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June 16, 2019
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Consumer Reports knocks Tesla’s Navigate on Autopilot feature

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Consumer Reports is calling the automatic lane-change feature on Tesla’s Navigate on Autopilot “far less competent” than a human driver and cautioned it could pose safety risks.

The consumer advocacy organization posted its review Wednesday on the newest version of Tesla’s advanced driver assistance system.

Navigate on Autopilot is an active guidance system that is supposed to navigate 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.

Tesla pushed out a software update last month to allow for automatic lane changes. Drivers have to enable this feature, which gives the car permission to make its own lane changes. If not enabled, the system asks the driver to confirm the lane change before moving over. Automatic lane changes can be canceled at any time.

The system has been touted as a way to make driving less stressful and improve safety. In practice, the system had startling behavior, Jake Fisher, senior director of auto testing at Consumer Reports told TechCrunch.

“It doesn’t take very long behind the wheel with this feature on to realize it’s not quite ready for prime time,” Fisher said. CR said one of the more troubling concerns were failures of Tesla’s three rearward-facing cameras to detect fast-approaching objects from the rear better than the average driver.

The CR reviewers found Navigate on Autopilot lagged behind human driving skills and engaged in problematic behavior such as cutting off cars and passing on the right. CR drivers often had to take over to prevent the system from making poor decisions.

As a result, the system increases stress and doesn’t improve safety, Fisher said, before asking “So what is the point of this feature?”

The automatic lane change reviewed by Consumer Reports is not the default setting for Autopilot, Tesla notes. It’s an option that requires drivers to remove the default setting. Tesla also argues that drivers using Navigate on Autopilot properly have successfully driven millions of miles and safely made millions of automated lane changes.

While Fisher acknowledged the default setting, he contends that isn’t the issue. He notes the Tesla has many warnings that the driver must be alert and ready to take over at any time.

“Our concern is that if you’re not alert (or ready to take over) you could be put into a tricky situation,” he said.

The bigger concern for all systems like these is the driver will put too much trust into it, Fisher said. The automatic lane-change feature might not be good enough for drivers to let down their guard yet. If Tesla improves this system, even a little bit, the risk of complacency and too much trust rises.

And that’s problematic because drivers still must be ready to take over. “Just watching automation is a harder human task than driving the car,” he said.

CR asserts that an effective driver monitoring system would mitigate this risk. DMS is typically a camera combined with software designed to track a driver’s attention and pick up on cognitive issues that could cause an accident such as drowsiness.

DMS are found in certain BMW models with an ADAS system called DriverAssist Plus, the new 2020 Subaru Outback and Cadillac’s equipped with its Super Cruise system.

This isn’t the first time CR has raised concerns about Autopilot. Last week, the consumer advocacy organization called on Tesla to restrict the use of Autopilot and install a more effective system to verify driver engagement in response to a preliminary report by National Transportation Safety Board on the fatal March 2019 crash of a Tesla Model 3 with a semi-trailer in Delray Beach, Fla.

Last year, CR gave GM’s Super Cruise the top spot in its first-ever ranking of partially automated driving systems because it is the best at striking a balance between technical capabilities and ensuring drivers are paying attention and operating the vehicle safely. Tesla followed in the ranking not because it was less capable, but because of its approach to safety, Fisher noted.

CR evaluated four systems: Super Cruise on the Cadillac CT6, Autopilot on Tesla Model S, X and 3 models, ProPilot Assist on Infiniti QX50 and Nissan Leaf, and Pilot Assist on Volvo XC40 and XC60 vehicles. The organization said it picked these systems because they’re considered the most capable and well-known in the industry.

London’s Tube network to switch on wi-fi tracking by default in July

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Transport for London will roll out default wi-fi device tracking on the London Underground this summer, following a trial back in 2016.

In a press release announcing the move, TfL writes that “secure, privacy-protected data collection will begin on July 8” — while touting additional services, such as improved alerts about delays and congestion, which it frames as “customer benefits”, as expected to launch “later in the year”.

As well as offering additional alerts-based services to passengers via its own website/apps, TfL says it could incorporate crowding data into its free open-data API — to allow app developers, academics and businesses to expand the utility of the data by baking it into their own products and services.

It’s not all just added utility though; TfL says it will also use the information to enhance its in-station marketing analytics — and, it hopes, top up its revenues — by tracking footfall around ad units and billboards.

Commuters using the UK capital’s publicly funded transport network who do not want their movements being tracked will have to switch off their wi-fi, or else put their phone in airplane mode when using the network.

To deliver data of the required detail, TfL says detailed digital mapping of all London Underground stations was undertaken to identify where wi-fi routers are located so it can understand how commuters move across the network and through stations.

It says it will erect signs at stations informing passengers that using the wi-fi will result in connection data being collected “to better understand journey patterns and improve our services” — and explaining that to opt out they have to switch off their device’s wi-fi.

