Transportation

Waymo launches robotaxi app on Google Play

Posted by | Android, Apps, automotive, electric vehicles, Google, Lyft, robotaxi, self-driving car, self-driving cars, transport, Transportation, Uber, waymo | No Comments

Waymo is making its ride-hailing app more widely available by putting it on the Google Play store as the self-driving car company prepares to open its service to more Phoenix residents.

The company, which spun out to become a business under Alphabet, launched a limited commercial robotaxi service called Waymo One in the Phoenix area in December. The Waymo One self-driving car service, and accompanying app, was only available to Phoenix residents who were part of its early rider program, which aimed to bring vetted regular folks into its self-driving minivans.

Technically, Waymo has had Android and iOS apps for some time. But interested riders would only gain access to the app after first applying on the company’s website. Once accepted to the early rider program, they would be sent a link to the app to download to their device.

The early rider program, which launched in April 2017, had more than 400 participants the last time Waymo shared figures. Waymo hasn’t shared information on how many people have moved over to the public service, except to say “hundreds of riders” are using it.

Now, with Waymo One launching on Google Play, the company is cracking the door a bit wider. However, there will be still be limitations to the service.

Interested customers with Android devices can download the app. Unlike a traditional ride-hailing service, like Uber or Lyft, this doesn’t mean users will get instant access. Instead, potential riders will be added to a waitlist. Once accepted, they will be able to request rides in the app.

These new customers will first be invited into Waymo’s early rider program before they’re moved to the public service. This is an important distinction, because early rider program participants have to to sign non-disclosure agreements and can’t bring guests with them. These new riders will eventually be moved to Waymo’s public service, the company said. Riders on the public service can invite guests, take photos and videos and talk about their experience.

“These two offerings are deeply connected, as learnings from our early rider program help shape the experience we ultimately provide to our public riders,” Waymo said in a blog post Tuesday.

Waymo has been creeping toward a commercial service in Phoenix since it began testing self-driving Chrysler Pacifica minivans in suburbs like Chandler in 2016.

The following year, Waymo launched its early rider program. The company also started testing empty self-driving minivans on public streets that year.

Waymo began in May 2018 to allow some early riders to hail a self-driving minivan without a human test driver behind the wheel. More recently, the company launched a public transit program in Phoenix focused on delivering people to bus stops and train and light-rail stations.

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Alibaba will let you find restaurants and order food with voice in a car

Posted by | alibaba, alibaba group, alipay, Android, Asia, automotive, AutoNavi, Baidu, Beijing, China, Emerging-Technologies, in-car apps, online marketplaces, operating system, operating systems, order food, shanghai, taobao, Tencent, Transportation | No Comments

Competition in the Chinese internet has for years been about who controls your mobile apps. These days, giants are increasingly turning to offline scenarios, including what’s going on behind the dashboard in your car.

On Tuesday, Alibaba announced at the annual Shanghai Auto Show that it’s developing apps for connected cars that will let drivers find restaurants, queue up and make reservations at restaurants, order food and eventually complete a plethora of other tasks using voice, motion or touch control. Third-party developers are invited to make their in-car apps, which will run on Alibaba’s operating system AliOS.

Rather than working as standalone apps, these in-car services come in the form of “mini apps,” which are smaller than regular ones in exchange for faster access and smaller file sizes, in Alibaba’s all-in-one digital wallet Alipay . Alibaba has other so-called “super apps” in its ecosystem, such as marketplace Taobao and navigation service AutoNavi, but the payments solution clearly makes more economic sense if Alibaba wants people to spend more while sitting in a four-wheeler.

There’s no timeline for when Alibaba will officially roll out in-car mini apps, but it’s already planning for a launch, a company spokesperson told TechCrunch.

Making lite apps has been a popular strategy for China’s internet giants operating super apps that host outside apps, or “mini-apps”; that way users rarely need to leave their ecosystems. These lite apps are known to be easier and cheaper to build than a native app, although developers have to make concessions, like giving their hosts a certain level of access to user data and obeying rules as they would with Apple’s App Store. For in-car services, Alibaba says there will be “specific review criteria for safety and control” tailored to the auto industry.

alios cars alibaba

Photo source: Alibaba

Alibaba’s move is indicative of a heightened competition to control the operating system in next-gen connected cars. For those who wonder whether the e-commerce behemoth will make its own cars given it has aggressively infiltrated the physical space, like opening its own supermarket chain Hema, the company’s solution to vehicles appears to be on the software front, at least for now.

In 2017, Alibaba rebranded its operating system with a deep focus to put AliOS into car partners. To achieve this goal, Alibaba also set up a joint venture called Banma Network with state-owned automaker SAIC Motor and Dongfeng Peugeot Citroen, which is the French car company’s China venture, that would hawk and integrate AliOS-powered solutions with car clients. As of last August, 700,000 AliOS-powered SAIC vehicles had been sold.

Alibaba competitors Tencent and Baidu have also driven into the auto field, although through slightly different routes. Baidu began by betting on autonomous driving and built an Android-like developer platform for car manufacturers. While the futuristic plan is far from bearing significant commercial fruit, it has gained a strong foothold in self-driving with the most mileage driven in Beijing, a pivotal hub to test autonomous cars. Tencent’s car initiatives seem more nebulous. Like Baidu, it’s testing self-driving and like Alibaba, it’s partnered with industry veterans to make cars, but it’s unclear where the advantage lies for the social media and gaming giant in the auto space.

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Movo grabs $22.5M to get more cities in LatAm scooting

Posted by | Argentina, brazil, Cabify, Chile, Colombia, e-mopeds, e-scooters, Europe, Fundings & Exits, Gadgets, latin america, madrid, Mexico, micromobility, Mobile, Movo, Recent Funding, seaya ventures, spain, Startups, Transportation, uruguay | No Comments

Madrid-based micromobility startup Movo has closed a €20 million (~$22.5M) Series A funding round to accelerate international expansion.

