Scale AI CEO Alex Wang weighs in on software bugs and what will make AV tech good enough

Scale co-founder and CEO Alex Wang joined us at TechCrunch Sessions: Mobility 2021 this week to discuss his company’s role in the autonomous driving industry and how it’s changed in the five years since its founding. Scale helps large and small AV players establish reliable “ground truth” through data annotation and management, and along the way, the standards for what that means have shifted as the industry matures.

Good data is the “good bones” of autonomous driving systems

Even if two algorithms in autonomous driving might be created more or less equal, their real-world performance could vary dramatically based on what they’re consuming in terms of input data. That’s where Scale’s value prop to the industry starts, and Wang explains why:

If you think about a traditional software system, the thing that will separate a good software system from a bad software system is the code, the quality of the code. For an AI system, which all of these self-driving vehicles or autonomous vehicles are, it’s the data that really separates an amazing algorithm from a bad algorithm. And so one thing we saw was that being one of the stewards and shepherds of high-quality data was going to be incredibly important for the industry, and that’s what’s played out. We work with many of the great companies in the space, from Aurora to Nuro to Toyota to General Motors, and our work with all of them is ensuring that they have really a solid data foundation, so they can build the rest of their stacks on top of it. (Time stamp: 06:24)

#adas, #alex-wang, #alexandr-wang, #artificial-intelligence, #automotive, #autonomous-vehicles, #av, #cybernetics, #ec-techcrunch-tc-mobility, #electric-vehicles, #mobility-2021, #nuro, #robotics, #scale-ai, #self-driving-car, #tc, #transportation

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For vehicle safety, the future is now

Every day in the United States, more than 100 people die because of a car crash. Some are teenagers, like the daughter of writer Michael Lewis and Tabitha Soren, and her boyfriend, who died in a wrong-way crash. Some are well known, like Kevin Clark, who played the drummer in “School of Rock,” who was hit and killed by a driver while biking. Others are not household names, like Janell Katesigwa, who was killed by a drunk driver in Albuquerque, New Mexico, and left behind four children.

Something else happens every day, too: a lack of congressional urgency to require available technology to prevent the next tragedy.

Sadly, what is stopping advanced technology from preventing these deaths is business as usual in Washington, which means a lot of talk about saving lives, but little action.

Vehicle safety is based on using layers of protection that have led to a five-fold reduction in the occurrence of car crash deaths in the United States over the last 50 years.

Existing advanced vehicle safety technology, such as driver monitoring systems, automatic emergency braking and lane-departure warnings, can dramatically reduce crashes like the three described above — and the thousands of others that are a result of drunk, drugged, drowsy and distracted driving.

But only if the technology becomes standard equipment in new vehicles. When technology — underwritten by standards, bolstered by oversight and backstopped by accountability — can annually spare tens of thousands of families from tragedy, our federal government must act.

Over the coming weeks and months, Congress will debate the future of motor vehicles in the United States. The debate will be focused on renewing the Surface Transportation Reauthorization Act, which is also referred to as the “highway bill.”

But make no mistake: While issues such as the future of the gas tax and arcane parliamentary procedures will grab headlines, vital decisions will be made about whether the growing and preventable public health crisis of car crash deaths will be prioritized or once again considered non-essential.

Despite the estimated 38,680 highway fatalities last year, which represented a 7.2% increase over 2019, some federal policymakers have failed to focus on available remedies that would result in fewer funerals and a reduction in lifelong debilitating injuries.

Perhaps the delay is a result of too many in Congress who believe the only available solution is rushing unsupervised driverless vehicles into the marketplace. Even if a green light for mass driverless vehicle production were given today, it would be decades before they could make a significant impact on improving overall safety. This single-minded focus on a unicorn to fix all transportation issues misunderstands the technical challenges and misreads the public mood.

A recent AAA survey found 86% of respondents would not trust riding in driverless vehicles, while another found consumers do not feel comfortable sharing the road with them. The technology industry’s habit of beta-testing unproven software on the public, combined with car companies’ track record of delaying safety in exchange for profit, will not increase consumer trust of the safety, inclusivity and equity of driverless technology.

Vehicle safety is based on using layers of protection that have led to a five-fold reduction in the occurrence of car crash deaths in the United States over the last 50 years. Seatbelts and airbags protect you when you crash. Electronic stability control and anti-lock brakes help you avoid rolling over. Regulations provide minimum levels of performance and recalls serve as a backstop to provide oversight when there is a defect.

It is hard to remember, but there was once a time when dual braking systems, intended to provide a safe stop even in the event of a catastrophic failure of one braking system, were considered revolutionary. Now such a layer of protection is standard.

At a time when the promise of automated vehicle technology could make or break America’s place atop the automobile industry, many in Congress want to ignore history and cut away layers of protection to rush driverless vehicles into the marketplace. One Senate proposal creates a fast track for manufacturers to sell tens of thousands of automated vehicles based on a flimsy promise that their vehicle is as safe as the least safe vehicle meeting current minimum standards. No one should forget that the Ford Pinto met all the minimum standards when it was recalled for exploding upon impact when hit from behind. Driverless vehicles should be held to a higher standard than the minimum.

