Editor’s note: A version of this article originally appeared in the author’s newsletter, Exponential View.
When people ask me to describe my work, I say I take a critical look at exponential technologies—which I define as technologies that follow an exponential growth curve. I’m the founder of the research group
Exponential View, and my mission also includes critically reviewing my own analyses.
So here’s a reflection on my analyses of autonomous vehicles. I have long argued that self-driving cars are metaphorically miles away from being a reality. For years, I’ve tried to offer a tonic to the rah-rah hype that carmakers were foisting upon us through marketing.
In 2017, when many carmakers were promising that fully autonomous vehicles would be on the road imminently, I
wrote in MIT Technology Review:
KITT, the car from
Knight Rider, will remain the gold standard for autonomous vehicles. Autonomous vehicle pilots will become increasingly ambitious, but the real-world hurdles will still take time to navigate, even with friendly city regulators. None will ship to the public in 2018.
Five years later, I remained pessimistic, as
I wrote in my newsletter,Exponential View:
Max Chalkin analyzes the disappointing trajectory of full self-driving efforts: US $100 billion invested and little to show. The self-driving pioneer Anthony Levandowski, who cofounded Waymo, has retreated to building autonomous trucks constrained to industrial sites. He reckons that is the most complex use case the technology can deliver in the near future.
Why it matters: Self-driving could be a pointless distraction for improving the environmental and human impact of transport. It takes attention away from micromobility, better urban infrastructure, and other strategies to improve the safety, pollution, climate, equity and economic returns of this sector.
That was then and this is now. KITT remains awesome and I’m changing my mind about self-driving cars. Far from being a “pointless distraction,” they’re nearly ready for prime time. And robotaxis are leading the charge.
That’s not just based on a hunch. It’s based on an increasing mountain of evidence pointing to their adoption and evolution—evidence that the industry is making progress on overlapping “S-curves.” These S-curves in technology typically show slow initial progress, followed by rapid advancement, and then a leveling off as the technology matures. Here’s how I’m thinking about the development of self-driving cars now.
Two autonomous taxis, from Pony.ai and Baidu’s Apollo Go, cross paths in Beijing. VCG/Getty Images
Baidu and Waymo Robotaxis Show the Way
In bellwether cities that have historically been ahead of the curve on tech adoption, we’re seeing more self-driving vehicles on the road—with robotaxis spearheading this revolution. Wuhan, the capital of China’s Hubei province, is striving to become “the world’s first driverless city.” So far, around three in every 100 taxis there are robotaxis, developed by Baidu’s autonomous car division, Apollo Go.
Over the past year, San Francisco has seen a rapid increase in Waymo rides. And as Alphabet’s autonomous vehicle company expands beyond San Francisco, so do its numbers: According to data from the California Public Utilities Commission, in August Waymo provided approximately 312,000 rides per month in California, doubling its ride volume from only three months before.
These numbers highlight how quickly robotaxis can grab market share. While it’s not clear what proportion of Waymo’s 312,000 monthly rides in California happens in San Francisco alone, the city is the company’s most mature market, so it likely accounts for the bulk of rides—let’s estimate 80 percent.
That gives us a direct comparison with Uber’s staffed rideshare service, which runs approximately 200,000 rides a day in San Francisco. Given Waymo’s 312,000-a-month figure, the company likely offers 8,000 or more rides per day in the city, a 4 percent or more market share. The tipping point in S-curves of adoption is typically 6 percent, signaling the beginning of a rapid growth phase, so Waymo is getting closer.
Meanwhile, Baidu leads in driving down the cost of robotaxi journeys. A 10-kilometer (6.2-mile) ride in a robotaxi in Wuhan costs
between 4 and 16 yuan ($0.60 to $2.30), whereas an equivalent ride in a car driven by a human costs between 18 and 30 yuan. Anecdotally, a Waymo ride in San Francisco often costs slightly more than an Uber.
Because a robotaxi doesn’t contend with driver fatigue, the number of rides it can run per day can be greater than that of a nonautomated taxi. In Wuhan, a robotaxi completes up to
20 rides a day, which exceeds the daily average of 13.2 rides for human taxi drivers in the city.
What about the economics? Baidu operated around
336,000 Apollo Go rides in July 2024. At the prices mentioned above, this means that Baidu Apollo could be grossing $200,000 to $800,000 per month, or $2.4 million to $9.6 million per year. The Apollo costs only $28,000 to build, so it’s much cheaper than a Waymo car, which is estimated to cost $150,000.
Baidu Apollo looks likely to reach profitability before its U.S. peer (setting aside all the prior investment in R&D): The firm
expects to break even this year and to become profitable in 2025. Waymo also has a path to profitability but will face challenges from the incumbents. For example, the British autonomous vehicle company Wayve recently announced a partnership with Uber. So there may be a few bumps in the road for Waymo.
