Generative AI Trajectory Simulation for Autonomous Vehicles

The patent introduces a trajectory simulation system as an intermediary component between the autonomous vehicle navigation system and the actual vehicle control. This simulation system uses neural networks to model complex traffic scenarios and generate virtual trajectory data, which then feeds back into the navigation algorithm for improvement. The intermediary simulation environment allows the system to learn from complex scenarios without directly exposing the vehicle control to these complexities, thereby improving reliability while managing architectural complexity through modular design.

The patent creates virtual copies of real-world traffic scenarios through the trajectory simulation system. By replicating complex scenarios like traffic merges and heavy traffic conditions in a controlled simulation environment, the system can repeatedly test and refine navigation algorithms without the risks of real-world operation. These simulated trajectory copies are then used to train and improve the actual vehicle navigation system, enabling higher reliability in complex scenarios while keeping the physical system architecture relatively simple.

The patent implements preliminary action by conducting all algorithm development and validation work in a simulated environment before deploying to real-world conditions. The trajectory simulation system pre-tests navigation algorithms against a wide variety of scenarios, including edge cases and complex traffic patterns, allowing iterative development and refinement. This preliminary simulation phase enables rapid prototyping and validation, significantly speeding up the development process while eliminating the safety risks associated with real-world testing during the development stage.

The patent converts the potentially harmful factor of uncontrolled real-world testing into a beneficial controlled simulation environment. By deliberately creating virtual copies of real-world scenarios in the trajectory simulation system, the patent transforms what would be risky real-world operation into a safe, controllable simulation space. This allows extensive algorithm testing and validation to proceed at high speed without exposing vehicles or pedestrians to actual danger, effectively turning the harm of real-world testing into the benefit of safe, rapid iterative development.