Here’s how it would work—all within the space of five seconds or less:

Software in the vehicle would analyze real-time vehicle data and electronically guesses 10-30 seconds into the future to estimate the likelihood of a “disengagement”—a situation where the car’s automated systems could need human help.
If the likelihood exceeds a pre-set threshold, the system contacts a remotely located control center and sends data from the car.
The control center’s system analyzes the car’s data, generates several possible scenarios and shows them to several human supervisors, who are situated in driving simulators.
The humans respond to the simulations and their responses are sent back to the vehicle.
The vehicle now has a library of human-generated responses that it can choose from instantaneously, based on information from on-board sensors.
Such a system might sound expensive and cumbersome, but Robert Hampshire, a research professor at UMTRI and U-M’s Ford School of Public Policy, says it would be far less expensive than having a human driver in every vehicle.
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