Zoox, Inc.

Aditya Pramod Khadilkar

Siavosh Rezvan Behbahani

Andrew Scott Crego

Subhasis Das

Sai Anurag Modalavalasa

Gerrit Bagschik

Muhammad Farooq Rama

An error estimation component may generate contours or a heat map of a likelihood that an object detection or prediction generated by a perception component of an autonomous vehicle is inaccurate. The contours or heat map may be used to lock or unlock actions available to a planning component and the planning component may use the contours or heat for determining a trajectory for controlling the autonomous vehicle. The planning component may additionally or alternatively alter operation of a sensor or determine a trajectory to unlock a target action that is currently locked due to a size/extent of uncertainty indicated by a contour/heat map.

Perception error model for fast simulation and estimation of perception system reliability and/or for control system tuning

Fast simulation of a scenario (e.g., simulating the scenario once as opposed to multiple times) to determine performance metric(s) of a configuration of one or more components of an autonomous vehicle may include training a perception error model based at least in part on a difference between a prediction output by a perception component associated with a future time and a perception output associated with that future time once that future time has arrived. A contour or heat map output by the perception error model may be used to determine one or more performance metric(s) associated with a component of the autonomous vehicle and identify which component may cause a degradation of a performance metric.

Techniques associated with generating simulation scenarios for simulating a vehicle controller are discussed herein. Log data may include sensor data captured by sensors of a vehicle. The log data may represent objects in an environment. Objects may be associated with a region of a discretized representation of the environment relative to the vehicle. Specific states of objects (relative position in a region type, velocity, classification, size, etc.) may represent an instance of an occupation. Log data can be aggregated based on similar region type and/or object state. A statistical model over object states can be determined for each region type and can later be sampled to determine simulation parameters. A simulation scenario can be generated based on the simulation parameters, and a vehicle controller can be evaluated based on the simulation scenario.

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Foster City, CA, United States of America

Aditya Pramod Khadilkar