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1.发明公开公开(公告)号：US20230406350A1
公开(公告)日：2023-12-21
申请号：US17959550
申请日：2022-10-04
Inventor： Minhae KWON , Dongsu LEE
CPC classification number: B60W60/0011 , B60W40/04 , G06N5/04 , G06N3/08 , G06F17/11 , B60W2554/4045 , B60W2554/4046
Abstract: The present disclosure relates to an apparatus and a method for deciding a behavior of an agent, and more particularly, to an apparatus and a method for deciding a behavior of a single agent using an episodic future thinking mechanism. The decision-making method according to an exemplary embodiment of the present disclosure includes collecting observation information and behavior information of a surrounding agent, by a first information collecting unit; inferring a character coefficient of a surrounding agent using data of the first information collecting unit, by a character inferring unit, collecting observation information of a main agent and the surrounding agent at a first time point, by a second information collecting unit; predicting a behavior of the surrounding agent based on the observation information and the character coefficient of the surrounding agent, by a behavior predicting unit, inferring expected observation information of the environment state and the surrounding agent at a second time point corresponding to the behavior prediction result of the surrounding agent, by a state inferring unit; and deciding a behavior of the main agent at the first time point based on the expected observation information of the environment state and the surrounding agent at a second time point, by a decision-making unit.
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公开(公告)号：US20230406327A1
公开(公告)日：2023-12-21
申请号：US17959515
申请日：2022-10-04
Inventor： Minhae KWON , Dongsu LEE
CPC classification number: B60W50/00 , G08G1/0116 , G08G1/0133 , G08G1/052 , G05B13/0265 , B60W60/001
Abstract: The present disclosure relates to a driving characteristic inference apparatus and method of a vehicle. According to an exemplary embodiment of the present disclosure, a driving characteristic inference method includes observing a target driving vehicle which is an observation target to generate driving data including behavior information of the target driving vehicle, by an observation module; performing reinforcement learning on an artificial intelligence model using learning data including a first driving characteristic coefficient, by a learning module; generating sampled inference behavior data with the driving data and the first driving character coefficient as an input of the artificial intelligence model, by a model utilization module; and comparing the generated inference behavior data with measured actual behavior data to determine the second driving characteristic coefficient, by an inference module.
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