Uber Suspends Robocar Testing After Crash

The crash flipped the Uber car, a Volvo, onto its side

1 min read
uber robocar flips on side
Photo: Mark Beach/Fresco News/Reuters

Editor’s note: On Monday morning Uber announced that it had resumed testing of its self-driving cars in San Francisco and that it would resume testing in Pittsburgh and Tempe, Ariz., later in the day, according toBloomberg.

Uber has temporarily suspended the testing of its self-driving cars following the crash of one of them in Tempe, Ariz. The ride-hailing company had also been conducting experiments in Pittsburgh and San Francisco.

"There was a person behind the wheel [of the Uber car]," Tempe police information officer Josie Montenegro told Bloomberg. "It is uncertain at this time if they were controlling the vehicle at the time of the collision." She added that the crash had apparently been caused by another vehicle’s failure to yield.

The crash was no mere fender-bender: The Uber car—a specially equipped Volvo—was left lying on its side. Contrast the evident violence of that accident with the record racked up by Waymo, the spinoff of the Google car project, which has had only a few minor scrapes during its years-long testing.

A month ago Waymo accused Uber of purloining aspects of its robocar technology, in part by hiring Waymo engineers, notably Anthony Levandowski. Waymo claims that Levandowski brought along gigabytes-worth of Waymo’s plans for lidar sensing systems.

NuTonomy, which is also investigating robocars for a ride-hailing service, yesterday told the Boston Herald that it would continue its testing in South Boston. NuTonomy has another such a program in Singapore.

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Self-Driving Cars Work Better With Smart Roads

Intelligent infrastructure makes autonomous driving safer and less expensive

9 min read
A photograph shows a single car headed toward the viewer on the rightmost lane of a three-lane road that is bounded by grassy parkways, one side of which is planted with trees. In the foreground a black vertical pole is topped by a crossbeam bearing various instruments. 

This test unit, in a suburb of Shanghai, detects and tracks traffic merging from a side road onto a major road, using a camera, a lidar, a radar, a communication unit, and a computer.

Shaoshan Liu

Enormous efforts have been made in the past two decades to create a car that can use sensors and artificial intelligence to model its environment and plot a safe driving path. Yet even today the technology works well only in areas like campuses, which have limited roads to map and minimal traffic to master. It still can’t manage busy, unfamiliar, or unpredictable roads. For now, at least, there is only so much sensory power and intelligence that can go into a car.

To solve this problem, we must turn it around: We must put more of the smarts into the infrastructure—we must make the road smart.

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