Wij willen met u aan tafel zitten en in een openhartig gesprek uitvinden welke uitdagingen en vragen er bij u spelen om zo, gezamelijk, tot een beste oplossing te komen.
Oftewel, hoe kan de techniek u ondersteunen in plaats van dat u de techniek moet ondersteunen.
GM has a “big team” working on an advanced version of its hands-free driving assistance system Super Cruise that will expand its capability beyond highways and apply it to city streets, the automaker’s vice president of global product development Doug Parks said Tuesday.
GM is also continuing to improve its existing Super Cruise product, Parks said during a webcasted interview at Citi’s 2020 Car of the Future Symposium.
“As we continue to ratchet up Super Cruise, we continue to add capability and not just highway roads,” Parks said, adding that a separate team is working on the hands-free city driving product known internally as “Ultra Cruise.”
“We’re trying to take that same capability off the highway,” he said. “Ultra cruise would be all of the Super Cruise plus the neighborhoods, city streets and subdivisions. So Ultra Cruise’s domain would be essentially all driving, all the time.”
Parks was quick to add that this would not be autonomous driving. Advanced driving assistance systems have become more capable, but they still require a human driver to take control and to be paying attention.
“What we’re not saying is that Ultra Cruise will be fully autonomous 100% of the time, although that could be one of the end games,” Parks said.
Parks didn’t provide a timeline for when Ultra Cruise might be available. A GM spokesperson said in a statement after his interview that the company continues to expand its hands-free driver assistance system technology across its vehicle portfolio and has “teams looking at how we can expand the capabilities to more scenarios.”
GM said it “does not have a name or anything specific to announce today, but stay tuned.”
This new Ultra Cruise feature would put it in competition with Tesla’s Autopilot advanced driving system, which is largely viewed as the most capable on the market today. Tesla’s “full self-driving” package, a more capable version of Autopilot, can now identify stop signs and traffic lights and automatically slows the car to a stop on approach. This feature is still considered to be in beta.
GM’s Super Cruise uses a combination of lidar map data, high-precision GPS, cameras and radar sensors, as well as a driver attention system, which monitors the person behind the wheel to ensure they’re paying attention. Unlike Tesla’s Autopilot driver assistance system, users of Super Cruise do not need to have their hands on the wheel. However, their eyes must remain directed straight ahead.
GM has taken a slower approach to Super Cruise compared to Tesla’s method of rolling out software updates that gives early access to some owners to test the improved features. When GM launched Super Cruise in 2017, it was only available in one Cadillac model — the full-size CT6 sedan — and restricted to divided highways. That began to change in 2019 when GM announced plans to expand where Super Cruise would be available.
GM’s new digital vehicle platform, which provides more electrical bandwidth and data processing power, enabled engineers to add to Super Cruise’s capabilities. In January, GM added a feature to Super Cruise that automated lane changes for drivers of certain Cadillac models, including the upcoming 2021 Escalade.
This enhanced version of Super Cruise includes better steering and speed control. The improved version will be introduced starting with the 2021 Cadillac CT4 and CT5 sedans, followed by the new 2021 Cadillac Escalade. The vehicles are expected to become available in the second half of 2020.
We’re still very much in the collaboration phase of autonomous driving, since it’s looking still quite a ways off from being anything consumers can use on the regular. That means there’s plenty of opportunity for things like the new “Autonomous Vehicle Computing Consortium” (AVCC) announced today to form. This industry group includes Arm, Bosch, Continental, GM, Toyota, Nvidia, NXP, and Denso, collecting top automakers along with some of the leading chipmakers and tier 1 suppliers in automotive today.
The group’s goal is to work together in order to “solve some of the most significant challenges to deploy self-driving vehicles at scale,” which pretty clearly translates into putting together the collective efforts of some of those who stand to gain most from autonomy becoming a commercially viable technology, in order to speed up said commercialization. While self-driving has been an area of intense investment and focus in the past few years, it still has a ways to go before these companies can start really reaping the rewards of their investments in terms of revenue-driving businesses.
So what will they actually do to achieve this goal? Step one will be setting up a set of recommended specs, essentially, outlining what size, temperature, power consumption and safety standards AV system architectures and computers should adhere to. The idea is that by arriving at some baseline standards, the group will be better able to move from prototyping, which is expensive and low-volume in terms of output, to manufacturing and deploying AVs at the scale where they’ll truly become a viable commercial enterprise.
