公开(公告)号：US11155258B2

公开(公告)日：2021-10-26

申请号：US16362889

申请日：2019-03-25

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Lawrence A. Bush ,  Manpreet S. Bajwa ,  Shuqing Zeng ,  Rickie A. Sprague

IPC: B60W30/09 ,  B60W30/095 ,  G05D1/02 ,  G06N20/00 ,  G01S13/931

Abstract: A risk maneuver assessment system and method to generate a perception of an environment of a vehicle and a behavior decision making model for the vehicle; a sensor system configured to provide the sensor input in the environment for filtering target objects; one or more modules configured to map and track target objects to make a candidate detection from multiple candidate detections of a true candidate detection as the tracked target object; apply a Markov Random Field (MRF) algorithm for recognizing a current situation of the vehicle and predict a risk of executing a planned vehicle maneuver at the true detection of the dynamically tracked target; apply mapping functions to sensed data of the environment for configuring a machine learning model of decision making behavior of the vehicle; and apply adaptive threshold to cells of an occupancy grid for representing an area of tracking of objects within the vehicle environment.

公开(公告)号：US20200307561A1

公开(公告)日：2020-10-01

申请号：US16362889

申请日：2019-03-25

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Lawrence A. Bush ,  Manpreet S. Bajwa ,  Shuqing Zeng ,  Rickie A. Sprague

IPC: B60W30/09 ,  B60W30/095 ,  G01S13/93 ,  G05D1/02 ,  G06N20/00

Abstract: A risk maneuver assessment system and method to generate a perception of an environment of a vehicle and a behavior decision making model for the vehicle; a sensor system configured to provide the sensor input in the environment for filtering target objects; one or more modules configured to map and track target objects to make a candidate detection from multiple candidate detections of a true candidate detection as the tracked target object; apply a Markov Random Field (MRF) algorithm for recognizing a current situation of the vehicle and predict a risk of executing a planned vehicle maneuver at the true detection of the dynamically tracked target; apply mapping functions to sensed data of the environment for configuring a machine learning model of decision making behavior of the vehicle; and apply adaptive threshold to cells of an occupancy grid for representing an area of tracking of objects within the vehicle environment.