公开(公告)号：US12118797B2

公开(公告)日：2024-10-15

申请号：US17457339

申请日：2021-12-02

Applicant: Aptiv Technologies AG

Inventor： Marco Braun ,  Moritz Luszek ,  Jan Siegemund

IPC: G06V20/56 ,  B60W40/10 ,  G06F18/2415 ,  G06N3/02

CPC classification number: G06V20/56 ,  B60W40/10 ,  G06F18/24155 ,  G06N3/02 ,  B60W2420/403 ,  B60W2420/408

Abstract: A method is provided for semantic segmentation of an environment of a vehicle. Via a processing device, a grid of cells is defined dividing the environment of the vehicle. A radar point cloud is received from a plurality of radar sensors, and at least one feature of the radar point cloud is assigned to each grid cell. By using a neural network including deterministic weights, high-level features are extracted for each grid cell. Several classes are defined for the grid cells. For layers of a Bayesian neural network, various sets of weights are determined probabilistically. Via the Bayesian neural network, confidence values are determined for each class and for each grid cell based on the high-level features and based on the various sets of weights in order to determine a predicted class and an extent of uncertainty for the predicted class for each grid cell.