Waymo, the self-driving car company under Alphabet, has been testing in the suburbs of Phoenix for several years now. And while the sunny metropolis might seem like the ideal and easiest location to test autonomous vehicle technology, there are times when the desert becomes a dangerous place for any driver — human or computer.
The two big safety concerns in this desert region are sudden downpours that cause flash floods and haboobs, giant walls of dust between 1,500 and 3,000 feet high that can cover up to 100 square miles. One record-breaking haboob in July 2011 covered the entire Phoenix valley, an area of more than 517 square miles.
Waymo released Friday a blog post that included two videos showing how the sensors on its self-driving vehicles detect and recognize objects while navigating through a haboob in Phoenix and fog in San Francisco. The vehicle in Phoenix was manually driven, while the one in the fog video was in autonomous mode.
The point of the videos, Waymo says, is to show how, and if, the vehicles recognize objects during these extreme low visibility moments. And they do. The haboob video shows how its sensors work to identify a pedestrian crossing a street with little to no visibility.
Waymo uses a combination of lidar, radar and cameras to detect and identify objects. Fog, rain or dust can limit visibility in all or some of these sensors.
Waymo doesn’t silo the sensors affected by a particular weather event. Instead, it continues to take in data from all the sensors, even those that don’t function as well in fog or dust, and uses that collective information to better identify objects.
The potential is for autonomous vehicles to improve on visibility, one of the greatest performance limitations of humans, Debbie Hersman, Waymo’s chief safety officer wrote in the blog post. If Waymo or other AV companies are successful, they could help reduce one of the leading contributors to crashes. The Department of Transportation estimates that weather contributes to 21% of the annual U.S. crashes.
Still, there are times when even an autonomous vehicle doesn’t belong on the road. It’s critical for any company planning to deploy AVs to have a system that can not only identify, but also take the safest action if conditions worsen.
Waymo vehicles are designed to automatically detect sudden extreme weather changes, such as a snowstorm, that could impact the ability of a human or an AV to drive safely, according to Hersman.
The question is what happens next. Humans are supposed to pull over off the road during a haboob and turn off the vehicle, a similar action when one encounters heavy fog. Waymo’s self-driving vehicles will do the same if weather conditions deteriorate to the point that the company believes it would affect the safe operation of its cars, Hersman wrote.
The videos and blog post are the latest effort by Waymo to showcase how and where it’s testing. The company announced August 20 that it has started testing how its sensors handle heavy rain in Florida. The move to Florida will focus on data collection and testing sensors; the vehicles will be manually driven for now.
Waymo also tests (or has tested) its technology in and around Mountain View, Calif., Novi, Mich., Kirkland, Wash. and San Francisco. The bulk of the company’s activities have been in suburbs of Phoenix and around Mountain View.
Porsche’s venture arm has acquired a minority stake in TriEye, an Israeli startup that’s working on a sensor technology to help vehicle driver-assistance and self-driving systems see better in poor weather conditions like dust, fog and rain.
The strategic investment is part of a Series A financing round that has been expanded to $19 million. The round was initially led by Intel Capital and Israeli venture fund Grove Ventures. Porsche has held shares in Grove Ventures since 2017.
TriEye has raised $22 million to date. Terms of Porsche’s investment were not disclosed.
The additional funding will be used for ongoing product development, operations and hiring talent, according to TriEye.
The advanced driver-assistance systems found in most new vehicles today typically rely on a combination of cameras and radar to “see.” Autonomous vehicle systems, which are being developed and tested by dozens of companies such as Argo AI, Aptiv, Aurora, Cruise and Waymo, have a more robust suite of sensors that include light detection and ranging radar (lidar) along with cameras and ultrasonic sensors.
For either of these systems to function properly, they need to be able to see in all conditions. This pursuit of sensor technology has sparked a boom in startups hoping to tap into demand from automakers and companies working on self-driving car systems.
TriEye is one of them. The premise of TriEye is to solve the low visibility problem created by poor weather conditions. The startup’s co-founders argue that fusing existing sensors such as radar, lidar and standard cameras don’t solve this problem.
