margins will set the
preference point for the rest ofthe industry, and they may find
(08:46):
itself defining the regulatory expectations others must meet
now. The engineering leap took years
because the problem seems simpleand it's not.
The freeways look structured, but the emergent behavior is
messy. People are weird.
On the highway. A system has to predict whether
a driver 2 lanes over will dive across to make a really quick
(09:09):
exit and cut a bunch of people off, whether a stop vehicle on
the shoulder hides A pedestrian about to step into traffic, and
whether an object ahead is safe to straddle or requires a lane
change right now. And that demands perception
range, multi agent prediction and a planner that chooses
smooth human like decisions without taking risks a
professional safety driver wouldreject.
(09:30):
And they have to talk about different things.
Now you can hear how the rolloutis described.
It's not framed as a bold stunt or a sudden leap forward.
It's just calm. It's presented as the next
capability enabled by a driver that has already survived hard
miles in the city. Learn to deal with cut insurance
(09:51):
and builds up the operational protocols to handle the
exceptions. Now this company is connected
the dots between city service areas in the corridors that make
those areas feel like one region.
City to city, the competitive responses will keep coming, too.
Uber wants to become both the marketplace for other robotaxi
fleets and a direct operator. Tesla's pushing toward
(10:14):
unsupervised capability from a supervised base.
Zoox is packaging autonomy with purpose built vehicles, and each
path is coherent. But the freeway litmus test will
expose differences in system maturity, safety, performance,
and user experience quickly because riders do not forgive
weirdness at 70 mph. Now the next meaningful
(10:39):
questions are the ones riders will ask without thinking about
autonomy at all. How long a time until a curbside
pickup is available at more airports?
When will late night rides feel just as smooth as daytime trips?
And how quickly do service maps fill the gaps between
neighborhoods that still requireawkward detours?
The answers will come from miles, hundreds of thousands of
(11:02):
miles of usage. If freeway trips become routine,
volume will rise and the servicewill feel less like a pilot and
more like transport infrastructure you can rely on
any time of the day. Hey, thank you so much for
listening today. I really do appreciate your
support. If you could take a second and
hit this subscribe or the followbutton on whatever podcast
(11:24):
platform that you're listening on.
Right now I. Greatly appreciate it, it helps
out the show tremendously and you'll never miss an episode and
each episode is about 10 minutesor less to get you.
Caught up quickly and. Please, if you want to support
the show even more, go to. Patreon dot.
Com slash. Stage 0.
And please take care of yourselves and each other, and
(11:46):
I'll see you tomorrow.
Your ultimate authority for daily Elon Musk news.
Exploring the world's biggest ideas with your host Will
Walden. There's something new every day.
So Waymo just switched on fully driverless freeway rides for
(00:23):
paying passengers in San Francisco, Los Angeles and
Phoenix. In the expansion connects SF to
San Jose with curbside access and Minita San Jose
International Airport. Now, is this the moment
robotaxis move from the city streets to true region to region
transportation that everyday riders will actually use?
(00:44):
Tesla does not do this yet. And freeways are the backbone of
how people travel in these metroareas.
So letting the service take the fastest route changes the value
of a robo taxi trip. Riders who were limited to
surface streets can now do airport runs, crosstown commutes
and city to suburb hops without a human being behind the wheel.
(01:06):
And the company says this rollout follows a steady safety
record in city driving. And it is extending that
approach to higher speeds and more complex merges.
Now freeway access is the unlockthat turns the novelty into a
network. The post break picture here is
simple. Then it gets nuanced.
(01:27):
First the capability. Vehicles can enter and exit
freeways, keep pace with traffic, and choose the route
that actually gets people there faster when the limited access
Rd. is best. Then this step arrives after
years of restricting service zones and gradual expansions in
the Bay Area and Phoenix, and after months of controlled roll
(01:49):
outs in Los Angeles neighborhoods.
