Sebastian Thrun and Udacity Launch New Self-Driving Nanodegree

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their design decisions, Thrun says. For example, Tesla developed its driver assistance system Autopilot without using expensive LIDAR technology, relying instead on less-costly sensors such as cameras.

Other companies simply push toward making AV systems that work, without worrying too much about costs today, Thrun says. It’s hard to predict the outcomes of either approach. “We’re in a very early stage of research,’’ Thrun says.

The cost problem may solve itself—at least in part—due to factors such as economies of scale, he says. Some elements of autonomous navigation systems, such as radar, are already dropping in price because they’ve found mass markets for current-day uses, such as vehicle cruise control. A radar installation that would have cost $50,000 about 20 years ago now sells for something like $60 to $80, Thrun says.

In addition, the cost of each self-driving car is likely to dip lower once the cars are manufactured en masse, such as in production runs of 100,000, he says.

Still, he says, costs have to come down. “I’m sure it’s on people’s minds,” Thrun says.

Photo of Sebastian Thrun in 2014, courtesy of Udacity

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