  As automated vehicles and their technology become more advanced and
technically sophisticated, evaluation procedures that can measure the safety
and reliability of these new driverless cars must develop far beyond existing
safety tests. To get an accurate assessment in field tests, such cars would
have to be driven millions or even billions of miles to arrive at an acceptable
level of certainty - a time-consuming process that would cost tens of millions
of dollars.
  Instead, researchers affiliated with the University of Michigan's Mcity
connected and automated vehicle center have developed an accelerated evaluation
process that eliminates the many miles of uneventful driving activity to filter
out only the potentially dangerous driving situations where an automated
vehicle needs to respond, creating a faster, less expensive testing program.
This approach can reduce the amount of testing needed by a factor of 300 to
100,000 so that an automated vehicle driven for 1,000 test miles can yield the
equivalent of 300,000 to 100 million miles of real-world driving.
  While more research and development needs to be done to perfect this
technique, the accelerated evaluation procedure offers a ground-breaking
solution for safe and efficient testing that is crucial to deploying automated
vehicles.