What matters now is how the service scales across corridors
that millions of people rely on,and how Tesla responds.
And in practical terms, riders in the Bay Area can book trips
that include freeway segments between San Francisco and San
Jose, and they can get dropped curbside at the San Jose
(02:11):
airport. That removes one of the most
obvious gaps in earlier service maps where airport access and
cross peninsula travel forced route compromises.
LA riders should see more directrouting between neighborhoods
split by wide interstates, and Phoenix riders already familiar
with driverless trips can now use freeways when that is
(02:32):
objectively the quickest option.Now the company positions this
as a proof of generalization. The driver handled dense
downtown's first, then complex suburban arterioles, and now it
steps into sustained high speed traffic with more lane changes,
(02:53):
merges, and incident handling. The claim is not that freeways
are easier or safer by default, but that the system's perception
prediction in planning stack hasmatured enough to operate at
freeway speeds while maintainingits conservative margins.
You know the internal message isexpansion methodically, not a
(03:16):
single headline moment. They're not looking to grab
attention here. They are working to make a robo
taxi that can drive you from network to network, from city to
city, from state to state, all across the United States.
Now, this roll out also relies on clear playbooks for awkward
(03:39):
edge cases. And if a vehicle defects on the
freeway, it'll pull over safely.A response protocol in
coordination with Highway Patrolwill then avoid secondary
incidents. Those procedures exist in city
service, where cars can stop at curbs with freeway shoulders.
Ramps and interchanges demand different timing and
(04:02):
communication. Now.
The team says it has worked withauthorities on the scenarios,
and that collaboration will matter if the service is to keep
public confidence as miles accumulate.
Now scale is the other story, and the numbers point to a
service that has moved beyond pilots.
Public reporting from recent weeks describes more than 1500
(04:24):
vehicles in the fleet, with steady weekly ride counts in the
hundreds of thousands. And the mix is still anchored by
electric crossovers equipped with prioritary lidar, cameras,
radar, and onboard compute designed for redundancy.
Now, hardware matters here because freeway driving brings
sustained vibration, higher closing speeds, and the need to
(04:48):
read both lane level markings and long range signals well
enough to plan several 100 meters ahead.
And competitors know freeway credibility is the threshold
that you have to cross to Uber plans to treat field driverless
taxis in San Francisco use and lucid gravity SU VS with
(05:09):
autonomous technology from Nero moving beyond a booking
partnership into direct competition on those same
streets. And the interim goal is to build
toward more than 100 vehicles during the ramp.
And if schedule holds, Bay Area riders will compare 2 driverless
services next year and also Tesla.
And that will be coming up. And the deciding factors will be
(05:31):
reliability, pick up, latency, trip time and, of course, price.
Tesla is pushing a different path, though that still requires
an attentive human ready to steer or brake at any moment for
now. And the company markets the
experience with a robot taxi label in its app.
But the underlying system today is supervised driver assistance,
(05:52):
not a completely driverless service.
And that distinction matters on a highway, because a service
that requires human fall back cannot offer the same value
proposition as a fully unattended ride, and it cannot
claim the safety or availabilityprofile of a Level 4 fleet.
Now Amazon is in this, too. Zoox is expanding its own
(06:14):
footprint with free rides aroundthe Las Vegas Strip, and those
deployments will keep pressure on all players to show smooth
autonomy and complex traffic. But the bar for freeways is
completely different. It is not enough to handle
predictable loops. A driverless service has to
merge in heavy traffic, navigateunpredictable human behavior at
(06:34):
on ramps and off ramps, and keepsituational awareness across
multiple lanes at 55 to 70 mph. That is why this particular
expansion is seen as a marker oftechnical maturity rather than a
simple map update. And the policy backdrop is
moving in parallel. City and state officials are
trying to balance the promise offewer crashes and lower
(06:56):
emissions with reasonable guardrails for new risks.
