Combining human and artificial intelligence in autonomous vehicles could push driverless cars more quickly toward wide-scale adoption, University of Michigan researchers say.
That’s the goal of a new project that relies on a technique called instantaneous crowdsourcing to provide a cost-effective, real-time remote backup for onboard autonomous systems without the need for a human to be physically in the driver’s seat. The research is taking place at the U-M Transportation Research Institute (UMTRI).
The need for human safety drivers in vehicles like Waymo’s recently introduced autonomous taxis undermines their cost advantage compared to traditional ride sharing services, the researchers say. It also keeps the era of cars as autonomous rolling living rooms tantalizingly out of reach. And most researchers agree that machines won’t be able to completely take over driving duties for years or even decades.