Congress has an opportunity to help build public trust in the safety of driverless technology by requiring existing innovations that will be the building blocks of driverless vehicles into cars right away, with immediate benefits. For example, in the future, automated vehicles will need driver monitoring systems to make smooth handoffs between machine and driver, automated braking to avoid crashes and lane-keeping technology to keep vehicles where they belong. Today these systems, when working correctly, can help limit crashes by assisting human drivers, just as someday these features may assist computer drivers. Using technology to save lives now does not preclude saving more lives later.

As Congress begins to actively debate the future of the automobile industry, there is a lot of talk about upgrading roads, encouraging electric battery-powered vehicles and accelerating the introduction of driverless cars. Yet, there is not nearly enough talk about what is needed to make us all safer sooner.

There have been a variety of reasonable bills introduced to help the U.S. catch up to the rest of the developed world when it comes to vehicle safety and safeguarding pedestrians. They include improving the safety of our back-seat passengers in crashes, better recall procedures, and more robust and transparent data collection, along with requiring advanced safety features now common around the world.

Unfortunately, we have a long way to go and no time to waste. The European Union, despite a larger population and an almost identical number of vehicles and land size, had under 19,000 crash deaths last year, less than half of the U.S. death toll. Further, the EU’s record-low vehicle-related deaths came without a single driverless vehicle on the road, but with robust consumer information and a regulatory scheme that mandates safety.

In the U.S., however, car manufacturers concerned about challenges from new market entrants — foreign and domestic — are lobbying for looser regulations and immunity from responsibility for automated vehicle crashes. Congress must push the industry to move quickly to protect lives before profits and stand behind their products when things inevitably go wrong. The best time to appropriately assign accountability regarding who will be held responsible if a car with a computer driver kills your loved ones, or a systemwide defect impacts an entire driverless fleet, is before the crash.

Moreover, history demonstrates that thoughtful requirements for all vehicles, crafted in a way to keep pace with major innovations in the automobile industry, have always been necessary to ensure vehicle safety is not reserved for the rich alone.

Federal legislation requiring objective performance standards based on data collected from driverless cars being tested on public streets can provide a path to this future. Yet Congress seems poised to do little, or nothing, once again. It is time for policy makers to reconcile the notion that the long-term viability of the driverless vehicle industry and keeping public roads safer now with incremental improvements, federal oversight and legal responsibility are not opposing ideas but necessary partners.

There is no question the U.S. can lead in the coming era of vehicle innovation while improving safety for all drivers, passengers and pedestrians. Success in this ambitious task will require moving forward quickly with existing safety technology and dispensing with the idea that innovations, safety and accountability are incompatible when, in fact, each is integral to the long-term success of the other.

#adas, #autonomous-vehicles, #column, #driverless-vehicles, #mobility, #opinion, #road-safety, #self-driving-car, #tc, #transportation

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Waabi’s Raquel Urtasun explains why it was the right time to launch an AV technology startup

Raquel Urtasun, the former chief scientist at Uber ATG, is the founder and CEO of Waabi, an autonomous vehicle startup that came out of stealth mode last week. The Toronto-based company, which will focus on trucking, raised an impressive $83.5 million in a Series A round led by Khosla Ventures. 

Urtasun joined Mobility 2021 to talk about her new venture, the challenges facing the self-driving vehicle industry and how her approach to AI can be used to advance the commercialization of AVs.


Why did Urtasun decide to found her own company?

Urtasun, who is considered a pioneer in AI, led the R&D efforts as a chief scientist at Uber ATG, which was acquired by Aurora in December. Six months later, we have Waabi. The company’s mission is to take an AI-first approach to solving self-driving technology. 

I left Uber a little bit over three months ago to start this new company, Waabi, with the idea of having a different way of solving self-driving. This is a combination of my 20-year career in AI as well as more than 10 years in self-driving. Thinking about a new company was something that was always in my head. And the more that I was in the industry, the more that I started thinking about going away from the traditional approach and trying to have a diverse view of how to solve self-driving was actually the way to go. So that’s why I decided to do this company. (Timestamp: 1:21)

#adas, #artificial-intelligence, #aurora-innovation, #autonomous-driving, #mobility-2021, #raquel-urtasun, #self-driving-vehicles, #tc, #transportation, #uber, #waabi

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The rise of robotaxis in China

AutoX, Momenta and WeRide took the stage at TC Sessions: Mobility 2021 to discuss the state of robotaxi startups in China and their relationships with local governments in the country.

They also talked about overseas expansion — a common trajectory for China’s top autonomous vehicle startups — and shed light on the challenges and opportunities for foreign AV companies eyeing the massive Chinese market.


Enterprising governments

Worldwide, regulations play a great role in the development of autonomous vehicles. In China, policymaking for autonomous driving is driven from the bottom up rather than a top-down effort by the central government, observed executives from the three Chinese robotaxi startups.

