It may be possible for MIT like institute to develop the control alogorithms based upon adaptive learning methods.
For example , based upon the currently available knowledge and the real time 3D data available from the sensors , the autonomous system can still remain in the learning mode while allowing the driver to have full control of the car. The system can then note down the driver actions vs. the analysis done by the system as per the sensor data and can prepare a kind of rule table. Over a period this rule table gets refined and refined so much that the system can use that rule-based table to make autonomous driving decisions.
Replay available now: A handful of emerging network technologies are competing to be the preferred wide-area connection for the Internet of Things. All claim lower costs and power use than cellular but none have wide deployment yet. Listen in as proponents of leading contenders make their case to be the metro or national IoT network of the future. Rick Merritt, EE Times Silicon Valley Bureau Chief, moderators this discussion. Join in and ask his guests questions.