Training, testing, and verifying autonomous machines using simulated environments

In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment - in some examples using hardware configured for installation in a vehicle - to control a virtual vehicle in the simulated environment.