Uber buys Otto, folks leave Google, Ford goes big, Tesla dumps MobilEye

The past period has seen some very big robocar news. Real news, not the constant “X is partnering with Y” press releases that fill the airwaves some times.

Uber has made a deal to purchase Otto, a self-driving truck company I wrote about earlier founded by several friends of mine from Google. The rumoured terms of the deal as astronomical — possibly 1% of Uber’s highly valued stock (which means almost $700M) and other performance rewards. I have no other information yet on the terms, but it’s safe to say Otto was just getting started with ambitious goals and would not have sold for less than an impressive amount. For a company only 6 months old, the rumoured terms surpass even the amazing valuation stories of Cruise and Zoox.

While Otto has been working on self-driving technology for trucks, any such technology can also move into cars. Uber already has an active lab in Pittsburgh, but up to now has not been involved in long haul trucking. (It does do local deliveries in some places.) There are many startups out there calling themselves the “Uber for Trucks” and Otto has revealed it was also working on shipping management platform tools, so this will strike some fear into those startups. Because of my friendship with Otto’s team, I will do more commentary when more details become public.

In other Uber news, Uber has announced it will sell randomly assigned Uber rides in their self-driving vehicles in Pittsburgh. If your ride request is picked at random (and because it’s in the right place) Uber will send one of their own cars to drive you on your ride, and will make the ride free, to boot. Of course, there will be an Uber safety driver in the vehicle monitoring it and ready to take over in any problem or complex situation. So the rides are a gimmick to some extent, but if they were not free, it would be a sign of another way to get customers to pay for the cost of testing and verifying self-driving cars. The free rides, however, will probably actually cause more people to take Uber rides hoping they will win the lottery and get not simply the free ride but the self-driving ride.

GM announced a similar program for Lyft — but not until next year.

Ford also goes all-in, but with a later date

Ford has announced it wants to commit to making unmanned capable taxi vehicles, the same thing Uber, Google, Cruise/GM, Zoox and most non-car companies want to make. For many years I have outlined the difference between the usual car company approaches, which are evolutionary and involve taking cars and improving their computers and the approaches of the non-car companies which bypass all legacy thinking (mostly around ADAS) to go directly to the final target. I call that “taking a computer and putting wheels on it.” It’s a big and bold move for Ford to switch to the other camp, and a good sign for them. They have said they will have a fleet of such vehicles as soon as 2021.

Other companies have announced plans to go for unmanned capable taxi vehicles, particularly Daimler and BMW, but they still maintain active “evolutionary” projects which hope to build on their prior ADAS work.


The other big news is that Ford, together with Baidu have made a $150M investment in Velodyne. Velodyne has been for a decade the primary supplier of LIDARs for robocar research projects, but their LIDARs are research instruments, high performance at high cost. In the meantime, other companies (such as Quanergy, for whom I am an advisor) have been pushing to make better priced LIDARs for real production. The Velodynes have been the right choice, because it is smart to research with what’s expensive today, knowing it will get cheap in the future. Baidu’s test cars have had Velodynes on them, but there were recent rumours of Baidu experimenting with alternatives to LIDAR, but this investment may counter those rumours.

This investment will move Velodyne more to a lower cost production unit, though at present at a higher cost than the solid-state plans of Quanergy and some others.

Google Departures

Otto included a few people from Google’s car team. It was also recently revealed that Chris Urmson, who had run the team for most of its existence and was moved to “CTO” after the arrival of John Krafcik, has departed. I worked for Chris but he has not told me his reason for departure. In general, Google’s car team has gotten huge, and the recently departed people are mostly folks who were among the first 20 on the team. This may simply be a sign of massive expansion, I have not heard much to credit the idea that there is some sort of internal chaos. In addition, deals like the Otto deal will certainly cause people to consider if they want to work for a big corporation or break out on their own.


A few weeks ago, MobilEye issued a press release that they would not be supplying the next generation of their EyeQ chips to Tesla. The EyeQ4 is a great deal more sophisticated than the EyeQ3 that Telsa uses, and Tesla even uses an older version with a more limited set of features — including, most famously, the inability to detect things like cross traffic. Since MobilEye announced it, it seems like it was their decision (You don’t usually issue a press release to say you have been dumped by a smaller customer.) It caused their stock to take a quick big hit (Disclaimer, I own a small amount) on the day of the announcement, but it recovered reasonably well. Tesla’s stock was not affected.

Tesla folks have always claimed that they only made minimal use of ME’s functionality, and that the real special sauce was theirs. ME folks have claimed the opposite. This break-up will settle that question, and presumably Tesla has been working on alternatives for a while as they don’t seem to be in much panic about it. Tesla has made announcements of plans for their new hardware and those plans look very similar to the EyeQ4, so they must have had their own parallel research underway.



Any thoughts about the MIT / DARPA announcement they might be able to design lidars on a chip to be priced at around $10 each Does that seem feasible to you? Significant?


Solid state

This project is attempting to do a solid state LIDAR, which is also the goal of Quanergy. Quanergy is much further along, and others hope to do the same thing.

