Supplementing vision-based system training with simulated content

A system comprising one or more processors and non-transitory computer storage medium storing instructions that when executed by the one or more processors, cause the processors to generate a set of machine learning algorithms training data, wherein the system is included in a simulation system, and wherein the generation of the training data comprises:

• creating driving environments based at least on vision-based image data received from one or more two-dimensional cameras of a vehicle;
• simulating driving a virtual vehicle by importing only vision-based image data associated with driving environment scenarios, wherein the driving environment scenario is based at least on the created driving environment, wherein, during the simulation, the system:
• monitors performance of the virtual vehicle, and
• dynamically updates at least one parameter of at least one vision-based machine learning model based on the performance, and
• wherein the system uses an updated at least one vision-based machine learning model for subsequent simulations;
• in response to completing the simulation, analyzing simulated results;
• determining optimized driving parameters associated with the driving environment scenario;
• and
• generating the set of machine learning algorithms training data based on the determined optimized driving parameters.