公开(公告)号：US20220221301A1

公开(公告)日：2022-07-14

申请号：US17147745

申请日：2021-01-13

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Meena Nagappan ,  Hyukseong Kwon ,  Joshua Lampkins ,  Rajan Bhattacharyya

IPC: G01C21/00 ,  B60W10/04 ,  B60W10/10 ,  B60W10/18 ,  B60W10/20

Abstract: A method for updating a localization of an autonomous vehicle includes receiving perception input data from a sensor of the autonomous vehicle and receiving map data including road lane information in a vicinity of the autonomous vehicle. The method includes processing the perception input data to extract perceived road lane information including a perceived x position, a perceived y position, a perceived z position, a perceived lane type, a perceived lane color, and a perceived lane curvature and processing the map data to extract map road lane information including a map x position, a map y position, a map z position, a map lane type, a map lane color, and a map lane curvature. The method includes calculating a transformation matrix from the perceived road lane information and the map road lane information and updating the map data and a localization of the vehicle based on the transformation matrix.

公开(公告)号：US12243328B2

公开(公告)日：2025-03-04

申请号：US17820317

申请日：2022-08-17

Applicant: GM Global Technology Operations LLC

Inventor： Jiejun Xu ,  Kenji Yamada ,  Michael J. Daily ,  Alireza Esna Ashari Esfahani ,  Hyukseong Kwon ,  Darren Michael Chan ,  Alan Perry ,  Joshua Lampkins

IPC: G06V20/58 ,  G06N3/045 ,  G06V10/82 ,  G06V20/62 ,  G06V30/262

Abstract: A road sign interpretation system includes a front-facing camera mounted on or in a vehicle collecting image data of multiple road signs. A first convolutional neural network (CNN) receives the image data from the front-facing camera and yields a set of sign predictions including one or more sign text instances. A second CNN defining a text extractor receives the image data from the front-facing camera and extracts text candidates including the multiple sign text instances. Sign and sign data localization is provided in the second CNN to compute a text order from the multiple sign text instances. A sign text synthesizer module receives individual sign text instances from the first CNN and individual ones of the sign text instances in digitized forms from an optical character recognizer (OCR). A semantic encoding and interpretation module receives the sign text instances and identifies semantics of the multiple road signs.

公开(公告)号：US11747164B2

公开(公告)日：2023-09-05

申请号：US17147745

申请日：2021-01-13

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Meena Nagappan ,  Hyukseong Kwon ,  Joshua Lampkins ,  Rajan Bhattacharyya

IPC: G01C21/00 ,  G05D1/02 ,  B60W10/04 ,  B60W10/10 ,  B60W10/18 ,  B60W10/20

CPC classification number: G01C21/3819 ,  B60W10/04 ,  B60W10/10 ,  B60W10/18 ,  B60W10/20 ,  G01C21/3833 ,  B60W2552/05 ,  B60W2552/30 ,  B60W2552/53 ,  B60W2556/40 ,  B60W2556/45 ,  B60W2710/1005 ,  B60W2710/18 ,  B60W2710/20 ,  B60W2720/106 ,  B60W2720/125 ,  G05D1/0212

Abstract: A method for updating a localization of an autonomous vehicle includes receiving perception input data from a sensor of the autonomous vehicle and receiving map data including road lane information in a vicinity of the autonomous vehicle. The method includes processing the perception input data to extract perceived road lane information including a perceived x position, a perceived y position, a perceived z position, a perceived lane type, a perceived lane color, and a perceived lane curvature and processing the map data to extract map road lane information including a map x position, a map y position, a map z position, a map lane type, a map lane color, and a map lane curvature. The method includes calculating a transformation matrix from the perceived road lane information and the map road lane information and updating the map data and a localization of the vehicle based on the transformation matrix.

公开(公告)号：US20240062555A1

公开(公告)日：2024-02-22

申请号：US17820317

申请日：2022-08-17

Applicant: GM Global Technology Operations LLC

Inventor： Jiejun Xu ,  Kenji Yamada ,  Michael J. Daily ,  Alireza Esna Ashari Esfahani ,  Hyukseong Kwon ,  Darren Michael Chan ,  Alan Perry ,  Joshua Lampkins

IPC: G06V20/58 ,  G06V20/62 ,  G06V10/82 ,  G06V30/262 ,  G06N3/04

CPC classification number: G06V20/582 ,  G06V20/63 ,  G06V10/82 ,  G06V30/274 ,  G06N3/0454

Abstract: A road sign interpretation system includes a front-facing camera mounted on or in a vehicle collecting image data of multiple road signs. A first convolutional neural network (CNN) receives the image data from the front-facing camera and yields a set of sign predictions including one or more sign text instances. A second CNN defining a text extractor receives the image data from the front-facing camera and extracts text candidates including the multiple sign text instances. Sign and sign data localization is provided in the second CNN to compute a text order from the multiple sign text instances. A sign text synthesizer module receives individual sign text instances from the first CNN and individual ones of the sign text instances in digitized forms from an optical character recognizer (OCR). A semantic encoding and interpretation module receives the sign text instances and identifies semantics of the multiple road signs.