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1.发明申请公开(公告)号：US20200172093A1
公开(公告)日：2020-06-04
申请号：US16521990
申请日：2019-07-25
Inventor： Dongsuk Kum , Seung Je Yoon , Jaehwan Kim , Sanmin Kim
Abstract: Disclosed are probabilistic prediction for a motion of a lane-based surrounding vehicle and a longitudinal control method and apparatus using the same. The method includes obtaining surrounding vehicle information using a sensor, predicting a target lane of the surrounding vehicle based on the obtained surrounding vehicle information, performing future driving trajectory prediction for each target lane based on the surrounding vehicle information, and computing a probability of a collision likelihood based on a target lane and trajectory predictions of the surrounding vehicle in which future uncertainty has been taken into consideration and performing longitudinal control for collision avoidance.
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公开(公告)号：US11433884B2
公开(公告)日：2022-09-06
申请号：US16521990
申请日：2019-07-25
Inventor： Dongsuk Kum , Seung Je Yoon , Jaehwan Kim , Sanmin Kim
Abstract: Disclosed are probabilistic prediction for a motion of a lane-based surrounding vehicle and a longitudinal control method and apparatus using the same. The method includes obtaining surrounding vehicle information using a sensor, predicting a target lane of the surrounding vehicle based on the obtained surrounding vehicle information, performing future driving trajectory prediction for each target lane based on the surrounding vehicle information, and computing a probability of a collision likelihood based on a target lane and trajectory predictions of the surrounding vehicle in which future uncertainty has been taken into consideration and performing longitudinal control for collision avoidance.
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公开(公告)号：US11858535B2
公开(公告)日：2024-01-02
申请号：US17121829
申请日：2020-12-15
Inventor： Dongsuk Kum , Sanmin Kim
CPC classification number: B60W60/0027 , G05B13/027 , G06N3/044 , G06N3/045 , G06T7/20 , B60W2554/4044 , G05D1/0088 , G06T2207/20084 , G06T2207/30236 , G06T2207/30241 , G06T2207/30252
Abstract: An electronic device and an operating method thereof may be configured to detect input data having a first time interval, detect first prediction data having a second time interval based on the input data using a preset recursive network, and detect second prediction data having a third time interval based on the input data and the first prediction data using the recursive network. The recursive network may include an encoder configured to detect each of a plurality of feature vectors based on at least one of the input data or the first prediction data, an attention module configured to calculate each of pieces of importance of the feature vectors by calculating the importance of each feature vector, and a decoder configured to output at least one of the first prediction data or the second prediction data using the feature vectors based on the pieces of importance.
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