The 2017-founded Spanish startup targets cities in its home market and in markets across LatAm, offering last-mile mobility via rentable electric scooters (e-mopeds and e-scooters) plotted on an app map. It’s a subsidiary of local ride-hailing firm Cabify, which provided the seed funding for the startup.

Movo’s Series A round is led by two new investors: Insurance firm Mutua Madrileña, doubtless spying strategic investment potential in helping diversify its business by growing the market for humans to scoot around cities on two wheels — and VC fund Seaya Ventures, an early investor in Cabify.

Both Mutua Madrileña and Seaya Ventures are now taking a seat on Movo’s board.

Commenting on the Series A in a statement, Javier Mira, general director of Mutua Madrileña, said: “The equity investment in Movo reflects Mutua Madrileña’s aspiration to respond to the new mobility needs that are emerging, and to the economic and social changes that are occurring and that are transforming our life habits.”

Movo currently operates in six cities across five countries — Spain, México, Colombia, Perú and Chile.

It first launched an e-moped service in Madrid a year ago, according to a spokeswoman, and has since expanded domestic operations to the southern Spanish coastal city of Malaga, as well as riding into Latin America.

The new funding is mostly pegged for further international expansion, with a plan to expand into new markets in LatAm, including Argentina, Brazil and Uruguay. Movo is targeting operating in a total of 10 countries by the end of 2019.

The Series A will also be used to grow its vehicle fleet in existing markets, it said.

“We are very excited to be able to offer a solution to the problems of mobility in cities, particularly for short distances in areas with high population density,” said CEO Pedro Rivas in a statement. “We are committed to working together with governments to complement mass public transport with these new micromobility alternatives, so that people can get around in a more sustainable and efficient way.”

Commenting on its investment in the Cabify subsidiary, Seaya Ventures’ Beatriz Gonzalez, founder and managing partner, said the fund is “committed to the evolution of mobility towards sustainable alternatives in the world’s major cities.”

“We want to be part of the transport revolution by promoting projects like Cabify and, of course, Movo,” she said in a statement, which seeks to paint micromobility as a solution for urban congestion and poor air quality. “We are motivated to continue to promote companies with which we share this sense of responsibility towards the development and improvement of people’s quality of life.”

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Flying taxis could be more efficient than gas and electric cars on long-distance trips

Posted by | automotive, flying cars, flying taxis, Gadgets, science, Transportation, University of Michigan | No Comments

Flying cars definitely sound cool, but whether they’re actually a good idea is up for debate. Fortunately they do seem to have some surefire benefits, among which you can now count improved efficiency — in theory, and on long trips. But it’s something!

Air travel takes an enormous amount of energy, since you have to lift something heavy into the air and keep it there for a good while. This is often faster but rarely more efficient than ground transportation, which lets gravity do the hard work.

Of course, once an aircraft gets up to altitude, it cruises at high speed with little friction to contend with, and whether you’re going 100 feet or 50 miles you only have to take off once. So University of Michigan researchers thought there might be a sweet spot where taking a flying car might actually save energy. Turns out there is… kind of. The team published their results today in Nature Communications.

The U-M engineers made an efficiency model for both ground transport and for electric vertical take-off and landing (VTOL) aircraft, based on specs from aerospace companies working on them.

“Our model represents general trends in the VTOL space and uses parameters from multiple studies and aircraft designs to specify weight, lift-to-drag ratio and battery-specific energy,” said study co-author Noah Furbush in a U-M news release.

They looked at how these various theoretical vehicles performed when taking various numbers of people various distances, comparing energy consumed.

As you might imagine, flying isn’t very practical for going a mile or two, since you use up all that energy getting to altitude and then have to come right back down. But at the 100-kilometer mark (about 62 miles) things look a little different.

For a 100 km trip, a single passenger in a flying car uses 35 percent less energy than a gas-powered car, but still 28 percent more than an electric vehicle. In fact, the flying car is better than the gas one starting at around 40 km. But it never really catches up with the EVs for efficiency, though it gets close. Do you like charts?

ICEV: Internal combustion engine vehicle; VTOL: Vertical takeoff and landing; BEV: Battery electric vehicle. The vertical axis is emissions.

To make it better, they had to juice the numbers a bit bit, making the assumption that flying taxis would be more likely to operate at full capacity, with a pilot and three passengers, while ground vehicles were unlikely to have their average occupancy of 1.5 people change much. With that in mind, they found that a 100 km trip with three passengers just barely beats the per-person efficiency of EVs.

That may seem like a bit of a thin victory, but keep in mind that the flying car would be making the trip in likely a quarter of the time, unaffected by traffic and other issues. Plus there’s the view.

It’s all theoretical right now, naturally, but studies like this help companies looking to get into this business decide how their service will be organized and marketed. Reality might look a little different from theory, but I’ll take any reality with flying cars.

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This self-driving AI faced off against a champion racer (kind of)

Posted by | artificial intelligence, Audi, automotive, Gadgets, hardware, robotics, science, self-driving cars, stanford, Stanford University, Transportation | No Comments

Developments in the self-driving car world can sometimes be a bit dry: a million miles without an accident, a 10 percent increase in pedestrian detection range, and so on. But this research has both an interesting idea behind it and a surprisingly hands-on method of testing: pitting the vehicle against a real racing driver on a course.

To set expectations here, this isn’t some stunt, it’s actually warranted given the nature of the research, and it’s not like they were trading positions, jockeying for entry lines, and generally rubbing bumpers. They went separately, and the researcher, whom I contacted, politely declined to provide the actual lap times. This is science, people. Please!

The question which Nathan Spielberg and his colleagues at Stanford were interested in answering has to do with an autonomous vehicle operating under extreme conditions. The simple fact is that a huge proportion of the miles driven by these systems are at normal speeds, in good conditions. And most obstacle encounters are similarly ordinary.

If the worst should happen and a car needs to exceed these ordinary bounds of handling — specifically friction limits — can it be trusted to do so? And how would you build an AI agent that can do so?

