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The IIHS studied over 5,000 crashes with

detailed causes that were collected by the

National Highway Traffic Safety Administration,

separating out those caused by “sensing and

perceiving” errors such as driver distraction,

impaired visibility or failing to spot hazards

until it was too late. Researchers also separated

crashes caused by human “incapacitation”

including drivers impaired by alcohol or drugs,

those who fell asleep or drivers with medical

problems. Self-driving vehicles can prevent

those, the study found.

However, the robocars may not be able to

prevent the rest, including prediction errors

such as misjudging how fast another vehicle is

traveling, planning errors including driving too

fast for road conditions and execution errors

including incorrect evasive maneuvers or other

mistakes controlling vehicles.

For example, if a cyclist or another vehicle

suddenly veers into the path of an autonomous

vehicle, it may not be able to stop fast enough or

steer away in time, Cicchino said. “Autonomous

vehicles need to not only perceive the world

around them perfectly, they need to respond to

what’s around them as well,” she said.

Just how many crashes are prevented depends

a lot on how autonomous vehicles are

programmed, Cicchino said. More crashes would

be stopped if the robocars obey all traffic laws

including speed limits. But if artificial intelligence

allows them to drive and react more like humans,

then fewer crashes will be stopped, she said.

“Building self-driving cars that drive as well

as people do is a big challenge in itself,” IIHS

Research Scientist Alexandra Mueller said in

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