Selling Self-Driving Cars to Suburbia
Of course, history is littered with technologies that excited early adopters but didn’t cut through to the masses. Yet here too I see evidence that self-driving vehicles—in their initial form of robotaxis—are starting to burst out of the tech bubble.
Waymo is expanding its self-driving taxi service as regulators become more accepting of autonomous vehicles. Already established in San Francisco and Phoenix, Waymo has recently launched in
Los Angeles and Austin, Texas. The company is also testing operations in 25 other major metro areas, including Atlanta, Dallas, Houston, Miami, and New York City. To be sure, Waymo is cherry-picking cities with favorable conditions for autonomous vehicles. Regardless, its expansion signals the increasing acceptance of self-driving technology in urban transportation.
Beyond robotaxis, the public is becoming more comfortable with the tech, too. I believe that
Tesla is far behind the likes of Waymo when it comes to self-driving technology, but the growing popularity of Tesla cars is helping normalize the tech. Tesla’s full self-driving mode is available to drivers all over the United States and Canada and is expected to roll out in China in early 2025. The more hands-on experience—or hands-off, as the case may be—people get with self-driving tech, the more willing they will be to set aside their worries and prejudices about it.
We see this shift reflected in surveys of people’s trust in autonomous vehicles. Respondents in Phoenix and San Francisco who have been exposed to self-driving cars gave a confidence score of 67 in a
2023 survey, while the average American gave a score of 37.
For meaningful adoption to occur, autonomous vehicle companies first need to address major safety concerns. In October of last year, a pedestrian was hit by a human-driven Nissan and then
struck and dragged for 6 meters (20 feet) by a Cruise self-driving car on a San Francisco street. This event led to Cruise losing its operating permit in California and ceasing operations in Arizona and Texas. It was an awful accident and a moment of reflection for the self-driving car sector.
But the fact is that self-driving cars are getting safer. If we measure Waymo’s performance by kilometers per disengagement—those times when a human has to take control—its record has been improving over the long run. In the chart below, the dip in kilometers per disengagement in 2021 is due to several factors: The company introduced new vehicles, increased the number of kilometers driven by 270 percent compared to 2020, and
shifted its focus from Mountain View, Calif., to San Francisco, which is a more complex driving environment. Despite that blip, the overall trend line is clear.
Self-driving cars are also perceived to be safer than vehicles driven by humans. Some cyclists, for example, say they feel safer biking next to a Waymo car than a human-driven vehicle because the Waymo’s actions are more predictable.
“As a cyclist, when I ride my bike and I get next to a
@Waymo. I know it watches me, and if I try to pass it on the right, it makes room for me. I feel so much safer because it always sees me. It will never get in my way. It will never cut me off. It will always prioritize my safety over itself,” one cyclist wrote on X.
Improvements to Self-Driving Tech
The two overlapping S-curves of self-driving cars add up to true technological innovation and exponential growth. First, we have the S-curve of technology improvement.
Autonomous vehicle leaders have taken different approaches to building their technology on three axes: sensors, maps, and intelligence. Waymo and Apollo are perhaps the most similar. Their cars are multisensorial, kitted out with cameras, lidar, and radar. They rely on high-definition custom maps. And the intelligence in both Waymo and Baidu vehicles are complex architectures that combine several AI systems to make decisions.
At the other extreme is Tesla, which uses only cameras, maps, and end-to-end deep learning—meaning that it has one AI system that takes in raw sensor data and produces driving decisions as outputs. Wayve also uses end-to-end deep learning but is agnostic about its use of sensors. Current Wayve cars rely on cameras; future ones will use other sensors when available.
The question of which technology will win out is superinteresting but beyond the scope of this essay. The one thing I’ll emphasize, though, is that competing approaches are a good thing. The proof of the improvement is in the data: falling rates of disengagement, at least for Waymo, Wayve, and Apollo.
As for safety,
Missy Cummings, a professor at George Mason University and a leading expert on autonomous transport, shared with me as-yet-unpublished data regarding self-driving cars’ progress. Her data shows that Waymo cars have a lower crash rate than the average rideshare driver, albeit still worse than a typical human.
We’re reaching a tipping point where the technology is not just functional, but increasingly reliable and commercially viable. And handily, the S-curve of technology improvement is overlapping with another one: the adoption curve. Combined, Waymo’s growth in San Francisco and Baidu’s mass experiments in Wuhan begin to look like proof that we have worked out how to deliver robotaxis at scale.
Adoption so far has been in robotaxis because companies can deploy them at scale and because their trips are fairly constrained and predictable. If Waymo’s vehicles can navigate hundreds of thousands of trips successfully each week and train subsequent AI models on that data, it gives me confidence that self-driving vehicles can be used for everyday trips, by everyday people, in cities around the world.