The $10 price point is when you are making many millions of the chip, and yes, anything that can go on one chip in those quantities can get a cost that low, though usually you add a few other things beyond the chip.

Whether it is this, or Quanergy, or other companies working on it, low cost LIDAR is definitely coming, and will be used on all robocars, I predict, even Tesla (though Elon has sworn otherwise.) Or at least it will until there is some remarkable breakthrough in computer vision. Which is not impossible, but not here yet. I expect the cheap lidars are sooner. But if you have cheap lidar and cheap camera you use both, of course, at least for the first decade.

Current cost of lidar

Brad, I highly appreciate your writing.

What are the current cost of lidars in an autonomous vehicle, and what has been the typical yearly price reduction so far?

Current cost

There is no standard LIDAR. Velodyne makes several products ranging from $8,000 to $75,000. Valeo sells a simple 4 plane designed by Ibeo for $250 but it’s not really suitable for self-driving. Quanergy has a $1,000 8 laser unit being tested by some automakers. There are a few other research ones out there. Many companies have this in development, they only just figured it out a while ago.

It is reasonable to expect that suitable LIDARs will be under $250, perhaps far under, but you may need more than one.

Quanergy et al chip based LiDAR RANGE

While I have seen multiple stories about chip-based LiDAR (mostly re: Quanergy), the one thing I haven't see is a spec on range. While the cost-effectiveness of these units could be a real breakthrough for driverless vehicles, if the range is under 100 feet their application will be quite limited. Have you seen or heard any quotes on range?


Range for LIDARs is more a function of their light frequency and eye safety rules. You can’t emit so much power that it would be dangerous to the eye. At that maximum power, you can go about 100m on a dark object and still be seen coming back (against the sun.) You can go further on brighter objects, and most objects are brighter, but you have to focus on that minimum range.

More sensitive lidar

Brad, there's an Israeli company working on more sensitive lidar sensors with a better range.

That is true

They are in my queue to write about

Don't forget the poaching of Apple's talent

Faraday Future also poached this week a high-profile Apple-engineer on self-driving and computervision:

Then the billboards all over highway 101 about the nano-degree in self-driving by Sebastian Thrun's Udacity

It's astonishing the tempo that this has taken and accelerating...

... but Apple also picked up an entire company's worth of PhDs

Apple just bought Turi (nee Dato, nee GraphLab). In doing so they acquired the GraphLab Create and Turi Distributed platforms, nice toolkits that accelerate common Machine Learning tasks. However, those don't seem to fit with Apple's product portfolio at all. However they also acquired 50+ data scientists, most with PhDs. To me it looks like perhaps it's an acqui-hire, so they can use those resources on their internal ML projects (cough-self-driving-car-cough).

Disclaimer: I'm an evangelist for Turi (i.e. a run a users' group for them, for which I get no cash compensation but do get the occasional perk like a conference ticket). However, I have no special knowledge about their business internals and this is speculation on my part.

Tesla & maps

Hi, have you heard any news on tesla negotiating with a global mapmaker?
I heard it here (webinar on high definition maps) http://ww2.frost.com/research/industry/automotive-transportation/automot...

Taxi model

Hi Brad

Given the pace at which taxi firms are trying to develop autonomous cars and autonomous car developers are increasingly foreseeing a car-on-demand model for the SDC operations, it remains to be seen how car owners/operators will prevent people from misusing the cars - Misusing meaning everything from pure vandalism and dirtying the car to outright car jacking/ using as a self-guided ballistic missile? Would you know if these firms have something in mind to prevent such incidents?

Rental cars

Are these issues different from the issues with rental cars (Hertz) or carshare (Zipcar)? If they don’t have a wheel, you can’t use them as a missile (unless you physically alter the car, which again you can do with any rental car.)

You are right! Autonomous

You are right! Autonomous cars as missiles seem to be less of a threat.

But when it comes to rental cars or car share, at the end of the day, the guy who takes it out has to face the owner of the car when handing it back. That leaves them kind of "obliged" to take care of the car in their custody, which is what prevents people from vandalizing the vehicle. Even a contract to take care of the car is useless if the car owner isn't around to track vandalism and take defaulters to task.

Compare that to public toilets where no one is watching you use it and you don't have to face the owner(the govt., public utility cos). So people do not care so much and just use and leave it as they feel. Even facing another user doesn't seem to have the same effect as facing the owner. I see an analog in current business models of autonomous cars - nobody is watching you use it and the car just goes to the next guy who wants to use it.

That made me wonder if such consumer behavior is already factored in (but maybe not announced) by autonomous car companies or is it that measures to counter such behavior need to be developed.

I have a number of articles on this topic

Mostly related to the privacy problems because taxi owners will indeed want cameras to stop damage (mostly accidental) to cars as well as people leaving their stuff in them. My current model is as you leave (to stop the meter running) you flip the lever on the camera’s cover, it takes a photo after you are out, and compares it to the photo before you got in, and if there’s a difference, it is examined. In most cases it’s, “You left your bag in the car” but sometimes it’s “You spilled your drink or puked” and the car goes to the car wash and you get the bill.

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