A Car Is Traveling At A Steady 80 Km H – Long before Big Tech took the wheel, Ernst Dickmanns launched a driverless Mercedes on European roads.
HOFOLDING, Germany — Other drivers wouldn’t have noticed anything unusual as two luxury cruisers with German license plates joined traffic on France’s Autobahn 1.
A Car Is Traveling At A Steady 80 Km H
But what they were witnessing – that sunny autumn day in 1994 – was something most of them would have dismissed as madness.
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It had taken a few calls from the German car lobby to convince the French authorities to give the green light. But here they are: two gray Mercedes 500 SELs, accelerating up to 130km / h, changing lanes and reacting to other cars, freely, with an on-board computer system that controls the steering wheel, accelerator pedal and brakes.
Decades before Google, Tesla and Uber entered the self-driving car business, a team of German engineers led by a scientist named Ernst Dickmanns had created a car that could drive French commuter traffic by itself.
The story of Dickmann’s invention, and how it was almost forgotten, is a clear example of how technology sometimes progresses: not by constant small steps, but by speed and speed, in impossible progress and inevitable retreat – “one step forward and step three behind. ,” as one AI researcher put it.
Ernst Dickmanns, a German scientist who tested autonomous cars on European roads in the 80s and 90s | Janosch Delcker for
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It’s also a kind of warning about the expectations we place on artificial intelligence and the limitations of some of the data-driven techniques used today.
“I stopped giving general advice to other researchers,” Dickmanns, now 82, said. “Just this: never forget the ways that were once so successful.”
Before becoming the man “who actually invented self-driving cars,” as Berkeley computer scientist Jitendra Malik put it, Dickmanns spent the first decade of his professional career analyzing the behavior of spacecraft as they reenter Earth’s atmosphere.
Trained as an aeronautical engineer, he quickly rose through the ranks of the West German aerospace community so that in 1975, still under 40, he secured a position at the new research university of the German armed forces.
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Three autonomous road vehicles at the PROMETHEUS demonstration in Paris, October 1994. From left to right: UniBwM VaMP, Daimler VITA-2, Daimler VITA-1 | Photo by Reinhold Behringer
By this time, he had already begun to think about what would soon become his life’s mission: teaching cars to see. The starting point, Dickmanns was more convinced, was not spaceships but cars. Within a few years he had bought a Mercedes, put computers, cameras and sensors in it, and by 1986 had started experimenting on university premises.
“His colleagues at the university said, well, he’s a genius, but he has a track record [of success in aerospace technology, ] so let’s get rid of him,” Dickmanns said during an interview at his family home, located steps away from onion. -Hofolding church, a small town outside Munich.
In 1986, Dickmanns van became the first self-driving car, on the skidpan of his university. The following year, an empty Bavarian still unopened took him down
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At a speed close to 90 kilometers per hour. Soon after, Dickmanns contacted the German car manufacturer Daimler. Together, they secured funding from a large Pan-European project and, in the early 1990s, the company came up with an idea that at first seemed “absurd” to Dickmanns.
“Can’t you prepare one of our supercars for the final show of the project in Paris in October [1994], and then drive it on a three-lane highway in public traffic?” he remembered the leaders asked.
He had to take a deep breath, “but then I told them that with my team and the methods we use, I think we have the ability to do it.”
Daimler has increased funding for the project. Car advocates have dispelled doubts within the French government. And in October 1994, the Dickmanns team picked up a group of high-ranking guests from Charles de Gaulle airport, drove them to a nearby road and put the two cars into self-driving mode.
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“Sometimes we took our hands off the wheel” – Reinhold Behringer, one of the engineers who sat in the driver’s seat during the demonstration
An engineer remained in the front seat of each car – with his hands on the wheel in case something went wrong – but the cars were moving.
“Sometimes, we would take our hands off the wheel,” said Reinhold Behringer, one of the engineers sitting in the driver’s seat during the demonstration, enthusiasm still in his voice 24 years later.
Newspapers published front-page stories about the protests, he recalled. And a year later, the Dickmanns team took the redesigned car on the longest journey, traveling more than 1,700 kilometers on the autobahn from Bavaria to Denmark, reaching speeds of more than 175 kilometers per hour.
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Soon, the project was completed. The technology that Dickmanns was using has reached its limit. Daimler has lost interest in funding the basic research needed to push it forward. Before long, the pioneering efforts of the Dickmanns were forgotten.
The history of artificial intelligence is one of bright springs followed by what researchers call “AI winters,” when attention and funding fade.
Dickmanns autopilot work began the first winter and ended a second after it began.
Artificial intelligence research – efforts to make machines do tasks that would otherwise require human thought – began in the late 1950s. From its early days, the field has been characterized by hype, leading to some ambitious researchers such as the economist Herbert Simon predicted in the 1960s that machines “will be able within 20 years to do any job that a human can do.” “.
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Spurred by such promises, funding exploded, but the technology didn’t work, and the bubble burst in the mid-1970s. Funds dwindled, and AI research was relegated to behind-the-scenes labs.
Inside the UniBwM VaMP test car, on the back bench where the computer system is installed for easy access and monitoring | Photo by Reinhold Behringer
The first winter of AI was one of the reasons why Dickmanns put his computer vision to work for himself in the early years. He knew, he said, that “people would say that the guy has a screw up somewhere.”
In the mid-80s, another spring of AI had arrived. His proof of concept generated enough interest to recruit a team that would eventually grow to 20 people before the 1994 Paris demonstration.
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“It was an interesting concept,” said Behringer, the engineer behind the wheel in Paris. “But for many it was still too far in the future.”
Technologists say there are two types of inventions: those like the light bulb, which have been used and improved since they were first invented. And those like super planes – remember Concorde? — which include revolutionary technological processes but are too advanced to last, at least at the time of their invention.
When he started making them in the early 1980s, it took a computer up to 10 minutes to scan the images. To drive autonomously, the car must respond to its environment, and to do so, Dickmanns calculated that the computer would need to scan at least 10 images per second.
Faced with what seemed an insurmountable obstacle, he was inspired by the human form. Cars, he decided, should be programmed to see the road as humans see their surroundings.
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Inside the UniBwM VaMP test car on a public highway in Denmark on November 11, 1995 | Photo by Reinhold Behringer
The human eye can only see a tiny dot in the center of its field of vision. Likewise, Dickmanns thought that a car should focus only on what is good for driving, such as road signs. This greatly reduced the amount of information the on-board computers had to process.
He also found other computational shortcuts: A significant amount of processing time was saved when Dickmanns realized that he didn’t need to use valuable processing power to store each image. He also programmed the car to learn from its mistakes, gradually improving its understanding of its environment.
Driving on the highway, it turns out, is one of the easiest tasks a self-driving car can accomplish. Conditions are well defined: traffic flows predictably, in one direction. The routes are clearly marked.
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And even then, the protest did not go perfectly. “It was a test,” Behringer said. “When, for example, there was a car in front of us covering the road signs and on the other side the road signs were flying, then the lane recognition function had problems.”
After the second AI winter began and the hype surrounding the Paris rally died down, Daimler told Dickmanns that he “wanted to have a product on the market as soon as possible,” he recalled. The automaker lost interest in its expensive basic research, which was unlikely to produce real software in the next few years.
“In retrospect, it was probably a mistake that the projects were not developed immediately,” said Jürgen Schmidhuber, co-director of the Dalle Molle Institute of
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