The researchers’ paper, published today in the journal Science Robotics, begins with the assumption that a physics-based model just isn’t adequate for the job. These are computer models that simulate the car’s motion in terms of weight, speed, road surface, and other conditions. But they are necessarily simplified and their assumptions are of the type to produce increasingly inaccurate results as values exceed ordinary limits.

Imagine if such a simulator simplified each wheel to a point or line when during a slide it is highly important which side of the tire is experiencing the most friction. Such detailed simulations are beyond the ability of current hardware to do quickly or accurately enough. But the results of such simulations can be summarized into an input and output, and that data can be fed into a neural network — one that turns out to be remarkably good at taking turns.

The simulation provides the basics of how a car of this make and weight should move when it is going at speed X and needs to turn at angle Y — obviously it’s more complicated than that, but you get the idea. It’s fairly basic. The model then consults its training, but is also informed by the real-world results, which may perhaps differ from theory.

So the car goes into a turn knowing that, theoretically, it should have to move the wheel this much to the left, then this much more at this point, and so on. But the sensors in the car report that despite this, the car is drifting a bit off the intended line — and this input is taken into account, causing the agent to turn the wheel a bit more, or less, or whatever the case may be.

And where does the racing driver come into it, you ask? Well, the researchers needed to compare the car’s performance with a human driver who knows from experience how to control a car at its friction limits, and that’s pretty much the definition of a racer. If your tires aren’t hot, you’re probably going too slow.

The team had the racer (a “champion amateur race car driver,” as they put it) drive around the Thunderhill Raceway Park in California, then sent Shelley — their modified, self-driving 2009 Audi TTS — around as well, ten times each. And it wasn’t a relaxing Sunday ramble. As the paper reads:

Both the automated vehicle and human participant attempted to complete the course in the minimum amount of time. This consisted of driving at accelerations nearing 0.95g while tracking a minimum time racing trajectory at the the physical limits of tire adhesion. At this combined level of longitudinal and lateral acceleration, the vehicle was able to approach speeds of 95 miles per hour (mph) on portions of the track.

Even under these extreme driving conditions, the controller was able to consistently track the racing line with the mean path tracking error below 40 cm everywhere on the track.

In other words, while pulling a G and hitting 95, the self-driving Audi was never more than a foot and a half off its ideal racing line. The human driver had much wider variation, but this is by no means considered an error — they were changing the line for their own reasons.

“We focused on a segment of the track with a variety of turns that provided the comparison we needed and allowed us to gather more data sets,” wrote Spielberg in an email to TechCrunch. “We have done full lap comparisons and the same trends hold. Shelley has an advantage of consistency while the human drivers have the advantage of changing their line as the car changes, something we are currently implementing.”

Shelley showed far lower variation in its times than the racer, but the racer also posted considerably lower times on several laps. The averages for the segments evaluated were about comparable, with a slight edge going to the human.

This is pretty impressive considering the simplicity of the self-driving model. It had very little real-world knowledge going into its systems, mostly the results of a simulation giving it an approximate idea of how it ought to be handling moment by moment. And its feedback was very limited — it didn’t have access to all the advanced telemetry that self-driving systems often use to flesh out the scene.

The conclusion is that this type of approach, with a relatively simple model controlling the car beyond ordinary handling conditions, is promising. It would need to be tweaked for each surface and setup — obviously a rear-wheel-drive car on a dirt road would be different than front-wheel on tarmac. How best to create and test such models is a matter for future investigation, though the team seemed confident it was a mere engineering challenge.

The experiment was undertaken in order to pursue the still-distant goal of self-driving cars being superior to humans on all driving tasks. The results from these early tests are promising, but there’s still a long way to go before an AV can take on a pro head-to-head. But I look forward to the occasion.

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Mobileye CEO clowns on Nvidia for allegedly copying self-driving car safety scheme

Posted by | artificial intelligence, automotive, autonomous vehicles, Gadgets, hardware, Intel, Mobileye, nvidia, robotics, self-driving cars, TC, Transportation | No Comments

While creating self-driving car systems, it’s natural that different companies might independently arrive at similar methods or results — but the similarities in a recent “first of its kind” Nvidia proposal to work done by Mobileye two years ago were just too much for the latter company’s CEO to take politely.

Amnon Shashua, in a blog post on parent company Intel’s news feed cheekily titled “Innovation Requires Originality, openly mocks Nvidia’s “Safety Force Field,” pointing out innumerable similarities to Mobileye’s “Responsibility Sensitive Safety” paper from 2017.

He writes:

It is clear Nvidia’s leaders have continued their pattern of imitation as their so-called “first-of-its-kind” safety concept is a close replica of the RSS model we published nearly two years ago. In our opinion, SFF is simply an inferior version of RSS dressed in green and black. To the extent there is any innovation there, it appears to be primarily of the linguistic variety.

Now, it’s worth considering the idea that the approach both seem to take is, like many in the automotive and autonomous fields and others, simply inevitable. Car makers don’t go around accusing each other of using the similar setup of four wheels and two pedals. It’s partly for this reason, and partly because the safety model works better the more cars follow it, that when Mobileye published its RSS paper, it did so publicly and invited the industry to collaborate.

Many did, and as Shashua points out, including Nvidia, at least for a short time in 2018, after which Nvidia pulled out of collaboration talks. To do so and then, a year afterwards, propose a system that is, if not identical, then at least remarkably similar, and without crediting or mentioning Mobileye is suspicious to say the least.

The (highly simplified) foundation of both is calculating a set of standard actions corresponding to laws and human behavior that plan safe maneuvers based on the car’s own physical parameters and those of nearby objects and actors. But the similarities extend beyond these basics, Shashua writes (emphasis his):

RSS defines a safe longitudinal and a safe lateral distance around the vehicle. When those safe distances are compromised, we say that the vehicle is in a Dangerous Situation and must perform a Proper Response. The specific moment when the vehicle must perform the Proper Response is called the Danger Threshold.

