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公开(公告)号：US20240391503A1
公开(公告)日：2024-11-28
申请号：US18670785
申请日：2024-05-22
Inventor： You-Seung Song , Kyoung-Wook Min , Jeong Dan Choi
IPC: B60W60/00 , G01S13/931 , G06F11/00 , H04W4/44 , H04W4/46
Abstract: A precise position correction method based on collaborative cognition in an autonomous vehicle includes: estimating object information on a road within a detection range on an autonomous vehicle; receiving a shared message from at least one of a first vehicle (another connected vehicle (CV) or automated vehicle (CAV)) and a road infrastructure device for V2X communication on the road, receiving the message including driving status information of the other CV when the first vehicle is the other CV, and receiving the driving status information of the other CAV and the message about a second vehicle, in which the V2X communication is not possible, recognized by the other CAV; calculating an estimated error by comparing the estimated object information with the message; and setting a radius based on the first vehicle corresponding to an estimated error application radius in consideration of a distance between the autonomous vehicle and the first vehicle.
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公开(公告)号：US20250157329A1
公开(公告)日：2025-05-15
申请号：US18935779
申请日：2024-11-04
Inventor： MyungIn Ji , JINWOO KIM , Kyoung-Wook Min , KYOUNG HWAN AN
IPC: G08G1/07
Abstract: Disclosed are an apparatus and method for controlling traffic lights, and more particularly, an apparatus and method for controlling traffic lights, which can provide information on the remaining time of a traffic signal. The apparatus for controlling traffic lights includes a traffic signal display controller configured to transmit a pattern control command including information related to the remaining time of a current traffic signal and traffic lights configured to display information on a traffic signal by receiving the pattern control command.
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公开(公告)号：US12300026B2
公开(公告)日：2025-05-13
申请号：US17575317
申请日：2022-01-13
Inventor： Jung-Gyu Kang , Kyoung-Wook Min , Jae-Hyuck Park , Doo-Seop Choi , Jeong-Dan Choi
Abstract: Disclosed herein is a method for deidentifying a driver image dataset. The method includes generating a combination dataset having a preset size based on a driver image dataset, extracting face shape information from each of pieces of driver image data forming the driver image dataset, and generating a deidentified dataset using the combination dataset and the face shape information.
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4.发明申请公开(公告)号：US20250026380A1
公开(公告)日：2025-01-23
申请号：US18421024
申请日：2024-01-24
Inventor： Dooseop Choi , Kyoung-Wook Min
IPC: B60W60/00 , B60W50/00 , G06N3/0442 , G06N7/01
Abstract: The present invention relates to a method and apparatus for predicting future trajectories of nearby vehicles for autonomous driving. The method of predicting the future trajectories of nearby vehicles according to the present invention includes generating past trajectories of the nearby vehicles, extracting local routes along which the nearby vehicles are travelable from a high-definition map, encoding the past trajectories and the local routes, and generating the future trajectories of the nearby vehicles using a deep neural network on the basis of the encoded past trajectories and an updated local route encoding.
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公开(公告)号：US12154033B2
公开(公告)日：2024-11-26
申请号：US17886198
申请日：2022-08-11
Inventor： Joo-Young Kim , Kyoung-Wook Min , Yong-Woo Jo , Doo-Seop Choi , Jeong-Dan Choi
Abstract: Disclosed herein are a deep network learning method using an autonomous vehicle and an apparatus for the same. The deep network learning apparatus includes a processor configured to select a deep network model requiring an update in consideration of performance, assign learning amounts for respective vehicles in consideration of respective operation patterns of multiple autonomous vehicles registered through user authentication, distribute the deep network model and the learning data to the multiple autonomous vehicles based on the learning amounts for respective vehicles, and receive learning results from the multiple autonomous vehicles, and memory configured to store the deep network model and the learning data.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240190420A1
公开(公告)日：2024-06-13
申请号：US18519203
申请日：2023-11-27
Inventor： Kyung Bok Sung , Kyoung-Wook Min , Jeong-Woo Lee , Jeong Dan CHOI
CPC classification number: B60W30/09 , B60W50/0097 , B60W50/06 , B60W60/0015 , G05B13/0265 , G08G1/161 , B60W2556/45
Abstract: A method of predicting a possibility of an accident is provided. The method includes abstracting surrounding situation data and movement data of an ego-vehicle input from a sensor to generate abstracted driving situation data by using an abstraction module executed by a processor, calculating a digitized score of a possibility of an accident of the ego-vehicle by using a calculation module executed by the processor, based on the abstracted driving situation data, and generating action data of the ego-vehicle for decreasing the possibility of the accident by using an action generating module executed by the processor, based on the score.