Huan Sun, Europe general manager at Momenta, which is backed by the government of Suzhou, a city near Shanghai, said her company had a “very good experience” working with the municipal governments across multiple cities.

In China, each local government is incentivized to really act like entrepreneurs like us. They are very progressive in developing the local economy… What we feel is that autonomous driving technology can greatly improve and upgrade the [local governments’] economic structure. (Time stamp: 02:56)

Shenzhen, a special economic zone with considerable lawmaking autonomy, is just as progressive in propelling autonomous driving forward, said Jewel Li, chief operation officer at AutoX, which is based in the southern city.

#adas, #aptiv, #artificial-intelligence, #automotive, #av, #china, #early-stage-2021, #ec-mobility-hardware, #ec-techcrunch-mobility, #ev, #robotaxi, #saic, #self-driving-cars, #tc, #techcrunch-mobility-event-2021, #transportation, #waymo

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Tesla has activated its in-car camera to monitor drivers using Autopilot

Tesla has enabled the in-car camera in its Model 3 and Model Y vehicles to monitor drivers when its Autopilot advanced driver assistance system is being used.

In a software update, Tesla indicated the “cabin camera above the rearview mirror can now detect and alert driver inattentiveness while Autopilot is engaged.” Notably, Tesla has a closed loop system for the data, meaning imagery captured by the camera does not leave the car. The system cannot save of transit information unless data sharing is enabled, according to Tesla. The firmware update was cited by a number of Tesla owners,  industry watchers and bloggers who are active on Twitter.

Tesla has faced criticism for not activating a driver monitoring system within the vehicle even as evidence mounted that owners were misusing the system. Owners have posted dozens of videos on YouTube and TikTok abusing the Autopilot system — some of whom have filmed themselves sitting in the backseat as vehicle drives along the highway. Several fatal crashes involving Tesla vehicles that had Autopilot engaged has put more pressure on the company to act.

Until now, Tesla has not used the camera installed in its vehicles and instead relied on sensors in the steering wheel that measured torque — a method that is supposed to require the driver to keep their hands on the wheel. Drivers have documented and shared on social media how to trick the sensors into thinking a human is holding the wheel.

“Consumer Reports has been calling for camera-based driver monitoring systems for automation systems like Tesla’s AutoPilot for years,” Jake Fisher, senior director of auto testing at CR told TechCrunch. “Tesla’s current system of sensing torque on the wheel cannot tell if the driver is looking at the road. If the new system proves effective, it could help prevent distraction and be a major improvement for safety – potentially saving lives. We hope that other cars are updated soon, and are looking forward to evaluating them.”

Tesla didn’t share details about the driver monitoring system — for instance, is it tracking eye gaze or head position — or whether it will be used to allow hands-free driving. GM’s Super Cruise and Ford’s Blue Cruise advanced driver assistance systems allow for hands-free driving on certain divided highways. Their systems use a combination of map data, high-precision GPS, cameras and radar sensors, as well as a driver attention system that monitors the person behind the wheel, to ensure drivers are paying attention.

Tesla vehicles come standard with a driver assistance system branded as Autopilot. For an additional $10,000, owners can buy “full self-driving,” or FSD — a feature that CEO Elon Musk promises will one day deliver full autonomous driving capabilities. FSD, which has steadily increased in price and capability, has been available as an option for years.

However, Tesla vehicles are not self-driving. FSD includes the parking feature Summon as well as Navigate on Autopilot, an active guidance system that navigates a car from a highway on-ramp to off-ramp, including interchanges and making lane changes. Once drivers enter a destination into the navigation system, they can enable “Navigate on Autopilot” for that trip.

The move comes just a week after Tesla tweeted that its Model Y and Model 3 vehicles bound for North American customers are being built without radar, fulfilling a desire by Musk to only use cameras combined with machine learning to support Autopilot and other active safety features.

Automakers typically use a combination of radar and cameras — and even lidar — to provide the sensing required to deliver advanced driver assistance system features like adaptive cruise control, which matches the speed of a car to surrounding traffic, as well as lane keeping and automatic lane changes. Musk has touted the potential of its branded “Tesla Vision” system, which only uses cameras and so-called neural net processing to detect and understand what is happening in the environment surrounding the vehicle and then respond appropriately.

The decision to pull radar out of the vehicles has caused some blowback for the company. Consumer Reports no longer lists the Model 3 as a Top Pick and the Insurance Institute for Highway Safety said it plans to remove the Model 3’s Top Safety Pick+ designation. The National Highway Traffic and Safety Administration has said that Model 3 and Model Y vehicles built on or after April 27, 2021 will no longer receive the agency’s check mark for automatic emergency braking, forward collision warning, lane departure warning and dynamic brake support.