Attempts in recent years by smartphone OSes to use MAC address randomization to try to defeat persistent device tracking have been shown to be vulnerable to reverse engineering via flaws in wi-fi set-up protocols. So, er, switch off to be sure.

We covered TfL’s wi-fi tracking beta back in 2017, when we reported that despite claiming the harvested wi-fi data was “de-personalised”, and claiming individuals using the Tube network could not be identified, TfL nonetheless declined to release the “anonymized” data-set after a Freedom of Information request — saying there remains a risk of individuals being re-identified.

As has been shown many times before, reversing ‘anonymization’ of personal data can be frighteningly easy.

It’s not immediately clear from the press release or TfL’s website exactly how it will be encrypting the location data gathered from devices that authenticate to use the free wi-fi at the circa 260 wi-fi enabled London Underground stations.

Its explainer about the data collection does not go into any real detail about the encryption and security being used. (We’ve asked for more technical details.)

“If the device has been signed up for free Wi-Fi on the London Underground network, the device will disclose its genuine MAC address. This is known as an authenticated device,” TfL writes generally of how the tracking will work.

“We process authenticated device MAC address connections (along with the date and time the device authenticated with the Wi-Fi network and the location of each router the device connected to). This helps us to better understand how customers move through and between stations — we look at how long it took for a device to travel between stations, the routes the device took and waiting times at busy periods.”

“We do not collect any other data generated by your device. This includes web browsing data and data from website cookies,” it adds, saying also that “individual customer data will never be shared and customers will not be personally identified from the data collected by TfL”.

In a section entitled “keeping information secure” TfL further writes: “Each MAC address is automatically depersonalised (pseudonymised) and encrypted to prevent the identification of the original MAC address and associated device. The data is stored in a restricted area of a secure location and it will not be linked to any other data at a device level.  At no time does TfL store a device’s original MAC address.”

Privacy and security concerns were raised about the location tracking around the time of the 2016 trial — such as why TfL had used a monthly salt key to encrypt the data rather than daily salts, which would have decreased the risk of data being re-identifiable should it leak out.

Such concerns persist — and security experts are now calling for full technical details to be released, given TfL is going full steam ahead with a rollout.

 

A report in Wired suggests TfL has switched from hashing to a system of tokenisation – “fully replacing the MAC address with an identifier that cannot be tied back to any personal information”, which TfL billed as as a “more sophisticated mechanism” than it had used before. We’ll update as and when we get more from TfL.

Another question over the deployment at the time of the trial was what legal basis it would use for pervasively collecting people’s location data — since the system requires an active opt-out by commuters a consent-based legal basis would not be appropriate.

In a section on the legal basis for processing the Wi-Fi connection data, TfL writes now that its ‘legal ground’ is two-fold:

  • Our statutory and public functions
  • to undertake activities to promote and encourage safe, integrated, efficient and economic transport facilities and services, and to deliver the Mayor’s Transport Strategy

So, presumably, you can file ‘increasing revenue around adverts in stations by being able to track nearby footfall’ under ‘helping to deliver (read: fund) the mayor’s transport strategy’.

(Or as TfL puts it: “[T]he data will also allow TfL to better understand customer flows throughout stations, highlighting the effectiveness and accountability of its advertising estate based on actual customer volumes. Being able to reliably demonstrate this should improve commercial revenue, which can then be reinvested back into the transport network.”)

On data retention it specifies that it will hold “depersonalised Wi-Fi connection data” for two years — after which it will aggregate the data and retain those non-individual insights (presumably indefinitely, or per its standard data retention policies).

“The exact parameters of the aggregation are still to be confirmed, but will result in the individual Wi-Fi connection data being removed. Instead, we will retain counts of activities grouped into specific time periods and locations,” it writes on that.

It further notes that aggregated data “developed by combining depersonalised data from many devices” may also be shared with other TfL departments and external bodies. So that processed data could certainly travel.

Of the “individual depersonalised device Wi-Fi connection data”, TfL claims it is accessible only to “a controlled group of TfL employees” — without specifying how large this group of staff is; and what sort of controls and processes will be in place to prevent the risk of A) data being hacked and/or leaking out or B) data being re-identified by a staff member.

A TfL employee with intimate knowledge of a partner’s daily travel routine might, for example, have access to enough information via the system to be able to reverse the depersonalization.

Without more technical details we just don’t know. Though TfL says it worked with the UK’s data protection watchdog in designing the data collection with privacy front of mind.

“We take the privacy of our customers very seriously. A range of policies, processes and technical measures are in place to control and safeguard access to, and use of, Wi-Fi connection data. Anyone with access to this data must complete TfL’s privacy and data protection training every year,” it also notes elsewhere.

