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elf-driving cars are making the move to San Francisco, in a new expansion of its pilot project with autonomous vehicles that will see Volvo SUVs outfitted with sensors and supercomputers begin picking up passengers in the city. The autonomous cars won???t operate completely driverless, for the time being ??? as in Pittsburgh, where Uber launched self-driving Ford Focus vehicles this fall, each SUV will have a safety driver and Uber test engineer onboard to handle manual driving when needed and monitor progress with the tests. But the cars will still be picking up ordinary passengers ??? any customers who request uberX using the standard consumer-facing mobile app are eligible for a ride in one of the new XC90s operated by Uber???s Advanced Technologies Group (ATG).

There???s a difference here beyond the geography; this is the third generation of Uber???s autonomous vehicle, which is distinct from the second-generation Fords that were used in the Pittsburgh pilot. Uber has a more direct relationship with Volvo in turning its new XC90s into cars with autonomous capabilities; the Fords were essentially purchased stock off the line, while Uber???s partnership with Volvo means it can do more in terms of integrating its own sensor array into the ones available on board the vehicle already.

Uber ATG Head of Product Matt Sweeney told me in an interview that this third-generation vehicle actually uses fewer sensors than the Fords that are on the roads in Pittsburgh, though the loadout still includes a full complement of traditional optical cameras, radar, LiDAR and ultrasonic detectors. He said that fewer sensors are required in part because of the lessons learned from the Pittsburgh rollout, and from their work studying previous generation vehicles; with autonomy, you typically start by throwing everything you can think of at the problem, and then you narrow based on what???s specifically useful, and what turns out not to be so necessary. Still, the fused image of the world that results from data gathered from the Volvo???s sensor suite does not lack for detail.

You combine [images and LiDAR] together you end up with an image which you know very explicitly distance information about, so it???s like this beautiful object that you can detect as you???re moving through,??? Sweeney explained to me. ???And with some of the better engineered integration here, we have some radars in the front and rear bumpers behind the facades.??? Those radar arrays provide more than just the ability to see even in conditions it might be difficult to do so optically, as in poor weather; Sweeney notes that the radar units they???re using can actually bounce signal off the surface of the road, underneath or around vehicles in front, in order to look for and report back information on potential accidents or hazards not immediately in front of the autonomous Uber itself.

The car is one of the reasons we???re really excited about this partnership, it???s a really tremendous vehicle,??? Sweeney said. ???It???s Volvo???s new SPA, the scalable platform architecture ??? the first car on their brand new, built from the ground up vehicle architecture, so you get all new mechanical, all new electrical, all new compute.??? Uber didn???t pick a partner blindly ??? Sweeney says they found a company with a reputation for nearly a hundred years of solid engineering, manufacturing and a commitment to iterating improvement in those areas. ???The vehicle that we???re building on top of, we???re very intentional about it,??? Sweeney said, noting that cars like this one are engineered specifically for safety, which is not the main failure point when it comes to most automobile accidents today ??? that role is reserved for the human drivers behind the wheel.

Uber???s contributions are mainly in the sensor pod, and in the compute stack in the trunk, which takes up about half the surface area of the storage space and which Sweeney said is ???a blade architecture, a whole bunch of CPUs and GPUs that we can swap out under there,??? though he wouldn???t speak to who???s supplying those components specifically. The tremendous computing power it represents taken together is the key identifying objects, doing so in higher volume, and doing better pathfinding in complex city street environments.

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