Zoox Flashes Serious Self-Driving Skills in Chaotic San Francisco

Zoox has shown its system can handle some of San Francisco's toughest driving situations, but the real proof of a self-driving system doesn’t fit onto a highlight reel.

San Francisco has some of the country’s worst traffic. The lights always feel out of sync. The pavement is riddled with potholes. And pedestrians, cyclists, one-wheelers, and scooter-ers spill into the streets like the fog descending from the hills. It is, in all, a horrific place to drive. And for the same reasons, it’s a tremendous place to teach a car to drive itself. To borrow a phrase from a rival city, if your robot can make it here, it can make it anywhere.

That’s why Zoox, a much-hyped self-driving car startup based in Silicon Valley, does much of its testing in the Financial District and North Beach, two of the city’s most vexing neighborhoods. In a three-minute video shared exclusively with WIRED, we see the view from one of Zoox’s test cars, a Toyota Highlander SUV retrofitted with its sensors and computing systems, face down some of San Francisco’s gnarliest thoroughfares and San Franciscans’ most befuddling moves. The vehicle scoots around double-parked cars, makes left turns across traffic, and safely slides between hordes of pedestrians. It does it at night, in the rain, and on hills so steep, you can hardly see the intersection up ahead.

“We’re handling the spectrum of complicated situations you need to drive in in a city like San Francisco,” says Jesse Levinson, Zoox’s CTO. “We have built the software and hardware frameworks that can handle this.”

Veröffentlichung:
30. Juli 2018

Auto-mat ist eine Initiative von

TCS Logo
 
 

Das Portal wird realisiert von

Mobilitätsakademie
 
 
© 2018 - auto-mat.ch