S-curves sometimes reveal paradigm shifts. And it feels like we’re on the cusp of one with self-driving vehicles.
Where Self-Driving Cars Go from Here
So what might happen next? History has shown that technology transitions can take place within a window of less than 20 years. Feature phones were
almost entirely replaced by smartphones in just seven years. It took 14 years for the motorcar to go from 5 percent to 75 percent market share in American cities, almost entirely replacing the horse. Large sailboats ferrying immigrants from Europe to New York at the turn of the 19th century were replaced by the new technology of steamships within 15 years.
However, there is a wrinkle with self-driving vehicles. Regulators are wary of removing the human from the loop. The advancement of self-driving in the United States will depend on cities and states beyond the early tech adopters like San Francisco. And the U.S. National Highway Traffic Safety Administration has acted quickly against auto companies where it saw harm to the public. After the October 2023 accident, Cruise
recalled its entire fleet of robotaxis—nearly 1,200 vehicles—to close an investigation by the regulator.
By contrast, China’s ambition is on full display in Wuhan. The Chinese government has already approved live testing on public roads in
at least 16 other major cities. This rapid advance is due to China’s more directive government but also the public’s willingness to embrace the tech. Chinese consumers are twice as likely as Americans to say they trust self-driving vehicles. In June 2024 the Chinese government approved nine automakers to test systems that go further than Tesla’s full self-driving mode (which requires driver attention at all times). The China Society of Automotive Engineers foresees that one in five cars sold in China will be fully driverless by the decade’s end.
And what about Tesla? The company has a data advantage over Waymo: By April of this year, the firm had garnered more than 2 billion km (more than 1.3 billion miles) of experience under full self-driving (FSD) mode, and drivers had begun to add about 1.6 billion new km (about 1 billion miles) every two months. And yet, Tesla is miles behind Waymo both technically and operationally. As Chris Anderson, former editor in chief of Wired, pointed out in a post on X, Tesla’s FSD doesn’t work on his Bay Area commute.
“Having now had a chance to compare Tesla FSD 12.4 in San Francisco with Waymo, I don’t yet see how Tesla can field a robotaxi fleet anytime soon.
With the Tesla, I still get 3 to 4 disengagements in my daily 1.5-hour commute, which is really not bad. But there’s no room for any disengagements with a robotaxi. And Waymo does things like pulling over for fire engines, which Tesla doesn’t do.
I’m a Tesla bull, but a Waymo ride shows just how challenging true Level 5 autonomy is.”
I wouldn’t trust Tesla’s FSD on the roads around where I live in the United Kingdom. Just the adaptive cruise control on my Tesla is prone to jerks and sudden stops on the small highways in and around London. And even when Tesla’s FSD is competitive with Waymo’s cars from a driving experience standpoint, the firm will have fulfilled only one part of the robotaxi promise: the car. Operating a robotaxi fleet that deals with humans (forgetting their bags in the car, spilling coffee on the seats, and so on) is another layer of learning.
My sense is that much of the deployment in the next few years will be robotaxi services from firms like Waymo and Baidu’s Apollo that have figured out the technology and the operations. I suspect that once robotaxis gain a reasonable market share in any particular city, it will take about 10 more years for autonomous vehicles to gain widespread adoption there.
In truth, there is so much we don’t know about how these cars will be adopted in the social systems that are modern urban environments. From her forthcoming research, George Mason University’s Cummings tells me that between 2022 and 2023, 48 percent of all crashes from the main U.S. self-driving platforms occurred when the vehicles were rear-ended. For human drivers, only 29 percent of crashes are rear-enders. Is this a human problem or a robotaxi problem? Quite possibly it is both: Robotaxis may brake faster than a human driver’s reflexes.
The regulatory environment will determine how long it takes each market to adopt self-driving technology and find answers to these hard questions. The China Society of Automotive Engineers’ 2030 prediction may come to pass, or it may be bluster. In the United States, we’re probably talking about a couple of decades before consumers are buying self-driving cars in meaningful numbers. Globally, it’ll be longer than that.
Of course, entrepreneurs may carve up the transportation market in novel ways. For example,
Glydways, backed by the famed venture capitalist Vinod Khosla and OpenAI CEO Sam Altman, is using autonomous vehicles to provide high-density mass transit in cities such as Atlanta. Other bold entrepreneurs are developing autonomous air taxis. We might start to see a broad diversity of autonomous systems popping up around the world.
If there’s one thing I’ve learned from my pessimism in 2018 and 2022, it’s that things can change significantly and in a matter of only a few years. My view on robotaxis has flipped. They snuck up on me, and they’re now politely waiting to offer me a ride.
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