In 2015, Chris Urmson, then the leader of Google's autonomous vehicle project, said that one of his goals in developing a fully autonomous vehicle was to ensure his 11-year-old son would never need a driver's license.
The subtext was that in five years, when Urmson's son turned 16, self-driving cars would be so ubiquitous and the technology so superior to human driving, that his teenage son would have no need or desire to learn to drive himself. .
Well, it's 2024 and Urmson's son is now 20 years old. Any bets on him getting that driver's license?
One of the hallmarks of the race to develop autonomous vehicles has been the wildly optimistic predictions about when they will be ready for everyday use. The panorama is plagued by missed deadlines.
In 2015, Baidu Senior Vice President Wang Jing said the technology company would sell self-driving cars to Chinese customers by 2020. In 2016, then-Lyft President John Zimmer claimed that “the majority” of rides are made on their shared trips. The network would be on fully autonomous cars “within five years.” That same year, Business Insider He said that by 2020 there will be 10 million autonomous vehicles on the roads.
GM said it would mass produce self-driving cars, without a steering wheel or pedals, by 2019. Ford, a little more conservative, predicted it would do the same in 2021. And in a perfect encapsulation of the autonomy hype of the mid-2010s , Intel predicted an investment of 7 billion dollars in 2017. industry (more than double what the global automotive industry does now) around autonomy by 2050.
Of course, no one has been more optimistic than Tesla CEO Elon Musk, who has turned mispredictions about the readiness of autonomous vehicles into an art form.
Of course, no one has been more optimistic than Tesla CEO Elon Musk, who has turned mispredictions about the readiness of autonomous vehicles into an art form. “By the middle of next year, we will have over a million Tesla cars on the roads with fully self-driving hardware,” Musk said in 2019. Tesla's fully self-driving (FSD) feature would be so reliable that the driver could ” go to sleep.” Teslas with the company's FSD software are not autonomous, and drivers would be wise not to sleep in their cars.
Of course, there are some Self-driving cars on the roads today. They are in San Francisco, Phoenix, Los Angeles, Hamburg and Beijing, among other cities. They are operated by some of the largest and most well-capitalized companies in the world. You can even ride some of them.
But they are stuck. Not stuck in the sense that a Tesla Cybertruck gets stuck in less than an inch of snow. But confined within geofenced service areas, held back by their own technological shortcomings, opposed by unions and supporters of more reliable modes of transportation, and with restrictions on driving on certain roads or in certain weather conditions.
“The autonomous vehicle industry, particularly companies that develop and test robotaxis, has gotten away with selling a vision of the future for too long that they should know full well will never come true,” Sam Anthony, co-founder and director of technology. from Perceived Automata, a now defunct audiovisual company, he wrote in his newsletter in 2022.
We assumed that robots could drive as freely as we could. After all, we built a world in which humans can (and do) drive anywhere, anytime. So why are we so wrong?
Before examining why the industry collectively snubbed the launch of self-driving cars, it's instructive to look at why these predictions were made in the first place. Why set these goals if they never really mattered?
Of course, the answer is money. By promising that self-driving cars were “just around the corner” and about to take over our roads, companies were able to raise hundreds of billions of dollars to fund their experiments.
The amount of money flowing into the autonomous vehicle space has also had the ripple effect of convincing regulators to take a lax approach when it comes to autonomous vehicles. AV proponents warned that too many rules would “stifle innovation” and jeopardize future gains, whether security or job creation.
And it turns out that regulators were very receptive to those arguments. The federal government, whether under Obama, Trump or Biden, has done very little to hinder companies from testing their technology on public roads. A bill in Congress that would speed up the rollout of cars with steering wheels and pedals has stalled due to disagreements over liability, but you wouldn't know it by looking at these fundraising trips.
Some states, such as California, have gone to great lengths to produce some type of regulatory manual. But most were eager to attract companies under the belief that driverless cars were the future. And who wants to stand in the way of the future?
For almost a decade, audiovisual operators were able to raise money almost without restrictions.
For almost a decade, audiovisual operators were able to raise money almost without restrictions. They did this through normal fundraising channels or by linking up with big tech and automotive companies. Cruise Automation was acquired by General Motors. Ford invested $1 billion in Argo ai. Google, always slightly ahead of the rest, transformed its autonomous vehicle project into Waymo. Amazon bought Zoox. Hyundai allied with Motional. Some have estimated that more than $160 billion has flowed into the industry in the last twelve years.
And after the pandemic, companies that couldn't approach big automakers or tech giants found a new way to raise cash quickly: SPACs. Traditional IPOs were slow and special acquisition companies were fast, so dozens of mobility-focused startups went public by merging with these so-called “blank check” companies to access more money faster.
And despite a series of setbacks, including accidents, lawsuits and investigations, the cash kept coming. It wasn't until 2021, when the industry raised $12.5 billion, led by GM's Cruise, which raised a whopping $2.75 billion, that funding for AV companies peaked. .
Predictions about the imminent arrival of safe and reliable autonomous driving technology helped accelerate the flow of money. And once those predictions failed to materialize, the money began to dry up.
Why did the predictions fail? The technology, while incredibly effective in getting us most of the way, stumbled as it approached the finish line.
In the audiovisual world, this is called the “long tail of 9”. It's the idea that you can get a vehicle that's 99.9 percent as good as a human driver, but you never actually get to 100 percent. And that's because of edge cases, these unpredictable events that baffle even human drivers.
When you train an ai program on driving, you can predict a lot of what to expect, but you can't predict everything. And when those extreme cases finally arise, the car can make mistakes, sometimes with tragic consequences.
When you train an ai program on driving, you can predict a lot of what to expect, but you can't predict everything.
Take the example of Cruise. In October of last year, a woman was hit by a human driver while crossing the street in San Francisco. The impact sent her flying into the path of a driverless Cruise vehicle, which braked immediately after hitting her as well. The Cruise vehicle then attempted to pull over to the side of the road, not realizing that the woman was still trapped underneath the vehicle, further injuring her in the process.
One of the first things Cruise did after the incident was to recall the 950 vehicles it had on US roads. This took the form of an over-the-air update to the collision detection subsystem software so that the vehicle would remain stationary during certain crash incidents, rather than stopping on the side of the road. Cruise found a borderline case and quickly corrected it.
But how many more extreme cases lurk in the shadows? And how many more people will be injured (or even killed) before these cars are considered more reliable?
Waymo has been at the forefront of trying to convince the public and regulators that its vehicles are as safe, if not safer, than humans. He has published a series of studies and statistical analyzes in recent years that he claims show that his vehicles suffer fewer accidents, cause less damage, and improve overall safety on the roads.
But for every Waymo, there's an Elon Musk, whose misleading predictions about the imminent availability of autonomous vehicles muddy the waters for everyone else who knows reality is much further away than previously thought. Waymo also takes legal responsibility for accidents involving its vehicles, something Tesla has so far refused to do.
But Waymo isn't driving public perception of autonomous vehicles; Tesla is. Broken promises and failed predictions are fueling growing skepticism about autonomous vehicles among the public who, as the years go by, grow increasingly discouraged at the idea of handing over control of their vehicles to a robot.
Without passengers there is no business. But without safe and reliable technology, there is no future for autonomous vehicles.
