General Motors (GM 4.37%) announced on Monday that it has acquired Strobe, Inc., a company that has been developing advanced lidar sensor systems for self-driving cars.
Strobe's technology has the potential to drastically reduce the costs of the sensor hardware needed for fully autonomous vehicles, as well as the physical size of the sensor units themselves. The acquisition gives GM exclusive access -- and brings GM one step closer to mass-producing self-driving cars.
GM's acquisition of Signal gives it a key piece of technology critical to mass-producing self-driving cars. Image source: General Motors.
What's the deal?
GM's announcement was short on specifics. (For starters, we don't know the purchase price.) We do know that the deal is done, not pending, and that Strobe's engineering team will join GM's San-Francisco-based self-driving subsidiary, Cruise Automation.
Strobe is a small company based in Pasadena, California.
What is lidar and why is it important?
Lidar is a sensor system that uses invisible laser beams to create high-resolution images of the sensor's surroundings. Most self-driving systems currently under development rely on high-definition maps, either as a primary system or as a backup to other sensors; matching those maps with the lidar sensor's input helps the car's "brain" know its precise location.
(I should note here that Tesla is the big exception: Tesla believes that a full self-driving system can be built without lidar.)
What does Strobe bring to the table?
Simply put, Strobe's system could help GM bring self-driving cars to market more quickly, at lower prices. Here's how Cruise CEO Kyle Vogt explained lidar solutions in a Medium post on Monday:
Existing commercially available solutions cost tens of thousands of dollars, are bulky and mechanically complex, and lack the performance needed to unlock self-driving operation at higher speeds and in more challenging weather.
To tackle these problems we've acquired Strobe, a company that has quietly been building the leading next-generation LIDAR sensors. Strobe's new chip-scale LIDAR technology will significantly enhance the capabilities of our self-driving cars. But perhaps more importantly, by collapsing the entire sensor down to a single chip, we'll reduce the cost of each LIDAR on our self-driving cars by 99%.
An early prototype of Signal's lidar system, shown with a marker for scale. Image source: General Motors.
What does it mean for GM investors?
All this means that GM's talk about mass-producing self-driving cars in the very near future isn't just talk:
That, in addition to testing its own ride hail service, makes it pretty vertically integrated in a way that few companies are.
-- Johana Bhuiyan (@JMBooyah) October 9, 2017
I think her take is spot-on. Here's a key bit of background: There are quite a few small companies "working on" lidar systems for self-driving cars, but right now, most self-driving test efforts rely on lidar sensors from a company called Velodyne.
That's not a bad thing: Velodyne's sensors work well; it has made good progress on making them smaller and cheaper (though they're still fairly big and quite expensive); and it's currently expanding its California factory in hopes of ramping up to 1 million units a year by the end of 2018.
Velodyne has close connections to GM rival Ford Motor Company (F 0.47%) and Chinese search-engine giant Baidu (BIDU 1.00%); both Ford and Baidu made significant investments in Velodyne last year. That has led some self-driving rivals, including Alphabet's (GOOG 1.25%) (GOOGL 1.27%) Waymo subsidiary, to invest in manufacturing their own lidar units in an effort to reduce costs and eliminate dependence on a single supplier.
GM's "third-generation" self-driving Bolt. Vogt said last month that this version is "mass-producible." Image source: General Motors.
GM is now going the same route. If GM can put Strobe's technology into mass production, it won't need to rely on Velodyne -- and it might be able to leapfrog the technology available to most of its rivals.
Long story short: GM is one step closer to not just mass-producing a self-driving car, but also delivering it at a competitive price.
