Almost two years ago, Motional was at a self-driving vehicle crossroads.
The company, born out of a $4 billion joint venture between Hyundai Motor Group and Aptiv, had already missed a deadline to launch a driverless robotaxi service with partner Lyft. It had lost Aptiv as one of its financial backers, prompting Hyundai to step up with another $1 billion investment to keep it going. Several layoffs, including a 40 percent restructuring cut in May 2024, reduced the company from a peak of about 1,400 employees to fewer than 600. Meanwhile, advances in artificial intelligence were changing the way engineers developed technology.
Motion was going to evolve or die. Stop everything and choose option #1.
Motion told TechCrunch that it has restarted its robotaxi plans with an AI-first approach to self-driving and a promise to launch a commercial driverless service in Las Vegas by the end of 2026. The company has already opened a robotaxi service — with a human safety operator at the wheel — to its employees. It plans to bring that service to the public with an unnamed ride-hailing partner later this year. (Motional has existing relationships with Lyft and Uber.) By the end of the year, the human safety operator will retire from robotaxis and launch a true commercial driverless service, the company said.
“We saw that there was huge potential with all the advances that were happening in artificial intelligence, and we also saw that while we had a safe driverless system, there was a gap to get to an affordable solution that could be generalized and scaled globally,” Motional president and CEO Laura Major said during a presentation at the company’s Las Vegas facility. “And so we made the very difficult decision to stop our trading activities, to slow down in the short term so that we can accelerate.”
This meant moving away from its classic robotic approach to one based on artificial intelligence models. Motion has never lacked AI. Motional’s self-driving system used individual machine learning models to handle perception, tracking, and semantic reasoning. But it also used more rule-based programs for other functions within the software stack. And the individual ML models made it a complex network of software, Major said.
Meanwhile, AI models originally built for language began to be applied to robots and other natural AI systems, including the development of autonomous driving. This transformer architecture made it possible to build large and complex AI models, eventually leading to the emergence and launch of the use of ChatGPT.
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Motion looked for ways to combine these smaller models and integrate them into a single trunk, enabling an end-to-end architecture. It has also kept the smaller models for developers, which Major explained gives Motion the best of both worlds.
“This is really critical for two things: One is to generalize more easily to new cities, new environments, new scenarios,” he said. “And the other thing is to do that in a cost-optimized way. So, for example, the traffic lights might be different in the next city you go to, but you don’t have to redeploy them or re-analyze them. You just collect some data, train the model, and it’s able to operate safely in that new city.”
TechCrunch got a first-hand look at Motional’s new approach during a 30-minute self-drive in Las Vegas. A demonstration cannot provide an accurate assessment of a self-driving system. It can, however, identify weaknesses and differences from previous iterations and measure progress.
Progress is what I saw as the Hyundai Ioniq 5 I was riding in autonomously navigated its way down Las Vegas Boulevard and into the Aria Hotel pickup and drop-off area. These busy areas are notorious in Las Vegas, and my experience was no different, as the self-driving vehicle slowly drove around a stopped taxi and unloaded passengers, changed lanes, and then came back again, passing dozens of people, giant pots, and cars along the way.
Motion previously operated a ride-hailing service in Las Vegas with partner Lyft using vehicles that would autonomously operate portions of a route. Parking lots and pick-up areas with valet and apps were never part of these features. A human safety operator, always behind the wheel, would take over navigating parking lots or busy hotel lobby pick-up and drop-off points.
There is still more progress to be made. The graphics displayed to riders inside the vehicle are still under development. And while there was never a disengagement during my test drive — which means the human safety operator takes over — the vehicle took its time pushing around a double-parked Amazon delivery truck.
However, Major maintains that Motional is on track to grow safely and cost-effectively. And Hyundai’s majority owner is in it for the long haul, he said.
“I think the real long-term vision, you know, for all of this, is to put Level 4 in people’s personal cars,” Major said, referring to a term that means the system handles all the driving without expecting human intervention. “Robotaxis, that’s the number one attitude and a huge impact. But ultimately, I think every OEM would like to incorporate that into their cars as well.”