TriEye, which was founded in 2017, believes the answer is through short-wave infrared (SWIR) sensors. The startup said it has developed an HD SWIR camera that is a smaller size, higher resolution and cheaper than other technologies. The camera is due to launch in 2020.
The technology is based on advanced nano-photonics research by Uriel Levy, a TriEye co-founder and CTO who is also a professor at the Hebrew University of Jerusalem.
The company says its secret sauce is its “unique” semiconductor design that will make it possible to manufacture SWIR HD cameras at a “fraction of their current cost.”
TriEye’s technology was apparently good enough to get Porsche’s attention.
Michael Steiner, a Porsche AG board member focused on R&D, said the technology was promising, as was the team, which is comprised of people with expertise in deep learning, nano-photonics and semiconductor components.
“We see great potential in this sensor technology that paves the way for the next generation of driver assistance systems and autonomous driving functions,” Steiner said in a statement. “SWIR can be a key element: it offers enhanced safety at a competitive price.”
In two years, Voyage has gone from a tiny self-driving car upstart spun out of Udacity to a company able to operate on 200 miles of roads in retirement communities.
Now, Voyage is on the verge of introducing a new vehicle that is critical to its mission of launching a truly driverless ride-hailing service. (Human safety drivers not included.)
This internal milestone, which Voyage CEO Oliver Cameron hinted at in a recent Medium post, went largely unnoticed. Voyage, after all, is just a 55-person speck of a startup in an industry, where the leading companies have amassed hundreds of engineers backed by war chests of $1 billion or more. Voyage has raised just $23.6 million from investors that include Khosla Ventures, CRV, Initialized Capital and the venture arm of Jaguar Land Rover.
Still, the die has yet to be cast in this burgeoning industry of autonomous vehicle technology. These are the middle-school years for autonomous vehicles — a time when size can be misinterpreted for maturity and change occurs in unpredictable bursts.
The upshot? It’s still unclear which companies will solve the technical and business puzzles of autonomous vehicles. There will be companies that successfully launch robotaxis and still fail to turn their service into a profitable commercial enterprise. And there will be operationally savvy companies that fail to develop and validate the technology to a point where human drivers can be removed.
Voyage wants to unlock both.
Gatik AI, the autonomous vehicle startup that’s aiming for the sweet middle spot in the world of logistics, is officially on the road through a partnership with Walmart .
The company received approval from the Arkansas Highway Commissioner’s office to launch a commercial service with Walmart . Gatik’s autonomous vehicles (with a human safety driver behind the wheel) is now delivering customer online grocery orders from Walmart’s main warehouse to its neighborhood stores in Bentonville, Arkansas.
The AVs will aim to travel seven days a week on a two-mile route — the tiniest of slivers of Walmart’s overall business. But the goal here isn’t ubiquity just yet. Instead, Walmart is using this project to capture the kind of data that will help it learn how best to integrate autonomous vehicles into their stores and services.
Gatik uses Ford transit vehicles outfitted with a self-driving system. Co-founder and CEO Gautam Narang has previously told TechCrunch that the company can fulfill a need in the market through a variety of use cases, including partnering with third-party logistics giants like Amazon, FedEx or even the U.S. Postal Service, auto part distributors, consumer goods, food and beverage distributors as well as medical and pharmaceutical companies.
The company, which emerged from stealth in June, has raised $4.5 million in a seed round led by former CEO and executive chairman of Google Eric Schmidt’s Innovation Endeavors. Other investors include AngelPad, Dynamo Fund, Fontinalis Partners, Trucks Venture Capital and angel investor Lior Ron, who heads Uber Freight.
Gatik isn’t the only AV company working with Walmart. Walmart has partnerships with Waymo and Udelv. Both of these partnerships involve pilot programs in Arizona.
Udelv is testing the use of autonomous vans to deliver online grocery orders to customers. Last year, members of Waymo’s early rider program received grocery savings when they shopped from Walmart.com. The riders would then take a Waymo car to their nearby Walmart store for grocery pickup.
