Self-driving cars, long touted by developers as a way to eliminate road deaths, could likely only prevent a third of all U.S. road crashes, according to a study released on Thursday. The Insurance Institute for Highway Safety (IIHS), a research group financed by U.S. insurers, found the remaining crashes were caused by mistakes that self-driving systems are not equipped to handle any better than human drivers.
Partners for Automated Vehicle Education, a consortium of self-driving companies and researchers, said in a statement on Thursday the study wrongly assumed that automated cars could only prevent crashes caused by perception errors and incapacitation.
Some 72% of crashes were avoidable, based on the study's calculations, if accidents caused by speeding and violation of traffic laws were included, the consortium said.
Traffic experts say roughly nine in 10 crashes result from human error and more than 36,000 people are estimated to have died in U.S. car crashes last year.
Self-driving vehicle developers, including traditional automakers and technology companies, have repeatedly positioned fully automated driving as a tool to drastically reduce road deaths.
But not all human mistakes can be eliminated by camera, radar and other sensor-based technology, according to the IIHS analysis of more than 5,000 representative police-reported crashes nationwide.
One-third of all crashes were the exclusive result of sensing and perception errors, or driver incapacitation, the study found.
Most crashes were due to more complex errors, such as making wrong assumptions about other road users' actions, driving too fast or too slow for road conditions, or making incorrect evasive maneuvers. Many crashes resulted from multiple mistakes.
"Our goal was to show that if you don't deal with those issues, self-driving cars won't deliver massive safety benefits," said Jessica Cicchino, IIHS vice president for research and a coauthor of the study.