Some local proposals would require a human operator and any
autonomous vehicle, which would collapse the economics that make
driverless service compelling. Others focus on incident
reporting, data sharing and coordination with first
responders, which can improve transparency without freezing
the technology in place. How those choices land will
(07:19):
shape where and how quickly freeway service rolls out next.
Safety investigations are part of the learning curve, too, and
everyone in the sector is dealing with them.
Reports or unexpected driving behavior have drawn federal
attention, and the result is a more formal feedback loop
between regulators and companies.
The outcome the public should watch for is not the absence of
(07:40):
scrutiny, but the presence of clear fixes, lower incident
rates over time, and better explanations of how the systems
are tested before features turn on.
For the general public and for riders, the litmus test is
simple. Does the car show up when the
app says it will pick a route that makes sense and complete
the trip without odd pauses or last minute reroutes?
(08:02):
Freeway access improves all three because a service can't
avoid fragile Surface St. shortcuts and take the obvious,
faster straight line path. It also enables more convincing
airport trips and cross metro rides that felt unnatural when
the car refused to enter on the highway and the business.
If a driver of this fleet can handle freeways reliability, it
(08:26):
can spread fixed costs across more miles, use vehicles more
hours per day, and price trips more competitively against ride
hail with human drivers. That is where the competitive
dynamic tightens. The player that proves it can do
this safely at scale with predictable margins will set the
preference point for the rest ofthe industry, and they may find
(08:46):
itself defining the regulatory expectations others must meet
now. The engineering leap took years
because the problem seems simpleand it's not.
The freeways look structured, but the emergent behavior is
messy. People are weird.
On the highway. A system has to predict whether
a driver 2 lanes over will dive across to make a really quick
(09:09):
exit and cut a bunch of people off, whether a stop vehicle on
the shoulder hides A pedestrian about to step into traffic, and
whether an object ahead is safe to straddle or requires a lane
change right now. And that demands perception
range, multi agent prediction and a planner that chooses
smooth human like decisions without taking risks a
professional safety driver wouldreject.
(09:30):
And they have to talk about different things.
Now you can hear how the rolloutis described.
It's not framed as a bold stunt or a sudden leap forward.
It's just calm. It's presented as the next
capability enabled by a driver that has already survived hard
miles in the city. Learn to deal with cut insurance
(09:51):
and builds up the operational protocols to handle the
exceptions. Now this company is connected
the dots between city service areas in the corridors that make
those areas feel like one region.
City to city, the competitive responses will keep coming, too.
Uber wants to become both the marketplace for other robotaxi
fleets and a direct operator. Tesla's pushing toward
(10:14):
unsupervised capability from a supervised base.
Zoox is packaging autonomy with purpose built vehicles, and each
path is coherent. But the freeway litmus test will
expose differences in system maturity, safety, performance,
and user experience quickly because riders do not forgive
weirdness at 70 mph. Now the next meaningful
(10:39):
questions are the ones riders will ask without thinking about
autonomy at all. How long a time until a curbside
pickup is available at more airports?
When will late night rides feel just as smooth as daytime trips?
And how quickly do service maps fill the gaps between
neighborhoods that still requireawkward detours?
The answers will come from miles, hundreds of thousands of
(11:02):
miles of usage. If freeway trips become routine,
volume will rise and the servicewill feel less like a pilot and
more like transport infrastructure you can rely on
any time of the day. Hey, thank you so much for
listening today. I really do appreciate your
support. If you could take a second and
hit this subscribe or the followbutton on whatever podcast
(11:24):
platform that you're listening on.
Right now I. Greatly appreciate it, it helps
out the show tremendously and you'll never miss an episode and
each episode is about 10 minutesor less to get you.
Caught up quickly and. Please, if you want to support
the show even more, go to. Patreon dot.
Com slash. Stage 0.
And please take care of yourselves and each other, and
(11:46):
I'll see you tomorrow.
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