Alphabet’s autonomous driving and robotaxi company Waymo does a lot of training in order to refine and improve the artificial intelligence that powers its self-driving software. Recently, it teamed up with fellow Alphabet company and AI specialist DeepMind to develop new training methods that would help make its training better and more efficient.
The two worked together to bring a training method called Population Based Training (PBT for short) to bear on Waymo’s challenge of building better virtual drivers, and the results were impressive — DeepMind says in a blog post that using PBT decreased by 24% false positives in a network that identifies and places boxes around pedestrians, bicyclists and motorcyclists spotted by a Waymo vehicle’s many sensors. Not only that, but is also resulted in savings in terms of both training time and resources, using about 50% of both compared to standard methods that Waymo was using previously.
To step back a little, let’s look at what PBT even is. Basically, it’s a method of training that takes its cues from how Darwinian evolution works. Neural nets essentially work by trying something and then measuring those results against some kind of standard to see if their attempt is more “right” or more “wrong” based on the desired outcome. In the training methods that Waymo was using, they’d have multiple neural nets working independently on the same task, all with varied degrees of what’s known as a “learning rate,” or the degree to which they can deviate in their approach each time they attempt a task (like identifying objects in an image, for instance). A higher learning rate means much more variety in terms of the quality of the outcome, but that swings both ways — a lower learning rate means much steadier progress, but a low likelihood of getting big positive jumps in performance.
But all that comparative training requires a huge amount of resources, and sorting the good from the bad in terms of which are working out relies on either the gut feeling of individual engineers, or massive-scale search with a manual component involved where engineers “weed out” the worst performing neural nets to free up processing capabilities for better ones.
What DeepMind and Waymo did with this experiment was essentially automate that weeding, automatically killing the “bad” training and replacing them with better-performing spin-offs of the best-in-class networks running the task. That’s where evolution comes in, since it’s kind of a process of artificial natural selection. Yes, that does make sense — read it again.
In order to avoid potential pitfalls with this method, DeepMind tweaked some aspects after early research, including evaluating models on fast, 15-minute intervals, building out strong validation criteria and example sets to ensure that tests really were building better-performing neural nets for the real world, and not just good pattern-recognition engines for the specific data they’d been fed.
Finally, the companies also developed a sort of “island population” approach by building sub-populations of neural nets that only competed with one another in limited groups, similar to how animal populations cut off from larger groups (i.e. limited to islands) develop far different and sometimes better-adapted characteristics versus their large land-mass cousins.
Overall, it’s a super interesting look at how deep learning and artificial intelligence can have a real impact on technology that already is, in some cases, and will soon be even much more, involved in our daily lives.
Postmates’ cooler-inspired autonomous delivery robot, which will roll out commercially in Los Angeles later this year, will rely on lidar sensors from Ouster, a burgeoning two-year-old startup that recently raised $60 million in equity and debt funding.
Postmates unveiled the first generation of its self-described “autonomous rover” — known as Serve — late last year. The vehicle uses cameras and light detection and ranging sensors called lidar to navigate sidewalks, as well as a backup human who remotely monitors the rover and can take control if needed.
A new second-generation version made its debut onstage earlier this month at Fortune’s Brainstorm Tech event. This newer version looks identical to the original version except a few minor details, including a change in lidar sensors. The previous version was outfitted with sensors from Velodyne, a company that has long dominated the lidar industry.
The supplier contract is notable for Ouster, a startup trying to carve out market share from the giant Velodyne and stand out from a global pack of lidar companies that now numbers close to 70. And it could prove substantial for the company if Postmates takes Serve to other cities as planned.
Lidar measures distance using laser light to generate highly accurate 3D maps of the world around the car. It’s considered by most in the self-driving car industry a key piece of technology required to safely deploy robotaxis and other autonomous vehicles.