SFF defines identical concepts with slightly modified terminology. Safe longitudinal distance is instead called “the SFF in One Dimension;” safe lateral distance is described as “the SFF in Higher Dimensions.”  Instead of Proper Response, SFF uses “Safety Procedure.” Instead of Dangerous Situation, SFF replaces it with “Unsafe Situation.” And, just to be complete, SFF also recognizes the existence of a Danger Threshold, instead calling it a “Critical Moment.”

This is followed by numerous other close parallels, and just when you think it’s done, he includes a whole separate document (PDF) showing dozens of other cases where Nvidia seems (it’s hard to tell in some cases if you’re not closely familiar with the subject matter) to have followed Mobileye and RSS’s example over and over again.

Theoretical work like this isn’t really patentable, and patenting wouldn’t be wise anyway, since widespread adoption of the basic ideas is the most desirable outcome (as both papers emphasize). But it’s common for one R&D group to push in one direction and have others refine or create counter-approaches.

You see it in computer vision, where for example Google boffins may publish their early and interesting work, which is picked up by FAIR or Uber and improved or added to in another paper 8 months later. So it really would have been fine for Nvidia to publicly say “Mobileye proposed some stuff, that’s great but here’s our superior approach.”

Instead there is no mention of RSS at all, which is strange considering their similarity, and the only citation in the SFF whitepaper is “The Safety Force Field, Nvidia, 2017,” in which, we are informed on the very first line, “the precise math is detailed.”

Just one problem: This paper doesn’t seem to exist anywhere. It certainly was never published publicly in any journal or blog post by the company. It has no DOI number and doesn’t show up in any searches or article archives. This appears to be the first time anyone has ever cited it.

It’s not required for rival companies to be civil with each other all the time, but in the research world this will almost certainly be considered poor form by Nvidia, and that can have knock-on effects when it comes to recruiting and overall credibility.

I’ve contacted Nvidia for comment (and to ask for a copy of this mysterious paper). I’ll update this post if I hear back.

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Gates-backed Lumotive upends lidar conventions using metamaterials

Posted by | accelerator, automotive, autonomous vehicles, Bill Gates, Gadgets, hardware, Intellectual Ventures, lasers, Lidar, Lumotive, robotics, science, self-driving cars, TC, Transportation | No Comments

Pretty much every self-driving car on the road, not to mention many a robot and drone, uses lidar to sense its surroundings. But useful as lidar is, it also involves physical compromises that limit its capabilities. Lumotive is a new company with funding from Bill Gates and Intellectual Ventures that uses metamaterials to exceed those limits, perhaps setting a new standard for the industry.

The company is just now coming out of stealth, but it’s been in the works for a long time. I actually met with them back in 2017 when the project was very hush-hush and operating under a different name at IV’s startup incubator. If the terms “metamaterials” and “Intellectual Ventures” tickle something in your brain, it’s because the company has spawned several startups that use intellectual property developed there, building on the work of materials scientist David Smith.

Metamaterials are essentially specially engineered surfaces with microscopic structures — in this case, tunable antennas — embedded in them, working as a single device.

Echodyne is another company that used metamaterials to great effect, shrinking radar arrays to pocket size by engineering a radar transceiver that’s essentially 2D and can have its beam steered electronically rather than mechanically.

The principle works for pretty much any wavelength of electromagnetic radiation — i.e. you could use X-rays instead of radio waves — but until now no one has made it work with visible light. That’s Lumotive’s advance, and the reason it works so well.

Flash, 2D and 1D lidar

Lidar basically works by bouncing light off the environment and measuring how and when it returns; this can be accomplished in several ways.

Flash lidar basically sends out a pulse that illuminates the whole scene with near-infrared light (905 nanometers, most likely) at once. This provides a quick measurement of the whole scene, but limited distance as the power of the light being emitted is limited.

2D or raster scan lidar takes an NIR laser and plays it over the scene incredibly quickly, left to right, down a bit, then does it again, again and again… scores or hundreds of times. Focusing the power into a beam gives these systems excellent range, but similar to a CRT TV with an electron beam tracing out the image, it takes rather a long time to complete the whole scene. Turnaround time is naturally of major importance in driving situations.

1D or line scan lidar strikes a balance between the two, using a vertical line of laser light that only has to go from one side to the other to complete the scene. This sacrifices some range and resolution but significantly improves responsiveness.

Lumotive offered the following diagram, which helps visualize the systems, although obviously “suitability” and “too short” and “too slow” are somewhat subjective:

The main problem with the latter two is that they rely on a mechanical platform to actually move the laser emitter or mirror from place to place. It works fine for the most part, but there are inherent limitations. For instance, it’s difficult to stop, slow or reverse a beam that’s being moved by a high-speed mechanism. If your 2D lidar system sweeps over something that could be worth further inspection, it has to go through the rest of its motions before coming back to it… over and over.

This is the primary advantage offered by a metamaterial system over existing ones: electronic beam steering. In Echodyne’s case the radar could quickly sweep over its whole range like normal, and upon detecting an object could immediately switch over and focus 90 percent of its cycles tracking it in higher spatial and temporal resolution. The same thing is now possible with lidar.

Imagine a deer jumping out around a blind curve. Every millisecond counts because the earlier a self-driving system knows the situation, the more options it has to accommodate it. All other things being equal, an electronically steered lidar system would detect the deer at the same time as the mechanically steered ones, or perhaps a bit sooner; upon noticing this movement, it could not just make more time for evaluating it on the next “pass,” but a microsecond later be backing up the beam and specifically targeting just the deer with the majority of its resolution.

Just for illustration. The beam isn’t some big red thing that comes out.

Targeted illumination would also improve the estimation of direction and speed, further improving the driving system’s knowledge and options — meanwhile, the beam can still dedicate a portion of its cycles to watching the road, requiring no complicated mechanical hijinks to do so. Meanwhile, it has an enormous aperture, allowing high sensitivity.

