Lyft, Inc.

Ranjith Unnikrishnan

David Tse-Zhou Lu

Emilie Jeanne Anne Danna

Ying Liu

Weiyi Hou

Suneet Rajendra Shah

Ivan Kirigan

Daxiao Liu

Sheng Yang

Systems, methods, and non-transitory computer-readable media can receive a query specifying at least one example scenario. At least one image representation of the at least one example scenario can be encoded based on the query to produce at least one encoded representation. An embedding of the at least one representation of the at least one example scenario can be generated based on the at least one encoded representation. At least one scenario that is similar to the at least one example scenario can be identified based at least in part on the embedding of the at least one representation of the at least one example scenario and an embedding representing the at least one scenario. Information describing the at least one identified scenario can be provided in response to the query.

Systems and methods for encoding and searching scenario information

Systems, methods, and non-transitory computer-readable media can determine sensor data captured by at least one sensor of a vehicle while navigating an environment over a period of time. Information describing one or more agents associated with the environment during the period of time can be determined based at least in part on the captured sensor data. A parameter-based encoding describing the one or more agents associated with the environment during the period of time can be generated based at least in part on the determined information and a scenario schema, wherein the parameter-based encoding provides a structured representation of the information describing the one or more agents associated with the environment. A scenario represented by the parameter-based encoding can be determined based at least in part on a cluster of parameter-based encodings to which the parameter-based encoding is assigned.

Approaches for encoding environmental information

Systems, methods, and non-transitory computer-readable media can access a plurality of parameter-based encodings providing a structured representation of an environment captured by one or more sensors associated with a plurality of vehicles traveling through the environment. A given parameter-based encoding of the environment identifies one or more agents that were detected by a vehicle within the environment and respective location information for the one or more agents within the environment. The plurality of parameter-based encodings can be clustered into one or more clusters of parameter-based encodings. At least one scenario associated with the environment can be determined based at least in part on the one or more clusters of parameter-based encodings.

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Fremont, CA, United States of America

Ranjith Unnikrishnan