The National Transportation Safety Board has released its preliminary report on the fatal March crash of an Uber self-driving car in Tempe, Arizona. It paints a damning picture of Uber's self-driving technology.
The report confirms that the sensors on the vehicle worked as expected, spotting pedestrian Elaine Herzberg about six seconds prior to impact, which should have given it enough time to stop given the car's 43mph speed.
The problem was that Uber's software became confused, according to the NTSB. "As the vehicle and pedestrian paths converged, the self-driving system software classified the pedestrian as an unknown object, as a vehicle, and then as a bicycle with varying expectations of future travel path," the report says.
Things got worse from there.At 1.3 seconds before impact, the self-driving system determined that an emergency braking maneuver was needed to mitigate a collision. According to Uber, emergency braking maneuvers are not enabled while the vehicle is under computer control, to reduce the potential for erratic vehicle behavior. The vehicle operator is relied on to intervene and take action. The system is not designed to alert the operator.
The car's sensors detected the pedestrian, who was crossing the street with a bicycle, but Uber's software decided it didn't need to react right away. That's a result of how the software was tuned. Like other autonomous vehicle systems, Uber's software has the ability to ignore "false positives," or objects in its path that wouldn't actually be a problem for the vehicle, such as a plastic bag floating over a road. In this case, Uber executives believe the company's system was tuned so that it reacted less to such objects. But the tuning went too far, and the car didn't react fast enough, one of these people said.