There’s more to this industry collaboration than just figuring out the specs range for systems, however: Participating companies will “study common technical challenges,” as well, meaning they’ll be putting their heads together to overcome the major, fundamental tech challenges that still act as hurdles to be overcome in getting self-driving vehicles on the roads.
And of course, though the initial founding group includes only those companies listed above, this new group is also open to new members.
The VW electric ID Buggy concept is delightful and bright, stout and smiling. It’s a vehicle fit for the sunshine and sand dunes, or perhaps a less committing slow roll along the beach.
And so my first drive in a prototype of the all-electric buggy — along the coast near Spanish Bay in Monterey, Calif., — was tinged with sadness. After all, the ID Buggy is just a concept. It’s not meant for this world. At least not right now.
There is still a chance that the ID Buggy will make it to production. VW is already in talks with “at least one company” to bring the buggy into production, TechCrunch confirmed.
The global debut of the ID Buggy concept at the 89th Geneva International Motor Show in March was meant to showcase VW’s electric future and demonstrate the versatility of its modular electric drive toolkit chassis, or MEB. The MEB, which was introduced in 2016, is a flexible modular system — really a matrix of common parts — for producing electric vehicles that VW says make it more efficient and cost-effective.
The first vehicles to use this MEB platform will be under the ID brand, although this platform can and will be used for electric vehicles under other VW Group brands such as Skoda and Seat. (The MEB won’t be used by VW brands Audi or Porsche, which are developing their own platform for electric vehicles.)
VW has shown off several ID concepts. Some of these, like the ID Crozz and ID Buzz are going into production. A production version of the Crozz is coming to the U.S. at the end of 2020. Others, like this buggy, are not currently on the production track.
Driving the ID Buggy Drive
The ID Buggy is simple, and that’s exactly what it should be. No clutter or whiz-bang creature comforts. Instead, this leisure vehicle inspired by the 1960s era Meyers Manx has no roof or doors — although a tarpaulin can be stretched between the windscreen frame and the Targa bar as a sun sail or light weather protection. Without doors, the driver climbs in, and with relative ease, depending on one’s general fitness and flexibility.
The ID Buggy towers over its inspiration — the iconic Meyers Manx buggy that became popular among the California beach-and-surf culture of the 1960s.
The ID Buggy was also a quieter, smoother ride than the Meyers Manx. I also spent some time in a classic bright red buggy with a four-speed manual transmission and gas engine that might have been a touch carbureted. While the Manx roared as I shifted into first and peeled away, the electric ID Buggy was silent and smooth as it rolled out of the sandy parking lot.
The main detail inside the ID Buggy is the lack of features and do-dads. The hexagonal steering wheel, shown above, isn’t littered with toggles; there are just a couple of controls on the crossbar. A small integrated stock to the right side of the steering wheel allows the driver to move the vehicle into drive, reverse and park. A digital instrument cluster provides the basic information like speed.
Even the brake and accelerator pedals continue this stripped-down design story.
The dashboard and the passenger area are just as void of features. This lack of “stuff” is more about function than form, although the matte green and textured grey blue at the bottom does make a visual statement. The ID Buggy is meant to be driven in the elements, rain or shine. And so designers made the interior waterproof.
Under the ID Buggy’s body is where the good stuff lives.
The rear-wheel drive buggy is outfitted with an electric motor that produces 201 horsepower and a maximum torque of 228 pound-feet. It has a 62-kilowatt-hour battery that can travel 155 miles (under the WLTP standard) on a single charge. There is not an EPA estimate for the range. It can accelerate from a standstill to 62 miles per hour in 7.2 seconds.
Unfortunately, this prototype had a kill-the-thrill speed limiter on it, scuttling my plans for a zippy ride along the coast.
Still, the ID Buggy offered a fun and easy, breezy ride. It handled the curves of the roads with ease and its wide body and higher rear end provided a sense of security even while driving amid other much larger passenger cars.
Building the ID Buggy
It’s unclear what company, or companies, are in talks to produce the buggy. VW wouldn’t give names; not even the ocean breeze and cloudless sky or the endless supercar eye candy were enough to loosen the lips of VW employees during Monterey Car Week.
It’s possible that this unnamed company is e.Go Mobile. VW announced in March that e.Go Mobile would be its first external partner to use its MEB electric platform to launch other EVs in addition to Volkswagen’s model range. A dedicated vehicle project is already being planned, VW said at the time.
A VW spokesperson told TechCrunch there’s no decision about which car will be produced under this partnership with e.Go Mobile. It could be the buggy; it could also be some other vehicle.
