Driver mistakes play a role in virtually all crashes.
So, the logic goes: If you remove people from the equation, far fewer crashes will happen. That’s why automation has been held up as a potential game-changer for safety. But autonomous vehicles might prevent only around a third of all crashes if automated systems drive too much like people, according to a new study from the US Insurance Institute for Highway Safety (IIHS).
According to a national survey of police-reported crashes, driver error is the final failure in the chain of events leading to more than 9 out of 10 crashes. Self-driving cars can account for some human error, but can’t yet account for more complex, prediction-based scenarios, according to the study.
The good news is that self-driving cars excel when drivers are distracted, visibility is low, or a potential hazard is recognised too late. The same goes for crashes due to impairment – caused by drugs and/or alcohol, or a medical emergency. But those types of crashes account for just one-third of all crashes.
To estimate how many crashes might continue to occur, IIHS researchers examined more than 5,000 police-reported crashes from the National Motor Vehicle Crash Causation Survey.
The IIHS team reviewed the case files and separated the driver-related factors that contributed to the crashes into five categories:
The researchers also determined that some crashes were unavoidable, such as those caused by a vehicle failure like a blowout or broken axle.
“Building self-driving cars that drive as well as people do is a big challenge in itself,” the IIHS said in a media statement, “but they’d actually need to be better than that to deliver on the promises we’ve all heard.”