Despite holding individual level location data for two years, TfL is also claiming that it will not respond to requests from individuals to delete or rectify any personal location data it holds, i.e. if people seek to exercise their information rights under EU law.

“We use a one-way pseudonymisation process to depersonalise the data immediately after it is collected. This means we will not be able to single out a specific person’s device, or identify you and the data generated by your device,” it claims.

“This means that we are unable to respond to any requests to access the Wi-Fi data generated by your device, or for data to be deleted, rectified or restricted from further processing.”

Again, the distinctions it is making there are raising some eyebrows.

What’s amply clear is that the volume of data that will be generated as a result of a full rollout of wi-fi tracking across the lion’s share of the London Underground will be staggeringly massive.

More than 509 million “depersonalised” pieces of data, were collected from 5.6 million mobile devices during the four-week 2016 trial alone — comprising some 42 million journeys. And that was a very brief trial which covered a much smaller sub-set of the network.

As big data giants go, TfL is clearly gunning to be right up there.

In Ford’s future, two-legged robots and self-driving cars could team up on deliveries

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Autonomous vehicles might someday be able to navigate bustling city streets to deliver groceries, pizzas, and other packages without a human behind the wheel. But that doesn’t solve what Ford Motor CTO Ken Washington describes as the last 50-foot problem.

Ford and startup Agility Robotics are partnering in a research project that will test how two-legged robots and self-driving vehicles can work together to solve that curb-to-door problem. Agility’s Digit, a two-legged robot that has a lidar where its head should be, will be used in the project. The robot, which is capable of lifting 40 pounds, can ride along in a self-driving vehicle and be deployed when needed to delivery packages.

“We’re looking at the opportunity of autonomous vehicles through the lens of the consumer and we know from some early experimentation that there are challenges with the last 50 feet,” Washington told TechCrunch in a recent interview. Finding a solution could be an important differentiator for Ford’s commercial robotaxi service, which it plans to launch in 2021.

The communication between Digit and a Ford autonomous vehicle is perhaps the most compelling piece of this research project. As the GIF below shows, the AV arrives at its destination, the hatch of the Ford Transit van opens and Digit unfolds itself, then grabs the package and walks to the door.

Digit is equipped with lidar and stereo cameras, just enough sensors for basic navigation.

But there’s more to the story. The autonomous vehicle — equipped with a robust suite of sensors and computing power that allows for more complex decision making — is sharing its data with Digit long before it is deployed. When Digit “wakes up” it already knows where it is in the world. And if Digit runs into trouble, it can communicate with the idling AV for that extra perception and decision-making prowess.

This solves what Agility CEO Damion Shelton describes as a “classic robotics problem,” of helping the robot know where it is when it wakes up from its sleep state.

“If you know you’re riding around in the vehicle with a clear view of your entire surroundings, it’s a lot easier to get up and move around,” Shelton explained. “That’s really how we’re viewing the primary purpose of this beta exchange; to help the robot be aware of its surroundings, so that you don’t go through this sort of boot up process where the robot gets out of the car and is confused for the first 30 seconds it’s turned on.”

Agility’s Digit robot isn’t the only option Ford is experimenting with to solve that vehicle-to-doorstep problem, Washington said. However, Washington did note that the two-legged robots do have certain advantages, like the ability to step over cracks in the sidewalk and walk up stairs, that can be problematic for wheeled robots.

Ford and Agility’s agreement is categorized as a research project, for now. Ford has not taken an equity stake in Agility, Washington said, although he quickly added “that doesn’t mean we’re not open to it at some point.” 

For Agility, this project is a turning point — or certainly an acceleration — of its very new business. The robotics startup spun out of Oregon State University in late 2015 with an aim to commercialize research from the Dynamic Robotics Laboratory on bipedal locomotion. The company introduced its ostrich-inspired Cassie robot in 2017 as a bipedal research platform. Digit, which added an upper torso, arms, sensors, and additional computing power to the Cassie design, was introduced in February 2019.

Agility has 20 employees, about half of whom support the construction of the robots. The company has raised nearly $8.8 million in capital from a seed and Series A round. And now, with this latest partnership, Agility is prepping to raise another round to help it scale.

Agility has made two first-generation Digit robots. The company, which has offices in Albany, Oregon and Pittsburgh, plans to unveil the second-generation Digit in early summer. A third version of Digit — marking the final design of this bipedal robot — will likely come out in summer or early fall, Shelton said.

Agility will produce about six of these final versions of Digit. From here, Shelton estimated the company will have a steady state production of about two Digits a month. Ultimately, Agility is on pace to make between 50 and 100 by 2021.

All of this research and experimentation is part of the Ford’s eventual goal to launch a commercial robotaxi service. And that last 50-feet will be one of the critical hurdles it will need overcome if it hopes to make self-driving vehicles a profitable enterprise. To prepare, the automaker is pursuing two parallels tracks — testing and honing in on how an AV business might operate, while separately developing autonomous vehicle technology through its subsidiary Argo AI .