Ouster’s strategy has been to cast a wider net for customers by selling its lidar sensors to other industries, including robotics, drones, mapping, defense, building security, mining and agriculture companies. It’s an approach that Waymo is also pursuing for its custom lidar sensors, which will be sold to companies outside of self-driving cars. Waymo will initially target robotics, security and agricultural technology.
Ouster’s business model, along with its tech, has helped it land 437 customers to date and raise a total of $90 million.
The contract with Postmates is its first major customer announcement. COAST Autonomous announced earlier this week that it was using Ouster sensors for its a low-speed autonomous shuttles. Self-driving truck companies Kodiak and Ike Robotics have also been using the sensors this year.
Ouster, which has 125 employees, uses complementary metal-oxide-semiconductor (CMOS) technology in its OS1 sensors, the same tech found in consumer digital cameras and smartphones. The company has announced four lidar sensors to date, with resolutions from 16 to 128 channels, and two product lines, the OS-1 and OS-2.
TechCrunch Sessions is heading to San Jose on July 10 — just a few days from now — to dig into the future (and present) of transportation.
The agenda at TC Sessions: Mobility is packed with startups and giants in the tech industry. TechCrunch has brought together some of the best and brightest minds working on autonomous vehicle technology, micromobility and electric vehicles, including Dmitri Dolgov at Waymo, Karl Iagnemma of Aptiv, Seleta Reynolds of the Los Angeles Department of Transportation, Ford Motor CTO Ken Washington, Katie DeWitt of Scoot and Argo AI’s chief security officer, Summer Craze Fowler.
It wouldn’t be a TechCrunch Sessions without an up-close look and demonstration of the tech. Alongside the speakers, TC Sessions: Mobility will have several demos, including the unveiling of one startup currently in stealth.
The demos will begin with Holoride, the startup that spun out of Audi that aims to bring a VR experience to the backseat of every car, no matter if it’s a Ford, Mercedes or Chrysler Pacifica minivan. Later in the day, check out Damon X Labs, a company aiming to make motorcycles safer with a system that anticipates accidents and warns the rider.
Finally, the day will wrap up with a Michigan-based startup coming out of stealth. We can’t say much yet, but this startup will show off its approach to getting things to people — even in winter.
TC Sessions: Mobility on July 10 in San Jose is fast approaching. Get ready for a superb lineup of speakers like Dmitri Dolgov (Waymo), Eric Allison (Uber) and Summer Craze Fowler (Argo AI). See the full agenda here.
In addition to the outstanding main stage content, TechCrunch is proud to partner with today’s leading mobility players for a full day of breakout sessions. These breakout sessions will give attendees deeper insights into overcoming some of mobility’s biggest challenges and answering questions directly from today’s industry leaders.
Breakout Session Lineup
How much data is needed to make Autonomous Driving a Reality?
Presented by: Scale AI
We are in the early days of autonomous vehicles, and what’s necessary to go into production is still very much undecided. Simply to prove that these vehicles are safer than driving with humans will require more than 1 billion miles driven. Data is a key ingredient for any AI problem, and autonomy is the mother of all AI problems. How much data is really needed to make autonomy safe, reliable, and widespread, and how will our understanding of data change as that becomes a closer reality? Sponsored by Scale AI.
Think Big by Starting Small: Micromobility Implications to the Future of Mobility
Presented by: Deloitte
A host of new micromobility services have emerged to address a broader range of transportation needs – bikesharing, electric scooters and beyond. The urban emergence of micromobility offers powerful lessons on finding the right balance between fostering innovations that will ultimately benefit consumers and broader transportation systems, while safeguarding public interests. Sponsored by Deloitte.
If You Build It, Will They Buy? – The Role of the FleetTech Partner in the Future Mobility Ecosystem with Brendan P. Keegan
Presented by: Merchants Fleet
The future will bring a convergence of new technologies, services, and connectivity to the mobility space – but who will manage and connect it all? Explore how FleetTech is creating the mobility ecosystem to help organizations embrace technologies – adopting your innovations through trials and pilots and bringing them to market. Sponsored by Merchants Fleet.