In terms of specs, it depends on many things, but if the beam is just sweeping normally across its 120×25 degree field of view, the standard unit will have about a 20Hz frame rate, with a 1000×256 resolution. That’s comparable to competitors, but keep in mind that the advantage is in the ability to change that field of view and frame rate on the fly. In the example of the deer, it may maintain a 20Hz refresh for the scene at large but concentrate more beam time on a 5×5 degree area, giving it a much faster rate.

Meta doesn’t mean mega-expensive

Naturally one would assume that such a system would be considerably more expensive than existing ones. Pricing is still a ways out — Lumotive just wanted to show that its tech exists for now — but this is far from exotic tech.

CG render of a lidar metamaterial chip.The team told me in an interview that their engineering process was tricky specifically because they designed it for fabrication using existing methods. It’s silicon-based, meaning it can use cheap and ubiquitous 905nm lasers rather than the rarer 1550nm, and its fabrication isn’t much more complex than making an ordinary display panel.

CTO and co-founder Gleb Akselrod explained: “Essentially it’s a reflective semiconductor chip, and on the surface we fabricate these tiny antennas to manipulate the light. It’s made using a standard semiconductor process, then we add liquid crystal, then the coating. It’s a lot like an LCD.”

An additional bonus of the metamaterial basis is that it works the same regardless of the size or shape of the chip. While an inch-wide rectangular chip is best for automotive purposes, Akselrod said, they could just as easily make one a quarter the size for robots that don’t need the wider field of view, or a larger or custom-shape one for a specialty vehicle or aircraft.

The details, as I said, are still being worked out. Lumotive has been working on this for years and decided it was time to just get the basic information out there. “We spend an inordinate amount of time explaining the technology to investors,” noted CEO and co-founder Bill Colleran. He, it should be noted, is a veteran innovator in this field, having headed Impinj most recently, and before that was at Broadcom, but is perhaps is best known for being CEO of Innovent when it created the first CMOS Bluetooth chip.

Right now the company is seeking investment after running on a 2017 seed round funded by Bill Gates and IV, which (as with other metamaterial-based startups it has spun out) is granting Lumotive an exclusive license to the tech. There are partnerships and other things in the offing, but the company wasn’t ready to talk about them; the product is currently in prototype but very showable form for the inevitable meetings with automotive and tech firms.

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Transportation Weekly: Polestar CEO speaks, Tesla terminology, and a tribute

Posted by | alex roy, Android, Aptiv, Audi, Automation, automotive, BMW, Canada, car, car sharing, Carmera, cars, China, e-bikes, Environmental Protection Agency, Ford, Google, honda, Joshua Schachter, Kia, Kirsten Korosec, Las Vegas, Lyft, mobility services, Netflix, New York, Peugeot, pininfarina, Polestar, rakuten, self-driving car, sidewalk labs, simulation, TechCrunch, Tesla Model S, tokyo, toronto, Toyota, toyota research institute, Transportation, Transportation Weekly, volkswagen, volvo, waymo, Zipcar, Zum | No Comments

Welcome back to Transportation Weekly; I’m your host Kirsten Korosec, senior transportation reporter at TechCrunch . This is the fourth edition of our newsletter, a weekly jaunt into the wonderful world of transportation and how we (and our packages) move.

This week we chat with Polestar CEO Thomas Ingenlath, dig into Lyft’s S-1, take note of an emerging trend in AV development, and check out an experiment with paving. Oh, and how could we forget Tesla.

Never heard of TechCrunch’s Transportation Weekly? Catch up here, here and here. As I’ve written before, consider this a soft launch. Follow me on Twitter @kirstenkorosec to ensure you see it each week. (An email subscription is coming). 


ONM …

There are OEMs in the automotive world. And here, (wait for it) there are ONMs — original news manufacturers. (Cymbal clash!) This is where investigative reporting, enterprise pieces and analysis on transportation lives.

This week, we’re featuring excerpts taken from a one-on-one interview with Polestar CEO Thomas Ingenlath.

On February 27, Volvo’s standalone electric performance brand Polestar introduced its first all-electric vehicle, a five-door fastback called the Polestar 2. The EV, which has a 78 kWh battery pack and can travel 275 miles (estimated EPA guidance) on a single charge, will be manufactured at a new factory in Chengdu, China. Other notable specs: The infotainment system will be powered by Android OS, Polestar is offering subscriptions to the vehicle, and production starts in 2020.

yellow-jacket-polestar

Here is what Ingenlath had to say to me about …

EV charging infrastructure

To be very unpolitical, I think it would be totally stupid if we were to aim to develop electric charging infrastructure on our own or for our brand specifically. If you join the electric market today, of course, you would see partnerships; that’s sensible thing to do. Car companies together are making a big effort in getting out a network of necessary charging stations along the highway. 

That’s what we’re doing; we’re teaming up and have the contracts being designed and soon signed.

On the company’s approach to automation 

The terminology is important for us. We very clearly put that into a different picture, we’re not talking about, and we clearly do not ever want to label it, anautopilot.” The focus of this system is a very safe distance control, which brakes for you and accelerates for you, and of course, the lane keeping. This is not about developing an autopilot system, it is about giving your safety. And that’s where we don’t want to provoke people thinking that they have full rollout autopilot system there. But it is a system that helps you being safe and protected on the road.

I also reached out to Transportation Weekly readers and asked what they wanted to know and then sent some of those questions to Ingenlath.

TW Reader: How did it feel taking one of your personal styling elements – the C shaped rear lamps – from your previous brand over to Polestar?
Ingenlath: It’s an evolutionary process. Polestar naturally builds on its “mothers” DNA and as a new branch develops its own personality. Thor’s hammer, the rear light signature -—with each new model launch (Volvo and Polestar) those elements diverge into a brand specific species.
TW Reader: How much do you still get to do what you love, which is design?
Ingenlath: Being creative is still my main job, now applied on a broader scope — trying to lead a company with a creative and  brand building mindset. Still, I love the Fridays when I meet up with Robin and Max to review the models, sketches and new data. We really enjoy driving the design of both brands to new adventures.