Argo AI,  the Pittsburgh-based company into which Ford invested $1 billion in 2017, is developing the virtual driver system and high-definition maps designed for Ford’s self-driving vehicles. Meanwhile, Ford is testing its go-to-market strategy through pilot programs with local businesses as well as large corporate partners like Walmart, Domino’s and Postmates.

Ford plans to spend $4 billion through 2023 under an LLC that’s dedicated to building out an autonomous vehicles business. The $4 billion spending plan includes a $1 billion investment in startup Argo AI.

Ford is testing in Detroit, Miami, Pittsburgh and Washington D.C. and is poised to expand into Austin.

Leak reveals Uber’s $9.99 unlimited delivery Eats Pass

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What’s the cord-cutting equivalent to ditching your kitchen? Uber’s upcoming subscription to unlimited free food delivery. Uber is preparing to launch the $9.99 per month Uber Eats Pass, according to code hidden in Uber’s Android app.

The subscription would waive Uber’s service fee that’s typically 15 percent of your order cost. Given that’s often $5 or more, users stand to save a lot if they order in frequently. But Uber could still earn money on menu item markups, cover costs with a flat order fee that protects against someone ordering a single taco, and most importantly, build loyalty and scale at a time of intense food delivery competition.

The Uber Eats Pass was first spotted by Jane Manchun Wong, the notorious reverse engineering specialist who’s become a frequent TechCrunch tipster. She managed to generate screenshots from Uber’s Android app code the reveals a prototype of the feature. “Get free delivery, any restaurant, any time” is says, showing the amount of money you could have or already saved.

A Uber spokesperson did not dispute the legitimacy of the findings and told TechCrunch “We’re always thinking about new ways to enhance the Eats experience.” They declined to provide further details, which could hint that a launch is imminent but some details are still subject to change. For now we don’t know exactly what perks come with an Eats Pass or where it will be launching first.

At $9.99 per month, the Uber Eats Pass would cost the same and work similarly to Postmates Unlimited and DoorDash DashPass. If they all seem like good deals, you see why they’re less about immediate revenue and more about customer lock-in. You’re a lot less likely to order GrubHub or Caviar if you’ve already pre-paid to cover your Uber Eats delivery costs. And whichever apps emerge from this battle will have instituted the scale and steady behavior to raise prices or just enjoy large lifetime value from each subscriber.

Exploring new business opportunities could help perk up Uber’s share price which closed at $41.50 today two weeks after IPOing at an opening price of $42. There are fears that intense competition across both ride sharing and food delivery could make for an expensive road ahead for the newly public company. Any way it can gain an edge on its rivals keep users from straying to them is important. The logistics giant is already experimenting with allowing restaurants to offer discounts in exchange for promoted placement in the app, which is the first step to Uber becoming an ads company where businesses pay for extra exposure.

If Uber combined Eats Pass with its car service subscription Ride Passes, you have the foundation for a sort of Uber Prime experience — one where you pay an upfront subscription fee that scores you perks and discounts but also makes you likely to spend a lot more on Uber. That bundle could be even more central to Uber than Amazon, which has few direct rivals in the west. People will need to eat and get around for the foreseeable future. Subsidizing loyalty now could be costly in the short-term, but poise Uber for years of lucrative business down the line.

The Exit: Getaround’s $300M roadtrip

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In August of last year, Getaround scored $300 million from Softbank. Eight months later they handed that same amount to Drivy, a Parisian peer-to-peer car rental service that was Getaround’s ticket to tapping into European markets.

Both companies shared similar visions for the future of car ownership, they were about the same size, both were flirting with expanding beyond their home market, but only one had the power of the Vision Fund behind it.

The Exit is a new series at TechCrunch. It’s an exit interview of sorts with a VC who was in the right place at the right time but made the right call on an investment that paid off. [Have feedback? Shoot me an email at lucas@techcrunch.com] 

Alven Capital’s Jeremy Uzan

Alven Capital partner Jeremy Uzan first invested in Drivy’s seed round in 2013. Uzan joined Index Ventures co-leading a $2 million round that valued the company at less than $10 million. The firms would later join forces again for the company’s $8.3 million Series A.

I chatted at length with Uzan about what lies ahead for the Drive team, what Paris’s startup scene is still in desperate need of, and how Softbank’s power is becoming even more impossible to ignore.

The interview has been edited for length and clarity. 


Getting the checkbook

Lucas Matney: So before we dive into this acquisition, tell me a little bit about how you got to the point where you were writing these checks in the first place.

Jeremy Uzan: So, I studied computer science and business and then spent three years as a tech banker. I was actually in a very small investment banking boutique in Paris helping young startups to raise their Series A rounds. They were all French companies, my first deal was with the YouTube competitor DailyMotion.

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