The Economics of Going Electric: Constructing NextGen EV Business Models
Presented by: ABB
How do we make the rapidly growing EV industry operational and scalable? Join ABB, HPE and Microsoft for a discussion on how government, industry, providers and suppliers are addressing market shifts and identifying solutions to build successful business models that support the future of mobility. Moderated and sponsored by ABB.
Bringing Efficiency to Closed-Course AV Testing with Atul Acharya
Presented by: AAA Northern California, Nevada & Utah
Looking to jump-start or accelerate your automated vehicle test operations? AAA has built its expertise by operating GoMentum Stations and performing safety assessments on multiple AVs and proving grounds. Join AAA as it shares its collective technical and operational learnings and testing results that will bring efficiency to your testing efforts. Sponsored by AAA Northern California, Nevada & Utah.
Friction-Free Urban Mobility
Presented by: Arrive
What does the future of seamless, urban mobility look like? How do mobility-as-a-service providers and connected vehicles work together to power transportation in a smart city? And which platform will aggregate all of the providers? In what promises to be a thought-provoking discussion, Arrive’s COO Dan Roarty will lay the foundation for what a city’s connected future will look like and outline key steps needed to achieve it. Sponsored by Arrive.
Michigan’s Mobility Ecosystem
Presented by: PlanetM
Revolutionary things can happen when some of the brightest minds in technology come together in one room. This Breakout Session will offer key insights into Michigan’s mobility ecosystem: the people, places and resources dedicated to the evolution of transportation mobility. Following a brief discussion, attendees will have the opportunity to connect with the people and companies moving the world forward through technology innovation and collaboration. Sponsored by PlanetM.
More than a dozen engineers, who lost their jobs after consumer robotics startup Anki shut down in April, have found a new home.
The 13 robotics experts, a group that includes Anki’s co-founder and former CEO Boris Sofman, are heading over to self-driving vehicle company Waymo, to lead engineering in the autonomous trucking division, according to a LinkedIn post. Sofman will report to CTO Dmitri Dolgov.
The group of engineers comprises nearly the entire technical team at Anki, many of whom have roots at Carnegie Mellon University’s robotics program, and includes its former behavior lead Brad Neuman and perception lead Andrew Stein. Anki’s head of hardware Nathan Monson and its former program manager Charlie Hite have also joined Waymo.
Axios was the first to report the move.
Anki built several popular products, starting with Anki Drive in 2013 and later the popular Cozmo robot. The Bay Area-startup had shipped more than 3.5 million devices with annual revenues approaching $100 million, Sofman wrote Thursday in a LinkedIn post.
Anki had raised more than $180 million, according to Crunchbase. The company was apparently prepared to take its robots business beyond entertainment, but it ran out of runway before it was able to activate that plan. “In the end we couldn’t overcome recent hurdles and the complexities of consumer hardware,” Sofman wrote.
Anki was a consumer robots company, which would seem like a bit of a leap over to Waymo. However, Sofman noted that it was autonomous driving that “first sparked” his attraction to the field and was the focus of his thesis at Carnegie Mellon.
“Throughout the last decade, I would look over at what was happening at Waymo and be inspired by the progress they were making, and the inevitable impact their technology would have on everyone’s lives in the years to come,” Sofman wrote.
The trucking team will work out of Waymo’s San Francisco office, a newer development within the company’s structure.
Much of the attention on Waymo has been on its robotaxi ambitions and its Waymo One ride-hailing service in the Phoenix area. However, the company has intentions to apply its full self-driving stack to other commercial applications, including trucks and deliveries.
“The nice thing about all those properties is that while the specialization layer are very different, the core technology, and the hardest problems that you’re trying to solve on research and engineering are exactly the same,” Dolgov said during an interview in March at MIT Tech Review’s EmTech Digital conference.
Autonomous driving company Waymo has launched its tie-in with Lyft, using a “handful” of vehicles to pick up riders in its Phoenix testing zone, per CNBC. To be eligible, Lyft users requesting a ride have to be doing a trip that both starts and ends in the area of Phoenix that it’s already blocked for for its own autonomous testing.
