-
公开(公告)号：US20250095487A1
公开(公告)日：2025-03-20
申请号：US18404077
申请日：2024-01-04
Inventor： Min Hae KWON , Chan In EOM , Dong Su LEE
IPC: G08G1/0967 , B60W30/14 , B60W60/00 , G08G1/01
Abstract: A traffic control method and apparatus with an autonomous vehicle based on adaptive reward. A traffic control apparatus for an autonomous vehicle based on adaptive reward comprises an information observation unit that collects observation information from a sensing module of an autonomous vehicle or a roadside unit (RSU); a policy execution unit that decides on an action including adjusting acceleration and changing lanes of the autonomous vehicle based on the observation information and policy; and a reward determination unit that determines reward according to observation information at a next timestep according to the decision made, wherein reward in the reward determination unit includes penalty in an event of an accident and reward when driving, wherein the reward when driving includes an adaptive target speed reward term, a successful lane change reward term, and a safety distance compliance reward term that are adaptively determined according to road traffic.
-
公开(公告)号：US20250077943A1
公开(公告)日：2025-03-06
申请号：US18414026
申请日：2024-01-16
Inventor： Min Hae KWON , Dong Su LEE
Abstract: An offline reinforcement learning-based foresighted decision-making apparatus and method for interaction between multiple agents. The offline reinforcement learning-based foresighted decision-making apparatus comprises a processor; and a memory connected to the processor, wherein the memory comprises program instructions for performing steps comprising collecting a raw data set about environment surrounding the multiple agents, processing the raw data set into a first data set containing at least one of state information, observation information, and action information in reinforcement learning, generating an episodic future data set from the first data set based on some of the state information, observation information, and action information, generating an episodic future data prediction model using the episodic future data set, and learning an optimal policy for decision-making for each of the multiple agents through offline reinforcement learning using the generated episodic future data prediction model or the episodic future data set.
-
3.发明公开公开(公告)号：US20240242596A1
公开(公告)日：2024-07-18
申请号：US18219628
申请日：2023-07-07
Inventor： Min Hae KWON , Chan In EOM , Dong Su LEE
IPC: G08G1/01 , G08G1/0967
CPC classification number: G08G1/0116 , G08G1/096725
Abstract: Provided is a method and an apparatus for determining a vehicle behavior, and more specifically, to a method and an apparatus for determining a vehicle behavior for bottleneck congestion control in a bottleneck section. Tn apparatus for determining a vehicle behavior may include an information collection unit collecting surrounding information of a target driving vehicle from a road side unit (RSU), a vehicle observation unit obtaining observation information based on the target driving vehicle from a sensing module mounted on the target driving vehicle, a reward determination unit determining a reward for the target driving vehicle through a reward function which uses the surrounding information and the observation information, a model training unit updating and training a decision making model through the reward, and a behavior determination unit determining a behavior of the target driving vehicle by inputting the observation information into the decision making model.
-
公开(公告)号：US20240239350A1
公开(公告)日：2024-07-18
申请号：US18139602
申请日：2023-04-26
Inventor： Minhae KWON , Dong Su LEE
CPC classification number: B60W40/09 , B60W60/001 , B60W2554/80 , B60W2556/45
Abstract: Provided is a method and an apparatus of inferring a stochastic driving characteristic of a driving vehicle. The driving characteristic inferring apparatus may include a model training unit which trains a plural driving characteristic model and an inference model using learning driving data of a learning driving vehicle, and a driving characteristic inferring unit which infers a driving characteristic coefficient representing a driving characteristic of a target driving vehicle with driving data of the target driving vehicle as an input of the inference model.
-
-
-
Search Results
4
records
(took 0.018 seconds)