#adas, #automotive, #autonomous-vehicles, #elon-musk, #ford, #gm, #tesla, #transportation

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Light is the key to long-range, fully autonomous EVs

Advanced driver assistance systems (ADAS) hold immense promise. At times, the headlines about the autonomous vehicle (AV) industry seem ominous, with a focus on accidents, regulation or company valuations that some find undeserving. None of this is unreasonable, but it makes the amazing possibilities of a world of AVs seem opaque.

One of the universally accepted upsides of AVs is the potential positive impact on the environment, as most AVs will also be electric vehicles (EVs).

Industry analyst reports project that by 2023, 7.3 million vehicles (7% of the total market) will have autonomous driving capabilities requiring $1.5 billion of autonomous-driving-dedicated processors. This is expected to grow to $14 billion in 2030, when upward of 50% of all vehicles sold will be classified as SAE Level 3 or higher, as defined by the National Highway Traffic Safety Administration (NHTSA).

Fundamental innovation in computing and battery technology may be required to fully deliver on the promise of AEVs with the range, safety and performance demanded by consumers.

While photonic chips are faster and more energy efficient, fewer chips will be needed to reach SAE Level 3; however, we can expect this increased compute performance to accelerate the development and availability of fully SAE Level 5 autonomous vehicles. In that case, the market for autonomous driving photonic processors will likely far surpass the projection of $14 billion by 2030.

When you consider all of the broad-based potential uses of autonomous electric vehicles (AEVs) — including taxis and service vehicles in major cities, or the clean transport of goods on our highways — we begin to see how this technology can rapidly begin to significantly impact our environment: by helping to bring clean air to some of the most populated and polluted cities.

The problem is that AEVs currently have a sustainability problem.

To operate efficiently and safely, AEVs must leverage a dizzying array of sensors: cameras, lidar, radar and ultrasonic sensors, to name just a few. These work together, gathering data to detect, react and predict in real time, essentially becoming the “eyes” for the vehicle.

While there’s some debate surrounding the specific numbers of sensors required to ensure effective and safe AV, one thing is unanimously agreed upon: These cars will create massive amounts of data.

Reacting to the data generated by these sensors, even in a simplistic way, requires tremendous computational power — not to mention the battery power required to operate the sensors themselves. Processing and analyzing the data involves deep learning algorithms, a branch of AI notorious for its outsized carbon footprint.

To be a viable alternative, both in energy efficiency and economics, AEVs need to get close to matching gas-powered vehicles in range. However, the more sensors and algorithms an AEV has running over the course of a journey, the lower the battery range — and the driving range — of the vehicle.

Today, EVs are barely capable of reaching 300 miles before they need to be recharged, while a traditional combustion engine averages 412 miles on a single tank of gas, according to the U.S. Department of Energy. Adding autonomous driving into the mix widens this gap even further and potentially accelerates battery degradation.

Recent work published in the journal Nature Energy claims that the range of an automated electric vehicle is reduced by 10%-15% during city driving.

At the 2019 Tesla Autonomy Day event, it was revealed that driving range could be reduced by up to 25% when Tesla’s driver-assist system is enabled during city driving. This reduces the typical range for EVs from 300 miles to 225 — crossing a perceived threshold of attractiveness for consumers.

A first-principle analysis takes this a step further. NVIDIA’s AI compute solution for robotaxis, DRIVE, has a power consumption of 800 watts, while a Tesla Model 3 has an energy consumption rate of about 11.9 kWh/100 km. At the typical city speed limit of 50 km/hour (about 30 mph), the Model 3 is consuming approximately 6 kW — meaning power solely dedicated to AI compute is consuming approximately 13% of total battery power intended for driving.

This illustrates how the power-hungry compute engines used for automated EVs pose a significant problem for battery life, vehicle range and consumer adoption.

This problem is further compounded by the power overhead associated with cooling the current generation of the power-hungry computer chips that are currently used for advanced AI algorithms. When processing heavy AI workloads, these semiconductor chip architectures generate massive amounts of heat.

As these chips process AI workloads, they generate heat, which increases their temperature and, as a consequence, performance declines. More effort is then needed and energy wasted on heat sinks, fans and other cooling methods to dissipate this heat, further reducing battery power and ultimately EV range. As the AV industry continues to evolve, new solutions to eliminate this AI compute chip heat problem are urgently needed.

The chip architecture problem

For decades, we have relied on Moore’s law, and its lesser-known cousin Dennard scaling, to deliver more compute power per footprint repeatedly year after year. Today, it’s well known that electronic computers are no longer significantly improving in performance per watt, resulting in overheating data centers all over the world.

The largest gains to be had in computing are at the chip architecture level, specifically in custom chips, each for specific applications. However, architectural breakthroughs are a one-off trick — they can only be made at singular points in time in computing history.

Currently, the compute power required to train artificial intelligence algorithms and perform inference with the resulting models is growing exponentially — five times faster than the rate of progress under Moore’s law. One consequence of that is a huge gap between the amount of computing needed to deliver on the massive economic promise of autonomous vehicles and the current state of computing.

Autonomous EVs find themselves in a tug of war between maintaining battery range and the real-time compute power required to deliver autonomy.