Dig In

Tesla is finally going to offer customers a $35,000 Model 3. How the automaker is able to sell this electric vehicle at the long-awaited $35,000 price point is a big piece of that story — and one that some overlooked. In short, the company is blowing up its sales model and moving to an online only strategy. Tesla stores will close or be converted to “information centers” and retail employees will be laid off.

But this is not what we’re going to talk about today. Tesla has also brought back its so-called “full self-driving” feature, which was removed as an option on its website last year. Now it’s back. Owners can opt for Autopilot, which has automatic steering on highways and traffic-aware cruise control, or FSD.

FSD capability includes several features such as Navigate on Autopilot that is supposed to guide a car from a highway on-ramp to off-ramp, including navigating interchanges and making lane changes. FSD also includes Advanced Summon, Auto Lane Change, and Autopark. Later this year, the system will recognize and respond to traffic lights in more complex urban environments, Tesla says.

All of these features require the driver to be engaged (or ready to take over), yet it’s called “full self-driving.” Now Tesla has two controversially named automation features. (The other is Autopilot). As Andrew Hawkins at The Verge noted in his coverage, “experts are beginning to realize that the way we discuss, and how companies market, autonomy is significant.”

Which begs the obvious question, and one that I asked Musk during a conference call on Thursday. “Isn’t it a problem that you’re calling this full self-driving capability when you’re still going to require the driver to take control or be paying attention?” (I also wanted to ask a followup on his response, but the moderator moved onto the next reporter).

His response:

“We are very clear when you buy the car what is meant by full self driving. It means it’s feature complete, but feature complete requiring supervision.

As we get more — we really need billions of miles, if not maybe 10 billion sort of miles or kilometers on that order collectively from the fleet — then in our opinion probably at that point supervision is not required, but that will still be up to regulators to agree.

So we’re just very clear.  There’s really three steps: there’s being feature complete of full self driving that requires supervision, feature complete but not requiring supervision, and feature complete not requiring supervision and regulators agree.

In other Tesla news, the National Transportation Safety Board is investigating a crash, that at first glance seems to be similar to the fatal crash that killed Tesla owner Joshua Brown.

In cooperation with the Palm Beach sheriff’s office, the NTSB is sending a team of three to conduct a safety investigation of the commercial motor vehicle and Tesla crash in Delray Beach, FL.

— NTSB_Newsroom (@NTSB_Newsroom) March 2, 2019


A little bird …

We hear a lot. But we’re not selfish. Let’s share.

blinky-cat-bird

It’s no secret that Pittsburgh is one of the hubs of autonomous vehicle development in the world. But what’s not so widely known — except for a group of government and company insiders — is that Mayor William Peduto is on the verge of issuing an executive order that will give more visibility into testing there. 

The city’s department of mobility and infrastructure is the central coordinator of this new executive order that aims to help guide testing and policy development there. The department is going to develop guidelines for AV testing, we’re told. And it appears that information on testing will be released to the public at least once a year.

Got a tip or overheard something in the world of transportation? Email me or send a direct message to @kirstenkorosec.


Deal of the week

Daimler and BMW are supposed to be competitors. And they are, except with mapping (both part of the HERE consortium), mobility services (car sharing, ride-sharing), and now the development of highly automated driving systems. The deal is notable because it illustrates a larger trend that has emerged as the AV industry hunkers down into the “trough of disillusionment.” And that’s consolidation. If 2016, was the year of splashy acquisitions, then 2019 is shaping up to be chockfull of alliances and failures (of some startups).

Also interesting to note, and one that will make some AV safety experts cringe, both companies are working on Level 3 driving automation, a designation by the SAE that means conditional driving automation in which multiple high levels of automation are available in certain conditions, but a human driver must be ready to take over. This level of automation is the most controversial because of the so-called “hand off” problem in which a human driver is expected to take control of the wheel in time.

Speaking of partnerships, another deal that got our attention this week involved New York-based mapping and data analytics startup Carmera and Toyota Research Institute-Advanced Development. TRI-AD is an autonomous drive unit started by Toyota with Denso and Aisin. TRI-AD’s mission is to take the research being done over at the Toyota Research Institute and turn its into a product.

The two companies are going to test a concept that will use cameras in Toyota test vehicles to collect data from downtown Tokyo and use it to create high definition maps for urban and surface roads.

TRI-AD considers this the first step towards its open software platform concept known as Automated Mapping Platform that will be used to support the scalability of highly automated driving, by combining data gathered from vehicles of participating companies to generate HD maps. AMP is new and has possible widespread implications at Toyota. And TRI-AD is full of A-listers, including CEO James Kuffner, who came from the Google self-driving project and Nikos Michalakis, who built Netflix’s cloud platform, and Mandali Khalesi, who was at HERE.

Read more on Khalesi and the Toyota’s open source ambitions here.

Other deals:


Snapshot

Snapshot this week is a bit untraditional. It’s literally a snapshot of myself and my grandmother, months before her 100th birthday. Her memorial service was held Saturday. She died at 101. She loved cars and fast ones, but not so much driving them. And every time I got a new press car, we’d hit the road and she’d encourage me to take the turns a bit faster.

She also loved road trips and in the 1920s, her father would drive the family on the mostly dirt roads from New Jersey to Vermont and even Canada. In her teens, she loved riding in the rumble seat, a feature found in a few vehicles at the time including the Ford Model A.

She was young at heart, until the very end. Next week, we’ll focus on the youngest drivers and one automotive startup that is targeting that demographic.


Tiny but mighty micromobility

Lyft’s S-1 lays out the risks associated with its micromobility business and its intent to continue relying on third parties to manufacture its bikes and scooters. Here’s a key nugget about adoption:

“While some major cities have widely adopted bike and scooter sharing, there can be no assurance that new markets we enter will accept, or existing markets will continue to accept, bike and scooter sharing, and even if they do, that we will be able to execute on our business strategy or that our related offerings will be successful in such markets. Even if we are able to successfully develop and implement our network of shared bikes and scooters, there may be heightened public skepticism of this nascent service offering.”

