Gm Cruise Holdings LLC

Elisha Ross Atkins

Adam Samuel Cadien

Daniel H Lee

Radu Raduta

Nicholas Semansky

Zhichang (Henry) Yan

Zhizhong (Joe) Yan

Yi-Yu Chen

The disclosed technology provides solutions for improving work ticketing triage and in particular, for improving the triage of work orders for detected failure events (or predicted failure events) for a fleet of vehicles, such as a fleet of autonomous vehicles (AVs). In some aspects, a process of the disclosed technology can include steps for receiving field data, processing the field data to identify two or more potential failure events associated with at least one AV from among one or more AVs, and automatically generating a work order for each of the two or more potential failure events. In some aspects, the process can further include steps for calculating a dynamic priority number for each of the two or more potential failure events and sorting the work orders based on the dynamic priority. Systems and machine-readable media are also provided.

Automated work ticketing and triage

Sensors coupled to a vehicle are calibrated using a dynamic scene with sensor targets around a motorized turntable that rotates the vehicle to different orientations. The sensors capture data at each vehicle orientation along the rotation. The vehicle's computer identifies representations of the sensor targets within the data captured by the sensors, and calibrates the sensor based on these representations, for example by generating a transformation based on mapping positions of these representations in the data to known positions of the sensor targets, such as to correct lens distortion, the transformation applied to post-calibration sensor data.

Vehicle sensor calibration system using dynamic scene

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San Francisco, CA, United States of America

Elisha Ross Atkins