公开(公告)号：US20250065917A1

公开(公告)日：2025-02-27

申请号：US18453489

申请日：2023-08-22

Applicant: GM Global Technology Operations LLC

Inventor： Michael Cui ,  Hyukseong Kwon ,  Rodolfo Valiente Romero ,  Andrew Howe ,  Alexander Waagen ,  Alexei Kopylov ,  Marcus James Huber ,  Alireza Esna Ashari Esfahani

IPC: B60W60/00 ,  B60W30/09 ,  B60W30/095

Abstract: According to several aspects, a method for path planning for a vehicle includes determining a predicted trajectory of a remote vehicle. The predicted trajectory of the remote vehicle includes a plurality of predicted trajectory nodes. The method further includes determining a plurality of possible trajectories for the vehicle. The plurality of possible trajectories includes a plurality of possible trajectory nodes. The method further includes determining one or more evaluation metrics of each of the plurality of possible trajectory nodes based at least in part on a weather condition in an environment surrounding the vehicle. The method further includes selecting an optimal trajectory for the vehicle from the plurality of possible trajectories based at least in part on the one or more evaluation metrics of each of the plurality of possible trajectory nodes. The method further includes performing a first action based at least in part on the optimal trajectory.

公开(公告)号：US20250044118A1

公开(公告)日：2025-02-06

申请号：US18362109

申请日：2023-07-31

Applicant: GM Global Technology Operations LLC

Inventor： Michael Cui ,  Hyukseong Kwon ,  Rodolfo Valiente Romero ,  Marcus James Huber ,  Alireza Esna Ashari Esfahani ,  Andrew Howe

IPC: G01C21/00 ,  G06V10/774 ,  G06V10/82 ,  G06V20/56 ,  G06V20/58 ,  G06V20/70

Abstract: A system for updating a road map for a vehicle includes a plurality of vehicle sensors and a vehicle controller in electrical communication with the plurality of vehicle sensors. The vehicle controller is programmed to gather input data about an environment surrounding the vehicle using the plurality of vehicle sensors. The input data includes at least one abnormal traffic pattern indication. The vehicle controller is further programmed to generate an input label map based at least in part on the input data. The vehicle controller is further programmed to generate a vehicle output label map based at least in part on the input label map. The vehicle output label map is generated using a machine learning algorithm. The vehicle controller is further programmed to perform a first action based at least in part on the vehicle output label map.