Photonic computers give AEVs a more sustainable future

Fundamental innovation in computing and battery technology may be required to fully deliver on the promise of AEVs with the range, safety and performance demanded by consumers. While quantum computers are an unlikely short- or even medium-term solution to this AEV conundrum, there’s another, more available solution making a breakthrough right now: photonic computing.

Photonic computers use laser light, instead of electrical signals, to compute and transport data. This results in a dramatic reduction in power consumption and an improvement in critical, performance-related processor parameters, including clock speed and latency.

Photonic computers also enable inputs from a multitude of sensors to run inference tasks concurrently on a single processor core (each input encoded in a unique color), while a traditional processor can only accommodate one job at a time.

The advantage that hybrid photonic semiconductors have over conventional architectures lies within the special properties of light itself. Each data input is encoded in a different wavelength, i.e., color, while each runs on the same neural network model. This means that photonic processors not only produce more throughput compared to their electronic counterparts, but are significantly more energy efficient.

Photonic computers excel in applications that require extreme throughput with low latency and relatively low power consumption — applications like cloud computing and, potentially, autonomous driving, where the real-time processing of vast amounts of data is required.

Photonic computing technology is on the brink of becoming commercially available and has the potential to supercharge the current roadmap of autonomous driving while also reducing its carbon footprint. It’s clear that interest in the benefits of self-driving vehicles is increasing and consumer demand is imminent.

So it is crucial for us to not only consider the industries it will transform and the safety it can bring to our roads, but also ensure the sustainability of its impact on our planet. In other words, it’s time to shine a little light on autonomous EVs.

#adas, #artificial-intelligence, #automotive, #av, #battery-technology, #column, #electric-vehicle, #energy, #energy-efficiency, #opinion, #tc, #tesla, #transportation

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NTSB: Autopilot could not have been engaged in fatal Tesla crash

Tesla’s advanced driver assistance system known as Autopilot could not have been engaged on the stretch of road where a Model S crashed last month in Texas, killing the two occupants, according to a preliminary report released Monday by the National Transportation Safety Board.

The results help clear up some of the mysteries around the crash, which has received widespread attention after police reported that there was no one in the driver’s seat, leading to speculation that Autopilot was functioning at the time.

Only adaptive cruise control, one of the functions in Autopilot, could be engaged in that section of the road, according to the NTSB. Autosteer, another feature that keeps the vehicle in the lane, was not available on that part of the road, the report says. The preliminary report supports comments made during Tesla’s vice president of vehicle engineering Lars Moravy, who said during an earnings call that adaptive cruise control was engaged and accelerated to 30 miles per hour before the car crashed.

NTSB also confirmed there were only two occupants in the vehicle. When the two men were found, one was in the passenger seat and the other was in the back seat, which led to speculation about whether Autopilot was engaged and even conspiracy theories that there was a third occupant.

“Footage from the owner’s home security camera shows the owner entering the car’s driver’s seat and the passenger entering the front passenger seat,” the report reads. “The car leaves and travels about 550 feet before departing the road on a curve, driving over the curb, and hitting a drainage culvert, a raised manhole, and a tree.”

What is still unknown is whether the driver moved to another seat before or after the crash.

The NTSB said it will continue to collect data to analyze the crash dynamics, postmortem toxicology test results, seat belt use, occupant egress and electric vehicle fires. All aspects of the crash remain under investigation, the NTSB said.

The NTSB’s preliminary report also indicated that the crash of the Tesla Model S, which caught fire after hitting a tree, destroyed an onboard storage device and damaged the restraint control module — two components that could have provided important information about the cause of the incident. The car’s restraint control module, which can record data associated with vehicle speed, belt status, acceleration, and airbag deployment, was recovered but sustained fire damage, the agency said. The NTSB has taken the restraint control module to its recorder laboratory for evaluation.

The NTSB is investigating the crash with support from Tesla and the National Highway Traffic Safety Administration. Harris County Texas Precinct 4 Constable’s Office is conducting a separate, parallel investigation.

#adas, #automotive, #autopilot, #elon-musk, #model-s, #ntsb, #tesla

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Legislation would mandate driver-monitoring tech in every car

A surprised woman gleefully lets go of her car's steering wheel.

Enlarge / A woman test drives Cadillac’s Super Cruise hands-free driver-assistance feature in 2018. Super Cruise includes a camera-based eye-tracking technology to ensure drivers are watching the road. (credit: Alexander Tamargo/Getty Images for Cadillac)

Three United States senators on Monday proposed legislation that would require all new cars in the United States to have driver-monitoring systems within six years. Two of the legislation’s sponsors—Ed Markey (D-MA) and Richard Blumenthal (D-CT)—recently sent a letter to federal regulators expressing concern about last week’s fatal Tesla crash in Texas.

It’s not clear how a 2019 Tesla Model S wound up crashing into a tree at high speed in a residential neighborhood outside Houston. Police reported that neither of the vehicle’s two passengers was in the driver’s seat: one was in the front passenger seat, while the other was sitting in a rear seat.

