Zoox, Inc.

Anas Lasram

James Graham Dolan

Ximing Li

A simulation system may generate radar data for synthetic simulations of autonomous vehicles by determining and applying radar masks for object radar data based on the attributes of simulated objects. A simulation system may determine a simulated object within a region of a simulated environment, and may apply a radar mask to determine the radar data within the region based on attributes of the simulated object. Such attributes may include the material properties, object type, and/or distance of the simulated object from the simulation sensors. Radar masks may be determining using masking percentages based on combinations of object attributes, and masks may be applied individually or by combining multiple masks for multiple occluding objects, in order to more accurately simulate the behavior of real-world radar signals in autonomous vehicle simulations.

Radar data masks in autonomous vehicle simulations

A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

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South San Francisco, CA, United States of America

Anas Lasram