And another about seasonality:

“Our limited operating history makes it difficult for us to assess the exact nature or extent of the effects of seasonality on our network of shared bikes and scooters, however, we expect the demand for our bike and scooter rentals to decline over the winter season and increase during more temperate and dry seasons.”

Lyft, which bought bike-share company Motivate back in July, also released some data about its electric pedal-assist bikes this week, showing that the pedal assist bikes are, unsurprisingly, more popular than the traditional bikes. They also traveled longer distances and improved winter ridership numbers. Now, Lyft is gearing up to deploy 4,000 additional electric bikes to the Citi Bike system in New York City.

One more thing …

Google Maps has added a feature that lets users see Lime scooters, pedal bikes and e-bikes right from the transit tab in over 80 new cities around the world. Users can click the tab to find out if Lime vehicle is available, how long it’ll take to walk to the vehicle, an estimate of how much their ride could cost, along with total journey time and ETA.


Notable reads

If take the time to read anything this week (besides this newsletter), spend some time with Lyft’s S-1. The ride-hailing company’s prospectus mentions autonomous 109 times. In short, yeah, it’s something the company’s executives are thinking about and investing in.

Lyft says it has a two-pronged strategy to bring autonomous vehicles to market. The company encouraging developers of autonomous vehicle technology to use its open platform to get access to its network and enable their vehicles to fulfill rides on the Lyft platform. And Lyft is trying to build its own autonomous vehicle system at its confusingly named “Level 5 Engineering Center.”

  • The company’s primary investors are Rakuten with a 13 percent stake, GM with 7.8 percent, Fidelity with 7.7 percent, Andreessen Horowitz with 6.3 percent and Alphabet with 5.3 percent. GM and Alphabet have business units, GM Cruise and Waymo respectively, that are also developing AV technology.
  • Through Lyft’s partnership with AV systems developer and supplier Aptiv, people in Las Vegas have taken more than 35,000 rides in Aptiv autonomous vehicles with a safety driver since January 2018.
  • One of the “risks” the company lists is “a failure to detect a defect in our autonomous vehicles or our bikes or scooters”

Other quotable notables:

Check out the Pedestrian Traffic Fatalities by State report, a newly released report from Volvo Car USA and The Harris Poll called  The State of Electric Vehicles in America.


Testing and deployments

Again, deployments doesn’t always mean the latest autonomous vehicle pilot.

On Saturday, Sidewalk Labs hosted its Open Sidewalk event in Toronto. This is part of Sidewalk Toronto, a joint effort by Waterfront Toronto and Alphabet’s Sidewalk Labs to create a “mixed-use, complete community” on Toronto’s Eastern Waterfront

The idea of this event was to share ideas and prototypes for making outdoor public space the “social default year-round.” One such prototype “hexagonal paving” got our attention because of its use case for traffic control and pedestrian and bicyclist safety. (Pictured below)

These individual precast concrete slabs are movable and permeable, can light up and give off heat. The idea is that these hexagonal-shaped slabs and be used to clear snow and ice in trouble spots and light up to warn drivers and pedestrians of changes to the street use or to illuminate an area for public uses or even designate bike lanes and hazard zones. And because they’re permeable they can be used to absorb stormwater or melted snow and guide it to underground stormwater management systems.

Sidewalk Labs tell me that the pavers have “plug and play” holes, which allow things like bike racks, bollards, and sign posts to be inserted. Sidewalk Labs initially built these with wood, and the new prototype is the next iteration, featuring modules built from concrete.


On our radar

There is a lot of transportation-related activity this month.

The Geneva Motor Show: Press days are March 5 and March 6. Expect concept, prototype and production electric vehicles from Audi, Honda, Kia, Peugeot, Pininfarina, Polestar, Spanish car company Hispano Suiza, and Volkswagen.

SXSW in Austin: TechCrunch will be at SXSW this coming week. Here’s where I’ll be.

  • 2 p.m. to 6:30 p.m. March 9 at the Empire Garage for the Smart Mobility Summit, an annual event put on by Wards Intelligence and C3 Group. The Autonocast, the podcast I co-host with Alex Roy and Ed Niedermeyer, will also be on hand.
  • 9:30 a.m. to 10:30 a.m. March 12 at the JW Marriott. The Autonocast and founding general partner of Trucks VC, Reilly Brennan will hold a SXSW podcast panel on automated vehicle terminology and other stuff.
  • 3:30 p.m over at the Hilton Austin Downtown, I’ll be moderating a panel Re-inventing the Wheel: Own, Rent, Share, Subscribe. Sherrill Kaplan with Zipcar, Amber Quist, with Silvercar and Russell Lemmer with Dealerware will join me.
  • TechCrunch is also hosting a SXSW party from 1 pm to 4 pm Sunday, March 10, 615 Red River St., that will feature musical guest Elderbrook. RSVP here

Self Racing Cars

Finally, I’ve been in contact with Joshua Schachter who puts on the annual Self Racing Car event, which will be held March 23 and March 24 at Thunderhill Raceway near Willows, California.

There is still room for participants to test or demo their autonomous vehicles, drive train innovation, simulation, software, teleoperation, and sensors. Hobbyists are welcome. Sign up to participate or drop them a line at contact@selfracingcars.com.

Thanks for reading. There might be content you like or something you hate. Feel free to reach out to me at kirsten.korosec@techcrunch.com to share those thoughts, opinions or tips. 

Nos vemos la próxima vez.

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Polestar unveils its all-electric response to the Tesla Model 3

Posted by | Android, automotive, car sharing, China, electric vehicles, Environmental Protection Agency, Europe, Geely, Google, linux, Polestar, sensus, Tesla, tesla model 3, Transportation, Volvo Cars | No Comments

Volvo’s standalone electric performance brand Polestar introduced Wednesday its first all-electric vehicle — a five-door fastback that is gunning for the Tesla Model 3.