The crash has drawn more attention to the long-running debate over adding driver-monitoring technology to cars. A few carmakers have already adopted robust driver-monitoring technology. Cadillac’s Super Cruise driver-assistance technology, for example, uses a driver-facing camera to verify that the driver’s eyes are focused on the road. Drivers can take their hands off the wheel while Super Cruise is active. But if they stop looking at the road ahead, Super Cruise will warn them and eventually disengage.

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#adas, #autopilot, #congresss, #dms, #policy, #self-driving-cars

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No one behind the wheel in deadly Tesla crash Saturday night, say authorities

The National Highway Transportation Safety Administration is opening an investigation into a crash involving a Tesla that authorities say was operating with no one behind the wheel, which left two men dead on late Saturday evening outside of Houston.

The 2019 Tesla Model S went off the road after it failed to negotiate a slight curve, local CBS-affiliate KHOU-TV reported. Harris County Precinct 4 Constable Mark Herman told local reporters that the accident was unprecedented.

“Our office has never experienced a crash scene like this,” he said. “Normally, when the fire dept arrives, they have a vehicle fire under control in minutes, but this went on for close to four hours.” The long burn time was reportedly due to the electric vehicle batteries repeatedly reigniting.

More than 30,000 gallons of water were used to put out the fire. One of the victims was in the front passenger seat and the other was in the backseat, “and at the time of the accident there was no one in the [driver’s] seat,” Herman said.

Earlier on the day of the crash, Tesla CEO Elon Musk retweeted news that the company released its first-quarter 2021 safety report. “Tesla with Autopilot engaged now approaching 10 times lower chance of accident than average vehicle,” he said. Tesla describes its Autopilot as a “suite of driver assistance features” and states that it requires “active driver supervision.”

“NHTSA is aware of the tragic crash involving a Tesla vehicle outside of Houston, Texas,” an spokesperson told TechCrunch. “NHTSA has immediately launched a Special Crash Investigation team to investigate the crash. We are actively engaged with local law enforcement and Tesla to learn more about the details of the crash and will take appropriate steps when we have more information.”

TechCrunch reached out to Tesla for comment and will update the story if the company responds.

#adas, #automotive, #autopilot, #elon-musk, #tc, #tesla, #tesla-model-s, #transportation

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Ford’s hands-free answer to GM’s Super Cruise is called BlueCruise

On Wednesday morning, the Ford Motor Company revealed some fresh information about its forthcoming hands-free highway driving assist. Originally known as Active Drive Assist, this new system has been renamed BlueCruise, and it will roll out in Q3 2021 via an over-the-air update to F-150 trucks and Mustang Mach-E crossovers that shipped with pre-installed hardware.

Like General Motors’ highly rated Super Cruise system, BlueCruise only enables hands-free driving on predetermined roads—in this case 110,000 miles (177,027 km) of pre-mapped divided-lane highways.

And, like Super Cruise, it uses an eye-tracking infrared camera to make sure that the driver’s eyes are on the road ahead while engaged. To prevent mode confusion, Ford says that the main instrument display will change unambiguously so drivers know whether BlueCruise is active.

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#adas, #advanced-driver-assistance-systems, #bluecruise, #cars, #ford, #ford-f-150, #ford-mustang-mach-e, #hands-free-driving

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Strapping a giant teddy bear to a car in the name of highway safety

A large teddy bear is strapped to the back of an SUV as it drives on an Interstate.

Enlarge / Would you notice if a large pink bear in a high-vis vest drove past you on the highway? (credit: IIHS)

Depending on your perspective, the advanced driver assistance systems (ADAS) that are appearing in more and more new cars are either a panacea for an epidemic of distracted driving or a reaction to a driving culture that doesn’t take seriously enough the act of controlling thousands of pounds of high-speed machinery. It doesn’t help that there’s widespread public confusion, particularly when it comes to the one-two combo of adaptive cruise control and lane keeping and whether they allow a driver to nap on the freeway.

Now, a series of tests involving a large pink teddy bear, wearing a high-vis vest while strapped to the back of a moving car, has shown that using adaptive cruise and lane keeping—known in industry jargon as “SAE Level 2 automation”—can help increase a driver’s situational awareness. However, the effect required some familiarity with such systems. The study was performed by the Insurance Institute of Highway Safety and published earlier this month.

You’re adapting my what?

When activated, adaptive cruise control uses forward-looking radar to maintain a specific distance to a vehicle in the lane ahead, slowing down or speeding up (to a maximum of whatever speed cruise control was set to) as necessary. Lane-keeping systems use forward-looking cameras to detect the lane markings on a road to keep the vehicle between them, and when both are active together, the vehicle will do a pretty good facsimile of driving itself, albeit with extremely limited situational awareness.