And then there’s Ford. Earlier this year, the two automakers announced a partnership that includes Ford producing electric cars based on the MEB developed by Volkswagen.
The VW folks on the ground in Monterey did express hope that a third party does build the buggy, or a modified version of it. As one spokesperson later told TechCrunch, “As the drive in Monterey showed, the Buggy is a great ambassador for Volkswagen and for e-mobility. I am sure it would find a lot of customers.”
In the end, the ID Buggy is a sleek cruiser rather than a beach bomber like the 1960s original. It successfully demonstrates the versatility around VW’s electric platform. After all, Volkswagen foresees critical parts in the ID Buggy used to power multiple consumer electric vehicles in the near future. And it’s a fair assumption the ID Buggy’s production cousins will have a bit more gadgets, including silly things like doors.
Cao Xudong turned up on the side of the road in jeans and a black T-shirt printed with the word “Momenta,” the name of his startup.
Before founding the company — which last year topped $ 1 billion in valuation to become China’s first autonomous driving “unicorn” — he’d already led an enviable life, but he was convinced that autonomous driving would be the real big thing.
Cao isn’t just going for the moonshot of fully autonomous vehicles, which he says could be 20 years away. Instead, he’s taking a two-legged approach of selling semi-automated software while investing in research for next-gen self-driving tech.
Cao, pronounced ‘tsao’, was pursuing his Ph.D. in engineering mechanics when an opportunity came up to work at Microsoft’s fundamental research arm in Asia, putatively the “West Point” for China’s first generation of artificial intelligence experts. He held out there for more than four years before quitting to put his hands on something more practical: a startup.
“Academic research for AI was getting quite mature at the time,” said now 33-year-old Cao in an interview with TechCrunch, reflecting on his decision to quit Microsoft. “But the industry that puts AI into application had just begun. I believed the industrial wave would be even more extensive and intense than the academic wave that lasted from 2012 to 2015.”
In 2015, Cao joined SenseTime, now the world’s highest-valued AI startup, thanks in part to the lucrative face-recognition technology it sells to the government. During his 17-month stint, Cao built the company’s research division from zero staff into a 100-people strong team.
Before long, Cao found himself craving for a new adventure again. The founder said he doesn’t care about the result as much as the chance to “do something.” That tendency was already evident during his time at the prestigious Tsinghua University, where he was a member of the outdoors club. He wasn’t particularly drawn to hiking, he said, but the opportunity to embrace challenges and be with similarly resilient, daring people was enticing enough.
And if making driverless vehicles would allow him to leave a mark in the world, he’s all in for that.
Make the computer, not the car
Cao walked me up to a car outfitted with the cameras and radars you might spot on an autonomous vehicle, with unseen computer codes installed in the trunk. We hopped in. Our driver picked a route from the high-definition map that Momenta had built, and as soon as we approached the highway, the autonomous mode switched on by itself. The sensors then started feeding real-time data about the surroundings into the map, with which the computer could make decisions on the road.
Momenta staff installing sensors to a testing car. / Photo: Momenta
Momenta won’t make cars or hardware, Cao assured. Rather, it gives cars autonomous features by making their brains, or deep-learning capacities. It’s in effect a so-called Tier 2 supplier, akin to Intel’s Mobileye, that sells to Tier 1 suppliers who actually produce the automotive parts. It also sells directly to original equipment manufacturers (OMEs) that design cars, order parts from suppliers and assemble the final product. Under both circumstances, Momenta works with clients to specify the final piece of software.
Momenta believes this asset-light approach would allow it to develop state-of-the-art driving tech. By selling software to car and parts makers, it not only brings in income but also sources mountains of data, including how and when humans intervene, to train its codes at relatively low costs.
The company declined to share who its clients are but said they include top carmakers and Tier 1 suppliers in China and overseas. There won’t be many of them because a “partnership” in the auto sector demands deep, resource-intensive collaboration, so less is believed to be more. What we do know is Momenta counts Daimler AG as a backer. It’s also the first Chinese startup that the Mercedes-Benz parent had ever invested in, though Cao would not disclose whether Daimler is a client.
“Say you operate 10,000 autonomous cars to reap data. That could easily cost you $ 1 billion a year. 100,000 cars would cost $ 10 billion, which is a terrifying number for any tech giant,” Cao said. “If you want to acquire seas of data that have a meaningful reach, you have to build a product for the mass market.”
