The challenge of understanding drivers' behavior and the quirks of local traffic means the use of autonomous vehicles on public roads will be constrained for many years.
Experts say teaching self-driving cars to use such knowledge requires vast datasets and currently unaffordable computing power. "There's an endless list of these cases where we as humans know the context, we know when to bend the rules and when to break the rules," says Carnegie Mellon University professor Raj Rajkumar.
In addition to variable driving customs and road conditions worldwide, autonomous cars will need to consider aggressive human drivers and driver error.
However, Intel's Kathy Winter is optimistic that auto and tech firms will contribute sensor-derived information to a massive database, to be accessed by artificial intelligence programs to make driving decisions.
Winter predicts autonomous cars will be able to see and think like humans before 2030.
From The Associated Press
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