Police Pull Over Google Self-Driving Car For Driving Too Slowly; Ford Does A Self-Driving Car First

Google’s Self-Driving Car Pulled Over For Driving Too Slowly
Police pulled over one of Google’s self-driving cars on Thursday because of the speed at which it was traveling, but there was no traffic infraction.

The cartoonishly curvacious vehicle was driving 24 miles per hour in a 35 mph zone in Mountain View, California, where the company has its headquarters. It was pulled over after a police officer noticed traffic backing up behind it.

“As the officer approached the slow moving car he realized it was a Google (GOOGL) autonomous vehicle,” the Mountain View Police Department wrote in a blog post. “The officer stopped the car and made contact with the operators to learn more about how the car was choosing speeds along certain roadways and to educate the operators about impeding traffic per 22400(a) of the California Vehicle Code.”

Continue reading at CNet.

In other news… 

Ford is first to test self-driving cars at fake Michigan city

Ford shifts its autonomous car program into a higher gear Friday, announcing it will become the first automaker to test its self-driving cars at a new Michigan compound.

While the Detroit manufacturer has been working on both connected- and autonomous-car technologies for a decade, the new testing program at Mcity – a 32-acre faux metropolis in Ann Arbor, Mich. – reflects Ford’s recent move to upgrade its self-driving efforts from pure research to advanced engineering.

“We’ve been testing (autonomous) cars in the real world, but using a place like Mcity will allow us to refine our algorithms and better calibrate car sensors by repeating specific situations in a reliable way,” says Raj Nair, Ford’s vice president of global product development.

Mcity opened this past summer and is a joint project of the University of Michigan and the state’s Department of Transportation. Ford is one of a few large automakers contributing $1 million over three years to Mcity, which features storefronts, traffic lights, pedestrian zones and other real-world infrastructure to better train autonomous cars on how they need to react in a range of scenarios.