Systems and methods providing adaptive path planning techniques utilizing localized learning with global planning are described. The adaptive path planning of embodiments provides global guidance and performs local planning based on localized learning, wherein the global guidance provides a planned path through the dynamic environment from a start location to a selected destination while the local planning provides for dynamic interaction within the environment in reaching the destination, such as in response to obstacles entering the planned path. Global guidance may combine an initial global path with history information for providing a global path configured to avoid points of frequent traffic conflicts. Local planning may utilize localized deep reinforcement learning to direct interactions of an automated vehicle traversing the global path in a dynamic environment, such as in response to obstacles entering the global path. Sequential localized maps may be generated for deep learning models utilized by localized training techniques.
SYSTEMS AND METHODS FOR ADAPTIVE PATH PLANNING