Gm Global Technolgoy Operations, Inc.

Gm Cruise Holdings LLC

Andrea Allais

Micah Christopher Chambers

Adam Samuel Cadien

Elliot Branson

William Gongshu Xie

Gautier Minster

Roman Sergeev

An autonomous vehicle is described herein. The autonomous vehicle generates segmentation scenes based upon lidar data generated by a lidar sensor system of the autonomous vehicle. The lidar data includes points indicative of positions of objects in a driving environment of the autonomous vehicle. The segmentation scenes comprise regions that are indicative of the objects in the driving environment. The autonomous vehicle generates scores for each segmentation scene based upon characteristics of each segmentation scenes and selects a segmentation scene based upon the scores. The autonomous vehicle then operates based upon the segmentation scene.

Conflict resolver for a lidar data segmentation system of an autonomous vehicle

An autonomous vehicle is described herein. The autonomous vehicle includes a lidar sensor system. The autonomous vehicle additionally includes a computing system that executes a lidar segmentation system, wherein the lidar segmentation system is configured to identify objects that are in proximity to the autonomous vehicle based upon output of the lidar sensor system. The computing system further includes a deep neural network (DNN), where the lidar segmentation system identifies the objects in proximity to the autonomous vehicle based upon output of the DNN.

Autonomous vehicle controlled based upon a lidar data segmentation system

Systems, methods, and devices are disclosed for synchronizing a map within shared memory for a navigating autonomous vehicle. A map, defined by a geographical area around an autonomous vehicle navigating a route, can be received and stored in shared memory. The shared memory can be a specific physical block of RAM. Concurrent access to the map within the shared memory can be granted to downstream nodes on the autonomous vehicle as the autonomous vehicle navigates the route. This shares the map among many nodes while, at the same time, allowing updates to the map without blocking those nodes at any time.

Shared tile map with live updates

Autonomous vehicle controlled based upon a LIDAR data segmentation system

An autonomous vehicle is described herein. The autonomous vehicle includes a lidar sensor system. The autonomous vehicle additionally includes a computing system that executes a lidar segmentation system, wherein the lidar segmentation system is configured to identify objects that are in proximity to the autonomous vehicle based upon output of the lidar sensor system. The computing system further includes a deep neural network (DNN), where the lidar segmentation system identifies the objects in proximity to the autonomous vehicle based upon output of the DNN. The computing system is further configured to align a heightmap to lidar data output by the lidar sensor system based upon output of the DNN. The lidar segmentation system can identify objects in proximity to the autonomous vehicle based upon the aligned heightmap.

Autonomous vehicle controlled based upon a lidar data segmentation system and an aligned heightmap

An autonomous vehicle generates segmentation scenes based upon lidar data generated by a lidar sensor system of the autonomous vehicle. The lidar data includes points indicative of positions of objects in a driving environment of the autonomous vehicle. The segmentation scenes comprise regions that are indicative of the objects in the driving environment. The autonomous vehicle generates scores for each segmentation scene based upon characteristics of each segmentation scenes and selects a segmentation scene based upon the scores. The autonomous vehicle then operates based upon the segmentation scene.

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San Francisco, CA, United States of America

Andrea Allais