Method and mobility device using the method for path prediction through interaction analysis between objects using artificial intelligence

Abstract

A method for controlling an autonomous driving of a vehicle is introduced. The method may comprise generating a weighted adjacency matrix from an object graph, based on a location relative to an anticipated collision point among objects. The method may further comprise, based on this matrix and a graph convolution layer of a high-order graph model, generating an Mth-order adjacency matrix, defining interrelations among objects across M number of hops, generating object attribute information from this matrix and feature information defining an attribute of an object, generating, based on a combination layer of the high-order graph model, cumulative feature information by integrating the object attribute information, embedding the cumulative feature information into the object graph, generating, based on the embedding and a predicted path model, an object's predicted path, and outputting, based on this predicted path, a signal for controlling the autonomous driving of the vehicle.