A system performs modeling and simulation of non-stationary traffic entities for testing and development of modules used in an autonomous vehicle system. The system uses a machine learning based model that predicts hidden context attributes for traffic entities that may be encountered by a vehicle in traffic. The system generates simulation data for testing and development of modules that help navigate autonomous vehicles. The generated simulation data may be image or video data including representations of traffic entities, for example, pedestrians, bicyclists, and other vehicles. The system may generate simulation data using generative adversarial neural networks.
NEURAL NETWORK BASED MODELING AND SIMULATION OF NON-STATIONARY TRAFFIC OBJECTS FOR TESTING AND DEVELOPMENT OF AUTONOMOUS VEHICLE SYSTEMS