Systems and Methods for Streaming Processing for Autonomous Vehicles

An autonomy computing system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising:
• (a) accessing autonomy data descriptive of a first object and a second object in a surrounding environment of an autonomous vehicle;
• (b) determining an interaction classification associated with the first object relative to the second object, the interaction classification indicative of a likelihood that the first object and the second object will interact;
• (c) obtaining a first portion of additional autonomy data descriptive of an updated state of the first object;
• (d) determining an expected time estimate for receiving a second portion of additional autonomy data descriptive of an updated state of the second object;
• (e) when the expected time estimate for receiving the second portion of additional autonomy data satisfies a first threshold, determining a predicted updated state of the second object, a predicted track of the first object based on the updated state of the first object, and a predicted track of the second object based on the predicted updated state of the second object;
• and
• (f) controlling navigation of the autonomous vehicle based on the predicted track of the first object and the predicted track of the second object.

An autonomous vehicle (AV) control system, comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising:
• (a) accessing autonomy data descriptive of a first object and a second object in a surrounding environment of an autonomous vehicle;
• (b) determining an interaction classification of the first object relative to the second object, the interaction classification indicative of a likelihood that the first object and the second object will interact;
• (c) obtaining, by a first system of the AV control system, a first portion of additional autonomy data descriptive of an updated state of the first object;
• (d) determining an expected time estimate for receiving a second portion of additional autonomy data descriptive of an updated state of the second object;
• (e) when the expected time estimate for receiving the second portion of additional autonomy data satisfies a first threshold, determining a predicted updated state of the second object, a predicted track of the first object based on the updated state of the first object, and a predicted track of the second object based on the predicted updated state of the second object, and transmitting the predicted track of the first object and the predicted track of the second object from the first system to a second system of the AV control system;
• and
• (f) controlling navigation of the autonomous vehicle based on the predicted track of the first object and the predicted track of the second object.

An autonomous vehicle, comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising:
• (a) accessing autonomy data descriptive of a first object and a second object in a surrounding environment of an autonomous vehicle;
• (b) determining a priority classification associated with the first object, the priority classification classifying the first object as one of high-priority or low-priority;
• (c) obtaining a first portion of additional autonomy data descriptive of an updated state of the first object;
• (d) when the priority classification associated with the first object is high-priority, determining a predicted updated state for the second object, a predicted track of the first object based on the updated state of the first object, and a predicted track of the second object based on the predicted updated state of the second object;
• and
• (e) controlling navigation of the autonomous vehicle based on the predicted track of the first object and the predicted track of the second object.