In the past few years, every time an electric vehicle — concept, prototype or production version — has been unveiled, the term “Tesla killer” has been tossed about regardless of whether that car will ever even come to market.

In the case of Polestar 2, it’s unclear if it will be the “Tesla killer.” It’s possible that an entirely new group of customers will be attracted to the vehicle. What is clear: The Polestar 2 was designed to compete with the Tesla Model 3 in the U.S., Europe and China. 

You can watch the reveal on Polestar’s YouTube channel.

The specs

The Polestar 2 is meant to be a performance electric vehicle. It’s equipped with two electric motors and a 78 kilowatt-hour battery pack that has an estimated EPA range of about 275 miles.

The Polestar 2’s all-wheel drive electric powertrain produces 300 kW (an equivalent of 408 horsepower) and 487 lb-ft of torque. This is above the rear-wheel (and currently cheapest) version of the Model 3. It’s just a skosh under the dual-motor performance version of the Model 3, which has an output of 450 horsepower and 471 lb-ft of torque.

The Polestar 2 accelerates from 0 to 100km (about 62 mph) in less than five seconds — again, a stat that puts it right above the mid-range Model 3 and below the performance version.

Polestar 2-Exterior-Front

Android inside

In 2017, Volvo announced plans to incorporate a version of its Android operating system into its car infotainment systems. A year later, the company said it would embed voice-controlled Google Assistant, Google Play Store, Google Maps and other Google services into its next-generation Sensus infotainment system.

Polestar has followed Volvo. The Polestar 2’s infotainment system will be powered by Android OS and, as a result, bring into the car embedded Google services such as Google Assistant, Google Maps and the Google Play Store.

This shouldn’t be confused with Android Auto, which is a secondary interface that lies on top of an operating system. Android OS is modeled after its open-source mobile operating system that runs on Linux. But instead of running smartphones and tablets, Google modified it so it could be used in cars.

The Polestar 2 will also have so-called “Phone-As-Key technology,” which basically means customers will have the ability to unlock their car remotely using their smartphones. This capability opens the door — literally and figuratively — for owners to rent their vehicle out via car sharing or use a delivery service to drop off items in the vehicle.

The feature also allows Polestar 2 to sense the driver upon approach. 

Polestar 2-Interior

Market plans

The base price of Polestar 2 is €39,900 ($45,389), the company says. However, for the first year of production the pricier “launch edition” will only be available at €59,900, or about $68,000. (The prices are listed before any federal or state incentives might be applied.)

The launch edition is essentially a base car with two packages, its advanced driver assistance system called Pilot Assist and Plus Pack.

Production of the Polestar 2 will begin in early 2020 at its Chengdu, China factory. The company is initially targeting sales in China, the U.S., Canada and a handful of European countries that include Belgium, Germany, the Netherlands, Norway, Sweden and the U.K.

Polestar, like its potential rival Tesla, is also ditching the dealership. Polestar will only sell its vehicles online and will offer customers subscriptions to the vehicle. Subscription pricing will be revealed at a later date, Polestar said.

The automaker is also opening “Polestar Spaces,” a showroom where customers can interact with the product and schedule test drives. These spaces will be standalone facilities and not within existing Volvo retailer showrooms. Polestar is planning to have 60 of these spaces open by 2020, including Oslo, Los Angeles and Shanghai.

Polestar was once a high-performance brand under Volvo Cars. In 2017, the company was recast as an electric performance brand aimed at producing exciting and fun-to-drive electric vehicles — a niche that Tesla was the first to fill and has dominated ever since. Polestar is jointly owned by Volvo Car Group and Zhejiang Geely Holding of China. Volvo was acquired by Geely in 2010.

The company’s first vehicle, the Polestar 1, was unveiled in September. The Polestar 1 is not a pure electric vehicle; it’s a plug-in hybrid with two electrical motors powered by three 34 kilowatt-hour battery packs and a turbo and supercharged gas inline 4 up front.

Polestar said Wednesday that its next vehicle, the Polestar 3, will be an all-electric “performance SUV.” The company didn’t provide any additional details about the Polestar 3.

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Ford partners with geocoding startup what3words

Posted by | Android, automotive, Cabify, Ford, Logistics, Lonely Planet, red cross, Software, spain, Sync 3, TomTom, Transportation, united nations, what3words | No Comments

Ford is partnering with what3words to give drivers access to the startup’s novel addressing system.

Under the partnership, drivers will be able to connect to the free what3words app — on an iOS or Android device — to their vehicle via their SYNC 3 infotainment platform. Drivers can find the three-word address on website contact pages, guidebooks and business cards. Drivers can enter the addresses via voice or text input and receive directions through the vehicle’s navigation system.

The startup, founded in 2013, has divided the entire world into 57 trillion 3-by-3 meter squares and assigned three words to each one. Users of the what3words app, which is available in 26 languages, has been adopted by logistics, travel, automotive and humanitarian organizations because it provides exact locations anywhere in the world.

The system is used by Lonely Planet, which has rolled out three-word addresses for each of its listings, as well as Mercedes-Benz, ride-hailing app Cabify, the UN, Red Cross and TomTom.

The startup has also attracted an interesting mix of investors, most recently Sony’s venture capital arm. And last year, Daimler took a 10 percent stake in what3words, following an announcement in 2017 to integrate the addressing system into Mercedes’ new infotainment and navigation system — called the Mercedes-Benz User Experience, or MBUX. MBUX is now in the latest Mercedes A-Class and B-Class cars and Sprinter commercial vehicles.

“We are more mobile than ever before, but with that comes its challenges. The growing traction that what3words is gaining within the automobility industry is a testament to how we are improving journeys and customer experiences,” CEO and co-founder Chris Sheldrick said.

What3words will initially be available to Ford owners in the U.K. and Ireland, Germany, Spain, the U.S. and Mexico. More markets and languages will follow later in the year. The addressing system can be downloaded for free on iOS and Android.

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