Carnegie Mellon’s Martial Hebert explains that the underlying technology for self-driving cars has been in place for some time, but deployment depends on the conditions the system is operating in.

Driving in heavily mapped, controlled environments with known variables is very different from operating in areas that haven’t been seen before, with changing conditions, varying pedestrian density, and unexpected scenarios.

Each of those factors can require different approaches in sensing, training, and system design. On top of that, systems have to go through extensive testing and validation before they can be used around the general public.

The gap between something that works technically and something that can be validated for real-world use is where most of the time has gone.