Systems and methods for generating motion forecast data for actors with respect to an autonomous vehicle and training a machine learned model for the same

A computing system comprising:

• one or more processors, and
• one or more memory resources storing instructions executable by the one or more processors to cause the one or more processors to:
• generate, using an object detection model, object detection data describing a location of an actor within an environment of an autonomous vehicle;
• generate, using a graph neural network, motion forecast data associated with the actor, wherein:
• the graph neural network comprises a plurality of nodes, wherein a first node of the plurality of nodes corresponds to the actor, and
• the graph neural network is configured to model anticipated interactions between the actor and other actors in the environment by passing one or more messages among the plurality of nodes to update at least one node state of the first node, wherein the anticipated interactions comprise an interaction between the actor and at least one other actor which alters a trajectory of the actor or the at least one other actor in the environment;
• determine a motion plan for the autonomous vehicle based on the motion forecast data;
• and
• control the autonomous vehicle based on the motion plan.

A non-transitory computer-readable media storing instructions executable by one or more processors of an autonomous vehicle computing system to cause the one or more processors to:

• generate, using an object detection model, object detection data describing a location of an actor within an environment of an autonomous vehicle;
• generate, using a graph neural network, motion forecast data associated with the actor, wherein:
• the graph neural network comprises a plurality of nodes, wherein a first node of the plurality of nodes corresponds to the actor, and
• the graph neural network is configured to model anticipated interactions between the actor and other actors in the environment by passing one or more messages among the plurality of nodes to update at least one node state of the first node, wherein the anticipated interactions comprise an interaction between the actor and at least one other actor which alters a trajectory of the actor or the at least one other actor in the environment;
• determine a motion plan for the autonomous vehicle based on the motion forecast data;
• and
• control the autonomous vehicle based on the motion plan.