Systems and methods for determining future intentions of objects

A system, comprising:

• a processor;
• a non-transitory computer-readable storage medium comprising programming instructions that are configured to cause the processor to implement a method for operating an autonomous vehicle, wherein the programming instructions comprise instructions to:
• use sensor data to track an object that was detected in proximity to the autonomous vehicle;
• classify the object into at least one dynamic state class of a plurality of dynamic state classes, wherein at least two dynamic state classes of the plurality of dynamic state classes indicate different possible reasons for any object being stationary, and a first one of the at least two dynamic state classes comprises a blocking object class and a second one of the at least two dynamic state classes comprises a parked vehicle class, a functionally stopped vehicle class, or a queued vehicle class;
• use a result from said classifying to determine at least one predicted future intention of the object by:
• accessing a single hierarchical probability tree comprising a plurality of first nodes respectively associated with a plurality of different dynamic state classes, a plurality of second nodes respectively associated with a plurality of different goal classes, and a plurality of third nodes respectively associated with a plurality of different proposed future intention classes;
• inputting the at least one dynamic state class into the single hierarchical probability tree;
• transforming the at least one dynamic state class into at least one goal class of the plurality of different goal classes by identifying at least one second node of the second nodes of the single hierarchical tree that is connected to at least one of the first nodes associated with the at least one dynamic state class, wherein the plurality of different goal classes specify possible current aims associated with the object;
• transforming the at least one goal class into at least one proposed future intention class of the plurality of different proposed future intention classes by identifying at least one third node of the third nodes of the single hierarchical tree that is connected to the at least one second node which was previously identified;
• and
• determining the at least one predicted future intention of the object based on the at least one proposed future intention class of the plurality of different proposed future intention classes that is associated with the at least one third node which was previously identified;
• perform at least one next cycle of said classifying, transforming and determining to obtain at least one next proposed future intention class for the object;
• combine a probability associated with the at least one proposed future intention class and a probability associated with the at least one next proposed future intention class to generate an aggregate probability;
• and
• cause the autonomous vehicle to perform at least one autonomous driving operation based on the at least one predicted future intention determined for the object.

A non-transitory computer-readable medium that stores instructions that, when executed by at least one computing device, will cause the at least one computing device to perform operations comprising:

• using sensor data to track an object that was detected in proximity to the autonomous vehicle;
• classifying the object into at least one dynamic state class of a plurality of dynamic state classes, wherein at least two dynamic state classes of the plurality of dynamic state classes indicate different possible reasons for any object being stationary, and a first one of the at least two dynamic state classes comprises a blocking object class and a second one of the at least two dynamic state classes comprises a parked vehicle class, a functionally stopped vehicle class, or a queued vehicle class;
• using a result from said classifying to determine at least one predicted future intention of the object by:
• accessing a single hierarchical probability tree comprising a plurality of first nodes respectively associated with a plurality of different dynamic state classes, a plurality of second nodes respectively associated with a plurality of different goal classes, and a plurality of third nodes respectively associated with a plurality of different proposed future intention classes;
• inputting the at least one dynamic state class into the single hierarchical probability tree;
• transforming the at least one dynamic state class into at least one goal class of the plurality of different goal classes by identifying at least one second node of the second nodes of the single hierarchical tree that is connected to at least one of the first nodes associated with the at least one dynamic state class, wherein the plurality of different goal classes specify possible current aims associated with the object;
• transforming the at least one goal class into at least one proposed future intention class of the plurality of different proposed future intention classes by identifying at least one third node of the third nodes of the single hierarchical tree that is connected to the at least one second node which was previously identified;
• and
• determining the at least one predicted future intention of the object based on the at least one proposed future intention class of the plurality different proposed future intention classes that is associated with the at least one third node which was previously identified;
• performing at least one next cycle of said classifying, transforming and determining to obtain at least one next proposed future intention class for the object;
• combining a probability associated with the at least one proposed future intention class and a probability associated with the at least one next proposed future intention class to generate an aggregate probability;
• and
• causing, by the computing device, the autonomous vehicle to perform at least one autonomous driving operation based on the at least one predicted future intention determined for the object.