Highway Pilot, the semi-autonomous solution that was controlling our car, is Momenta’s first mass-produced software. More will launch in the coming seasons, including a fully autonomous parking solution and a self-driving robotaxi package for urban use.
In the long run, the startup said it aims to tackle inefficiencies in China’s $ 44 billion logistics market. People hear about warehousing robots built by Alibaba and JD.com, but overall, China is still on the lower end of logistics efficiency. In 2018, logistics costs accounted for nearly 15 percent of national gross domestic product. In the same year, the World Bank ranked China 26th in its logistics performance index, a global benchmark for efficiency in the industry.
Cao Xudong, co-founder and CEO of Momenta / Photo: Momenta
Cao, an unassuming CEO, raised his voice as explained the company’s two-legged strategy. The twin approach forms a “closed loop,” a term that Cao repeatedly summoned to talk about the company’s competitive edge. Instead of picking between the presence and future, as Waymo does with Level 4 — a designation given to cars that can operate under basic situations without human intervention — and Tesla with half-autonomous driving, Momenta works on both. It uses revenue-generating businesses like Highway Pilot to fund research in robotaxis, and the sensor data collected from real-life scenarios to feed models in the lab. Results from the lab, in turn, could soup up what gets deployed on public roads.
Human or machine
During the 40-minute ride in midday traffic, our car was able to change lanes, merge into traffic, create distance from reckless drivers by itself except for one brief moment. Toward the end of the trip, our driver decided to grab the wheel for a lane change as we approached a car dangerously parked in the middle of the exit ramp. Momenta names this an “interactive lane change,” which it claims is designed to be part of its automated system and by its strict definition is not a human “intervention”.
“Human-car interaction will continue to dominate for a long time, perhaps for another 20 years,” Cao noted, adding the setup brings safety to the next level because the car knows exactly what the driver is doing through its inner-cabin cameras.
“For example, if the driver is looking down at their cellphone, the [Momenta] system will alert them to pay attention,” he said.
I wasn’t allowed to film during the ride, so here’s some footage from Momenta to give a sneak peek of its highway solution.
Human beings are already further along the autonomous spectrum than many of us think. Cao, like a lot of other AI scientists, believes robots will eventually take over the wheel. Alphabet-owned Waymo has been running robotaxis in Arizona for several months now, and smaller startups like Drive.ai are also offering a similar service in Texas.
Despite all the hype and boom in the industry, there remains thorny questions around passenger safety, regulatory schema and a host of other issues for the fast-moving tech. Uber’s fatal self-driving crash last year delayed the company’s future projects and prompted a public backlash. As a Shanghai-based venture capitalist recently suggested to me: “I don’t think humanity is ready for self-driving.”
The biggest problem of the industry, he argued, is not tech-related but social. “Self-driving poses challenges to society’s legal system, culture, ethics and justice.”
Cao is well aware of the contention. He acknowledged that as a company with the power to steer future cars, Momenta has to “bear a lot of responsibility for safety.” As such, he required all executives in the company to ride a certain number of autonomous miles so if there’s any loophole in the system, the managers will likely stumble across it before the customers do.
“With this policy in place, the management will pay serious attention to system safety,” Cao asserted.
Momenta’s new headquarters in Suzhou, China / Photo: Momenta
In terms of actually designing the software to be reliable and to trace accountability, Momenta appoints an “architect of system research and development,” who essentially is in charge of analyzing the black box of autonomous driving algorithms. A deep learning model has to be “explainable,” said Cao, which is key to finding out what went wrong: Is it the sensor, the computer, or the navigation app that’s not working?
Going forward, Cao said the company is in no rush to make a profit as it is still spending heavily on R&D, but he assured that margins of the software it sells “are high.” The startup is also blessed with sizable fundings, which Cao’s resume certainly helped attract, and so did his other co-founders Ren Shaoqing and Xia Yan, who were also alumni of Microsoft Research Asia.
As of last October, Momenta had raised at least $ 200 million from big-name investors including GGV Capital, Sequoia Capital, Hillhouse Capital, Kai-Fu Lee’s Sinovation Ventures, Lei Jun’s Shunwei Capital, electric vehicle maker NIO’s investment arm, WeChat operator Tencent and the government of Suzhou, which will house Momenta’s new 4,000 sq-meter headquarters right next to the city’s high-speed trail station.
When a bullet train speeds past Suzhou, passengers are able to see from their windows Momenta’s recognizable M-shape building, which, in the years to come, might become a new landmark of the historic city in eastern China.