Innovation & Tech Today – May 2019

As ride-hailing companies (Lyft and Uber)

head into the public market, more financial

details are being made public and the numbers

tell a cautionary story about what we can

expect from the coming world of autonomous

vehicles (AV). Both companies have held out

the hope for investors that eliminating the

driver would help their companies drive

toward profitability. But The Economist found

that research showed the cost per mile of

operating an autonomous vehicle-based ride-

hailing service is higher than a person driving

their own car.

One of the surprising costs that skews the

numbers for AV services could be said to be

sky high. Cloud computing companies like

Amazon Web Services are critical to making

AVs work. The data that the sensors, lidars,

radars, and cameras must analyze constantly

requires massive computing power and

storage. Intel’s former CEO Brian Krzanich

told journalists last year that eight hours of

driving in an AV would generate 30 terabytes

(that’s 3,000 gigabytes) of data. And, of course,

that’s exactly what AVs are supposed to do –

drive all day.

The data comes fast with cameras generating

20 to 40 mbps and radar adding 10 to 100

kbps. Lidar adds another 20 to 100 mbps. GPS

systems another 50 kbps. Ultrasonic

technology could add more. The number of

individual inputs will vary from vehicle to

vehicle, but as is being proved out in testing,

having more sensing technologies is better. In

fact, more sensors is critical to creating a

functioning, safe AV. Current versions of fully

autonomous cars have anywhere from 20 to 40

different kinds of sensors feeding data to the

cloud or other computer systems.

This is just from one car. If you’re a ride-

hailing service running a fleet of 100 cars

in a city, the cloud computing bill becomes

significant. For comparison, by one estimate,

Twitter’s 270 million users generate 100 GB

of data daily; a single AV will produce

3,000 times that.

There’s more. That data might seem to be

transitory, so that it could be dumped to make

room for new data being created. But that may

not be possible if it’s necessary to use it for the

vehicle to learn new things to improve its

driving. Or the data for an AV may need to be

stored as a record to protect the vehicle or its

supplier from potential legal actions in case of

failure or other issues in the field. Every byte of

data may not need to be stored, but given the

potential negative financial consequences, it’s a

good bet more will be preserved rather than

less. As it ramps up to launch its Cruise AVs,

GM said it is building computer systems to

store and process the AV data. It will use the

data to analyze how its vehicles are performing

and promote further development of its

technology. According to media reports, GM’s

two new data warehouses cost $288 million.

Computing costs are rarely mentioned in

stories about autonomous vehicles, which are

often presented as technological wonders, but

with little detail on this backend world. One

approach to mitigating what appear to be

exponentially growing costs is the drive to

monetize some of this data and create revenue

to offset those costs. That remains to be seen

and will likely only come after a company

spends money up front to capture, use, and

store that data. Q

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