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#adaptive-cruise-control, #adas, #advanced-driver-assistance-systems, #auto-safety, #cars, #iihs, #insurance-institute-of-highway-safety, #lane-keeping, #safety

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Consumer Reports: Tesla Autopilot a “distant second” to GM Super Cruise

The dashboard of the 2021 Cadillac CT4-V.

Enlarge / Super Cruise will be available on the 2021 Cadillac CT4-V. (credit: Cadillac)

Cadillac Super Cruise has retained its title as the best driver assistance system on the market, Consumer Reports declared in a new ranking. Super Cruise also won CR’s last ranking in 2018. While Super Cruise started out as a Cadillac-only feature, GM is planning to bring it to 22 vehicles by 2023.

Tesla’s Autopilot came in second place—a “distant second” according to Consumer Reports. The group says it saw “minor improvements in lane keeping performance” from Tesla’s offering since the system was last evaluated in 2018.

Those minor improvements were enough for Autopilot to get the top spot in the “lane keeping and performance” category of CR’s report. CR ranked Autopilot 9/10 for performance, while Super Cruise scored 8/10. Tesla also got top marks for Autopilot’s ease of use.

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#adas, #cadillac-super-cruise, #cars, #consumer-reports, #tesla-autopilot

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How Moovit went from opportunity to a $900M exit in 8 years

In May 2020, Intel announced its purchase of Moovit, a mobility as a service (MaaS) solutions company known for an app that stitched together GPS, traffic, weather, crime and other factors to help mass transit riders reduce their travel times, along with time and worry.

According to a release, Intel believes combining Moovit’s data repository with the autonomous vehicle solution stack for its Mobileye subsidiary will strengthen advanced driver-assistance systems (ADAS) and help create a combined $230 billion total addressable market for data, MaaS and ADAS .

Before he was a member of Niantic’s executive team, private investor Omar Téllez was president of Moovit for the six years leading up to its acquisition. In this guest post for Extra Crunch, he offers a look inside Moovit’s early growth strategy, its efforts to achieve product-market fit and explains how rapid growth in Latin America sparked the company’s rapid ascent.


In late 2011, Uri Levine, a good friend from Silicon Valley and founder of Waze, asked me to visit Israel to meet Nir Erez and Roy Bick, two entrepreneurs who had launched an application they had called “the Waze of public transportation.”

By then, Waze was already in conversations to be sold (Google would finally buy it for $1.1 billion) and Uri was thinking about his next step. He was on the board of directors of Moovit (then called Tranzmate) and thought they could use a lot of help to grow and expand internationally, following Waze’s path.

At the time, I was part of Synchronoss Technologies’ management team. After Goldman Sachs and Deutsche Bank took us public in 2006, AT&T and Apple presented us with an idea that would change the world. It was so innovative and secret that we had to sign NDAs and personal noncompete agreements to work with them. Apple was preparing to launch the first iPhone and needed a system where users could activate devices from the comfort of their homes. As such, Synchronoss’ stock became very attractive to the capital markets and ours became the best public offering of 2006.

After six years with Synchronoss while also making some forays into the field of entrepreneurship, I was ready for another challenge. With that spirit in mind, I got on the plane for Israel.

I will always remember the landing at Ben Gurion airport. After 12 hours traveling from JFK, I was called to the front of the immigration line:

“Hey! The guy in the Moovit T-shirt, please come forward!”

For a second, I thought I was in trouble, but then the immigration officer said, Welcome to Israel! We are proud of our startups and we want the world to know that we are a high-tech powerhouse,” before he returned my passport and said goodbye.

I was completely amazed by his attitude and wondered if I really knew what I was getting into.

The opportunity in front of Moovit

At first glance, the numbers seemed very attractive. In 2012, there were roughly seven billion people in the world and only a billion vehicles. Thus, many more people used mass public transport than private and users had to face not only the uncertainty of when a transport would arrive, but also what might happen to them while waiting (e.g., personal safety issues, weather, etc.). Adding more uncertainty: Many people did not know the fastest way to get from point A to point B. As designed, mass public transport was a real nightmare for users.

Uri advised us to “fall in love with the problem and not with the solution,” which is what we tried to do at Moovit. Although Waze had spawned a new transportation paradigm and helped reduce traffic in big cities, mass transit was a much bigger monster that consumed an average of two hours of each day for some people, which adds up to 37 days of each year*!

What would you do if someone told you that in addition to your vacation days, an app could help you find 18 extra days off work next year by cutting your transportation time in half?

* Assumes 261 working days a year, 14 productive hours per day.

#adas, #apps, #automotive, #brazil, #chile, #colombia, #column, #entrepreneurship, #extra-crunch, #google, #growth-and-monetization, #israel, #latin-america, #ma, #maas, #mobility, #moovit, #sao-paulo, #sequoia-capital, #startups, #synchronoss-technologies, #tc, #transportation, #uri-levine, #waze

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Electric car startup Lucid is challenging Tesla’s anti-lidar stance

Promotional image of high-end electric car.