The number of cars on the road is less than 10, since Waymo plans to eventually expand to 10 total for this trial but isn’t there yet. Those factors combined mean that the number of people who’ll get this option probably isn’t astronomical, but when they are opted in, they’ll get a chance to decide whether to go with the autonomous option via one of Waymo’s vans (with a safety driver on board) or just stick with a traditional Lyft .
Waymo and Lyft announced their partnership back in May, and the company still plans to continue operating its own Waymo One commercial autonomous ride-hailing service alongside the Lyft team-up.
Sidewalk Labs, the smart city technology firm owned by Google’s parent company Alphabet, released a plan this week to redevelop a piece of Toronto’s eastern waterfront into its vision of an urban utopia — a ‘mini’ metropolis tucked inside a digital infrastructure burrito and bursting with gee-whiz tech-ery.
A place where high-tech jobs and affordable housing live in harmony, streets are built for people, not just cars, all the buildings are sustainable and efficient, public spaces are dotted with internet-connected sensors and an outdoor comfort system with giant “raincoats” designed to keep residents warm and dry even in winter. The innovation even extends underground, where freight delivery system ferries packages without the need of street-clogging trucks.
But this plan is more than a testbed for tech. It’s a living lab (or petri dish, depending on your view), where tolerance for data collection and expectations for privacy are being shaped, public due process and corporate reach is being tested, and what makes a city equitable and accessible for all is being defined.
It’s also more ambitious and wider in scope than its original proposal.
“In many ways, it was like a 50-sided Rubik’s cube when you’re looking at initiatives across mobility, sustainability, the public realm, buildings and housing and digital governance,” Sidewalk Labs CEO Dan Doctoroff said Monday describing the effort to put together the master plan called Toronto Tomorrow: A New Approach for Inclusive Growth.
Even the harshest critics of the Sidewalk Labs plan might agree with Doctoroff’s Rubik cube analogy. It’s a complex plan with big promises and high stakes. And despite the 1,500-plus page tome presenting the idea, it’s still opaque.
It’s stunning how fast emerging new technologies can coalesce around a simple human need and suddenly change everything, not to mention spur billions in investment.
That’s what has happened in the past five years to the basics of humans getting around town, or “mobility” in the shorthand of Silicon Valley. And that’s the first of the five reasons TC Sessions: Mobility is a must: The Mobility category is too momentous to walk on by. Arguably no tech category has invoked a bigger spectrum of emerging technology to deliver results that touch more lives.
The second reason? Mobility is still the Wild West any way you look at it. Very little is settled on either the tech or business front. What is true vehicle autonomy, for example, and when will we have it? At TC Sessions: Mobility, attendees like Waymo CTO Dmitri Dolgov, Zoox co-founder Jesse Levinson and Lia Theodosiou-Pisanelli from Aurora, among others, will be weighing in on those topics — and many more.
Keeping those onstage interviews real when it comes to demanding topics is always a challenge, which brings us to the third reason: TechCrunch has some of the most respected editors anywhere when it comes to covering mobility. TechCrunch’s Kirsten Korosec, Megan Rose Dickey and Matt Burns built this show and will handle most of the interviews onstage. You can trust them to ask the right questions.
Fourth, please check out the amazing agenda for the show. It really speaks for itself. There is no hot mobility topic — from autonomy to VC investing trends, from micro-mobility to mobility-first city design, to safety and security — that the agenda does not touch.
And the last reason, but perhaps most valuable of all: Consider who you will meet at this show, and how easily you will make new connections. Thanks to our CrunchMatch system, attendees can easily discover each other based on interests and arrange to meet at the show. At every TechCrunch event, literally thousands of new connections arise through CrunchMatch.
And here’s a bonus reason: The sponsors organizing breakout sessions and exhibits at this show are recognized mobility leaders and will have top team leads on site. Catch up with ABB, AAA, Merchants Fleet, Waymo and many more — see the breakout lineup here.
We hope to see you there!
Psst – if you’re a student you can book a $45 ticket with this link.