Lyft, Inc.

Sheng Yang

David Tse-Zhou Lu

Emilie Jeanne Anne Danna

Ying Liu

Weiyi Hou

Suneet Rajendra Shah

Ranjith Unnikrishnan

Ivan Kirigan

Daxiao Liu

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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Palo Alto, CA, United States of America

Sheng Yang