Enlarge (credit: Lucid)

Electric car startup Lucid doesn’t like the phrase “Tesla killer,” but the comparison is hard to avoid. The company raised $1 billion from Saudi Arabia two years ago and is working on the Lucid Air, a high-end battery electric sedan reminiscent of Tesla’s Model S. Lucid is scheduled to officially unveil the car in September and begin selling it next year.

One area where Lucid is looking to differentiate itself from its more established electric rival is with its advanced driver-assistance system (ADAS) called DreamDrive. Elon Musk has ambitious goals for Tesla’s Autopilot technology, but the company has struggled to meet them. One possible factor: Musk has ruled out using lidar, a sensor that is widely used by companies attempting to develop fully driverless vehicles.

“Anyone relying on lidar is doomed,” Musk said at an event last year to showcase Tesla’s progress in self-driving technology. Musk believes that cameras and radar will be sufficient to achieve full autonomy and that lidar is a “crutch” that distracts companies from pursuing more fundamental breakthroughs.

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#adas, #cars, #lucid, #tesla

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Optimized sensors are key to future of automated vehicles

Sensors are critical components of the modern vehicle. They are the eyes of a car, enabling everything from existing ADAS (Advanced Driver-Assistance Systems) features such as automated braking and lane keeping to potential removal of the driver altogether. The consequences of these “eyes” not pointing in the right direction or not seeing clearly could be catastrophic; your car could needlessly break in the middle of the highway or suddenly swerve into another lane. Sufficiently high and safe sensor accuracy is essential, and calibration is critical to ensuring that a vehicle’s sensors are operating at the highest fidelity.

Sensors can be miscalibrated due to everything from daily normal use and changes in operating conditions (temperature or vibrations) to something more severe like accidents or part replacements. Unfortunately, very little emphasis has been placed on addressing the issue. This comes as no surprise; the automotive product cycle is incredibly long, and automated vehicles simply haven’t been tested long enough yet to thoroughly expose this issue.

Most standard perception sensors in the market today can perform intrinsic (refers to internal parameters of one sensor) calibration autonomously. However, extrinsic (refers to parameters relating multiple sensors together) calibration poses significant problems to fleets given the ever-increasing reliance on multiple sensors to overcome the shortcomings of individual sensors. Most calibration solutions today rely on picking functionally or economically inferior sensor configurations and/or simply hoping that the sensors never become miscalibrated from initial factory settings in the first place. Yet while this is obviously unsafe, there exist no common metrics to measure what it means for a sensor to be miscalibrated and no common standards that companies can hold their sensor calibrations up against. Every player in this space has their own unique sensor suites and an accompanying set of unique calibration practices, further complicating the matter.

Current aftermarket, maintenance, and return-to-service options are woefully underprepared to address the issue. Consider ADAS calibration at a typical maintenance shop. The procedure takes 15-120 minutes and requires expensive equipment (scanning tools, large and clear paved areas, alignment racks, etc.). The vehicle itself also needs to be prepared to meticulous standards; the fuel tank must be full, the tires must be properly inflated, the vehicle must be perfectly flat on a balanced floor, etc. Most garages and mechanics are underequipped and insufficiently trained to conduct what is an incredibly tedious and technically complex procedure. This ultimately causes improper calibration that endangers the vehicle’s passengers and those around them.

Innovations and opportunities in sensor calibration

#adas, #artificial-intelligence, #automotive, #bridgestone, #calibration, #column, #extra-crunch, #gps, #machine-learning, #market-analysis, #mems, #reilly-brennan, #robotics, #sensors, #standards, #startups

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People who know more about self-driving technology trust it more

People who know more about self-driving technology trust it more

Enlarge (credit: Natalya Burova/Getty Images)

Robotaxis have a real public image problem, according to new survey data collected by an industry group. Partners for Automated Vehicle Education surveyed 1,200 Americans earlier this year and found that 48 percent of Americans say they would “never get in a taxi or ride-share vehicle that was being driven autonomously.” And slightly more Americans—20 percent versus 18 percent—think autonomous vehicles will never be safe compared to those who say they’d put their names down on a waiting list to get a ride in an autonomous vehicle.

PAVE says its data doesn’t reflect skepticism or fear based on the killing of a pedestrian by one of Uber’s autonomous vehicles, nor the series of drivers killed while using Tesla’s Autopilot. In fact, those events don’t even register with much of the population. Fifty-one percent said they knew nothing at all about the death of Elaine Herzberg in Arizona, and a further 37 percent only knew a little about the Uber death. Similar numbers said they knew nothing at all (49 percent) or very little (38 percent) about Tesla Autopilot deaths. But those who reported knowing a lot about the deaths were more likely to tell the survey they thought autonomous vehicles were safe now.

According to the survey data, getting a ride in a robotaxi might change some of those minds. Three in five said that they’d have more trust in autonomous vehicles if they had a better understanding of how those vehicles worked, and 58 percent said that firsthand experience—i.e. going for a ride in a self-driving car—would make them trust the technology more.

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#adas, #autonomous-vehicles, #cars, #driver-assist, #pave, #self-driving

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