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公开(公告)号：US11507783B2
公开(公告)日：2022-11-22
申请号：US17380663
申请日：2021-07-20
Inventor： Dong-Jin Lee , Do-Wook Kang , Jungyu Kang , Joo-Young Kim , Kyoung-Wook Min , Jae-Hyuck Park , Kyung-Bok Sung , Yoo-Seung Song , Taeg-Hyun An , Yong-Woo Jo , Doo-Seop Choi , Jeong-Dan Choi , Seung-Jun Han
Abstract: Disclosed herein are an object recognition apparatus of an automated driving system using error removal based on object classification and a method using the same. The object recognition method is configured to train a multi-object classification model based on deep learning using training data including a data set corresponding to a noise class, into which a false-positive object is classified, among classes classified by the types of objects, to acquire a point cloud and image data respectively using a LiDAR sensor and a camera provided in an autonomous vehicle, to extract a crop image, corresponding to at least one object recognized based on the point cloud, from the image data and input the same to the multi-object classification model, and to remove a false-positive object classified into the noise class, among the at least one object, by the multi-object classification model.
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公开(公告)号：US20250095489A1
公开(公告)日：2025-03-20
申请号：US18751421
申请日：2024-06-24
Inventor： JU WAN KIM , Jeong-Woo Lee , Kyoung-Wook Min , Jeong Dan Choi
IPC: G08G1/0967
Abstract: A training data service system for operation scope-oriented autonomous driving shuttle includes a communication module configured to collect an autonomous driving data set from an autonomous driving vehicle to construct training data and distribute the training data to an autonomous driving shuttle, a memory configured to store a program for construction of the training data, and a processor configured to generate query data including road shape information, road attribute information, traffic environment information, and collection sensor information by executing the program stored in the memory, detect data satisfying a condition corresponding to the query data from a previously collected autonomous driving data set, construct training data for the autonomous driving shuttle, based on the detected data, and distribute the constructed training data to a corresponding autonomous driving shuttle.
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公开(公告)号：US20250018939A1
公开(公告)日：2025-01-16
申请号：US18678658
申请日：2024-05-30
Inventor： Jinhong NOH , Jooyoung Kim , Kyoung-Wook Min , Yongwoo Jo
IPC: B60W30/095 , B60W60/00
Abstract: According to the present invention, autonomous driving may be performed according to an autonomous driving strategy defined in trajectory constraints generated based on object recognition information about a road map and various traffic participants, and thus, because collision avoidance does not obstruct traffic of an adjacent lane despite a situation where an autonomous vehicle stops for avoiding a collision, the stability of autonomous driving may increase and vehicle traffic management may be easily performed.
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10.发明申请公开(公告)号：US20240375647A1
公开(公告)日：2024-11-14
申请号：US18657179
申请日：2024-05-07
Inventor： Jinwoo KIM , Ki Tae Kim , Kyoung-Wook Min , Myungwook Park , Kyoung Hwan An , Myungln Ji , Jeong Dan Choi , Seung Jun Han
IPC: B60W30/095 , B60W50/14 , G06V20/58
Abstract: Disclosed are a device for multiple interactions between moving objects and autonomous vehicles and a driving method thereof. The device for multiple interactions between moving objects and autonomous vehicles includes memory in which a program for multiple interactions between moving objects and autonomous vehicles has been stored and a processor configured to execute the program. The processor confirms the status of the moving object including at least any one of a nearby vehicle, a pedestrian, and a mobility user and transmits a control command for a notification function that shares situation information.
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