Experts: Uber SUV’s autonomous system should have seen woman

TEMPE, Ariz. — Two experts say video of a deadly crash involving a self-driving Uber vehicle shows the sport utility vehicle’s laser and radar sensors should have spotted a pedestrian, and computers should have braked to avoid the crash.

Authorities investigating the crash in a Phoenix suburb released the video of Uber’s Volvo striking a woman as she walked from a darkened area onto a street.

Experts who viewed the video told The Associated Press that the SUV’s sensors should have seen the woman pushing a bicycle and braked before the impact.

Also, Uber’s human backup driver appears on the video to be looking down before crash and appears startled about the time of the impact.

“The victim did not come out of nowhere. She’s moving on a dark road, but it’s an open road, so Lidar (laser) and radar should have detected and classified her” as a human, said Bryant National Transportation Safety Board via AP

Investigators examine a driverless Uber SUV that fatally struck a woman in Tempe, Ariz. The fatality prompted Uber to suspend all road-testing of such autos in the Phoenix area, Pittsburgh, San Francisco and Toronto.

Walker Smith, a University of South Carolina law professor who studies autonomous vehicles.

Sam Abuelsmaid, an analyst for Navigant Research who also follow autonomous vehicles, said laser and radar systems can see in the dark much better than humans or cameras and that the pedestrian was well within the system’s range.

“It absolutely should have been able to pick her up,” he said. “From what I see in the video it sure looks like the car

is at fault, not the pedestrian.”

The video could have a broad impact on autonomous vehicle research, which has been billed as the answer to cutting the 40,000 traffic deaths that occur annually in the U.S. in human-driven vehicles.

Proponents say that human error is responsible for 94 percent of crashes, and that self-driving vehicles would be better because they see more and don’t get drunk, distracted or drowsy.