Enabling Autonomous Vehicles to Train Themselves

The article “How Deep Learning Networks Can Use Virtual Worlds To Solve Real World Problems” introduced me to the idea of augmenting a real world data set with data from a virtual world. This allows one to “what if” an infinite number of scenarios without having to attempt to find or create the situation in the real world data. Leveraging this, a system can be built to teach itself (in the spirit of AlphaGo) and could lead to great advances in automous vehicle safety in sooner-than-expected timeframes. This system could also be used to determine how sensor quality and changes in position or number of sensors would affect the resulting driving.