Zoox, Inc.

Andrew Glen Tsao

Eric Yan Tin Chu

Deepan Subrahmanian Palguna

Antonio Prioletti

Clement Besson

Rishi Bhatnager

Paul Syta

Adam Kane Wiener

Techniques associated with ingesting data based on the catalog are discussed herein. In some examples, log data associated with a vehicle in an environment can be received. The log data can include at least one of location data, state data, or prediction data. A sequence of data can be identified as corresponding to a driving sequence based on a set of rules. An identification of the driving sequence involving the vehicle in the environment can be associated with the sequence of data in a database. An inquiry for retrieving the sequence of data or information associated with the driving sequence can be received. In response to the inquiry, the sequence of data or information associated with the driving sequence can be returned.

Systems and methods for ingesting data based on predefined driving sequences

Techniques for analyzing driving scenarios are discussed herein. For example, techniques may include determining, based at least in part on log data representing a scenario of the vehicle operating in an environment, a plurality of frames of the scenario. For individual frames, the techniques may determine a respective set of discrete areas of the environment based on a respective position of the vehicle in the frame, determine a respective set of labels for the discrete areas for the individual frame, determine respective agent feature values of agent features for agents in individual discrete areas of the discrete areas of the individual frame, and determine a feature vector for the scenario by aggregating agent feature values of the individual frames based on the labels for the discrete areas for the frame. An action may then be performed based at least in part on the feature vector.

Determining scene similarity

Systems and techniques for determining and predicting the operational capacity of a fleet of vehicles are described. Data may be collected for various fleet parameters (e.g., based on vehicle and fleet operations) and distributions of such data may be used to determine rates of change for the parameters. Predicted distributions of the fleet parameters may be determined based on historical parameter distributions and/or predicted distributions and the corresponding rates of change. Fleet operational capacity determinations may be made based on these parameter distributions, including probability distributions of predicted fleet operational capacity measurements.

Systems and methods for determining fleet capacity

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San Carlos, CA, United States of America

Andrew Glen Tsao