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公开(公告)号:US11845464B2
公开(公告)日:2023-12-19
申请号:US17162054
申请日:2021-01-29
Applicant: Honda Motor Co., Ltd.
Inventor: Nakul Agarwal , Yi-Ting Chen
Abstract: Driver behavior risk assessment and pedestrian awareness may include an receiving an input stream of images of an environment including one or more objects within the environment, estimating an intention of an ego vehicle based on the input stream of images and a temporal recurrent network (TRN), generating a scene representation based on the input stream of images and a graph neural network (GNN), generating a prediction of a situation based on the scene representation and the intention of the ego vehicle, and generating an influenced or non-influenced action determination based on the prediction of the situation and the scene representation.
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公开(公告)号:US11679500B2
公开(公告)日:2023-06-20
申请号:US17165790
申请日:2021-02-02
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Yuchen Xiao , Haiming Gang
CPC classification number: B25J9/1661 , B25J9/163 , B25J9/1612 , B25J9/1653 , B25J9/1666 , B25J9/1697 , B25J13/088
Abstract: Systems and techniques for target object retrieval may include or utilize an image capture device, and a task planner. The image capture device may receive an image of an environment including identified objects. The task planner may determine potential actions, calculate a probability of success of achieving a desired goal for each of the potential actions based on an action prediction model, the corresponding potential action, a current state of the environment, any previously taken action, and the desired goal, select a potential action associated with the highest calculated probability of success, and simulate a subsequent state based on the selected potential action and a dynamic prediction model. The potential actions may be associated with an identified object of the identified objects and an operation to be performed on the identified object.
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公开(公告)号:US20220184806A1
公开(公告)日:2022-06-16
申请号:US17165790
申请日:2021-02-02
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Yuchen Xiao , Haiming Gang
Abstract: Systems and techniques for target object retrieval may include or utilize an image capture device, and a task planner. The image capture device may receive an image of an environment including identified objects. The task planner may determine potential actions, calculate a probability of success of achieving a desired goal for each of the potential actions based on an action prediction model, the corresponding potential action, a current state of the environment, any previously taken action, and the desired goal, select a potential action associated with the highest calculated probability of success, and simulate a subsequent state based on the selected potential action and a dynamic prediction model. The potential actions may be associated with an identified object of the identified objects and an operation to be performed on the identified object.
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公开(公告)号:US20220144260A1
公开(公告)日:2022-05-12
申请号:US17161555
申请日:2021-01-28
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Zihao Xiao
IPC: B60W30/095 , G06N3/04 , G06T7/38 , B60W50/10 , B60W50/14
Abstract: A system and method for completing risk object identification that include receiving image data associated with a monocular image of a surrounding environment of an ego vehicle and analyzing the image data and completing semantic waypoint labeling of at least one region of the surrounding environment of the ego vehicle. The system and method also include completing counterfactual scenario augmentation with respect to the at least one region. The system and method further include determining at least one driver intention and at least one driver response associated with the at least one region.
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公开(公告)号:US11260872B2
公开(公告)日:2022-03-01
申请号:US16159194
申请日:2018-10-12
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Mingze Xu , Mingfei Gao
Abstract: A system and method for utilizing a temporal recurrent network for online action detection that include receiving image data that is based on at least one image captured by a vehicle camera system. The system and method also include analyzing the image data to determine a plurality of image frames and outputting at least one goal-oriented action as determined during a current image frame. The system and method further include controlling a vehicle to be autonomously driven based on a naturalistic driving behavior data set that includes the at least one goal-oriented action.
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公开(公告)号:US20210080971A1
公开(公告)日:2021-03-18
申请号:US16728581
申请日:2019-12-27
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Chengxi Li , Yue Meng
IPC: G05D1/02 , G06F16/901 , G07C5/06 , G05D1/00 , G06K9/00
Abstract: Systems and methods for driver behavior recognition is provided. In one embodiment a computer implemented method includes receiving image data associated with a general objects. The method also includes identifying a reactive object and an inert object from the general objects based on the image data. An ego reactive graph is generated for the reactive object based on a reactive feature of the reactive object and a reactive position vector. An ego inert graph is generated for the inert object based on an inert feature of the inert object and an inert distance. The method further includes performing interaction modeling based on the ego reactive graphs and the ego inert graphs to generate updated features. The method also includes performing temporal modeling on the updated features. The method further includes determining an egocentric representation of a tactical driver behavior based at least in part on the updated features.
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公开(公告)号:US20210027066A1
公开(公告)日:2021-01-28
申请号:US16804949
申请日:2020-02-28
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Behzad Dariush , Nakul Agarwal , Ming-Hsuan Yang
Abstract: A system and method for providing unsupervised domain adaption for spatio-temporal action localization that includes receiving video data associated with a surrounding environment of a vehicle. The system and method also include completing an action localization model to model a temporal context of actions occurring within the surrounding environment of the vehicle based on the video data and completing an action adaption model to localize individuals and their actions and to classify the actions based on the video data. The system and method further include combining losses from the action localization model and the action adaption model to complete spatio-temporal action localization of individuals and actions that occur within the surrounding environment of the vehicle.
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公开(公告)号:US10650531B2
公开(公告)日:2020-05-12
申请号:US15923592
申请日:2018-03-16
Applicant: HONDA MOTOR CO., LTD.
Inventor: Athmanarayanan Lakshmi Narayanan , Yi-Ting Chen
Abstract: A system, computer-readable medium, and method for improving semantic mapping and traffic participant detection for an autonomous vehicle are provided. The methods and systems may include obtain a two-dimensional image, obtain a three-dimensional point cloud comprising a plurality of points, perform semantic segmentation on the image to map objects with a discrete pixel color, and overlaying the semantic segmentation on the image to generate a updated image, generate superpixel clusters from the semantic segmentation to group like pixels together, project the point cloud onto the updated image comprising the superpixel clusters, and remove points determined to be noise/errors from the point cloud based on determining noisy points within each superpixel cluster.
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公开(公告)号:US10482334B1
公开(公告)日:2019-11-19
申请号:US16132950
申请日:2018-09-17
Applicant: Honda Motor Co., Ltd.
Inventor: Yi-Ting Chen , Athmanarayanan Lakshmi Narayanan
Abstract: Driver behavior recognition may be provided using a processor and a memory. The memory may receive an image sequence and a corresponding vehicle data signal sequence. The processor may generate or process features for each frame of the respective sequences. The processor may generate a first feature vector based on the image sequence and a first neural network. The processor may generate a second feature vector based on a fully connected layer and the vehicle data signal sequence. The processor may generate a fusion feature by performing data fusion based on the first feature vector and the second feature vector. The processor may process the fusion feature using a long short term memory layer and store the processed fusion feature as a recognized driver behavior associated with each corresponding frame. The processor may, according to other aspects, generate the fusion feature based on a third feature vector.
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公开(公告)号:US20180336697A1
公开(公告)日:2018-11-22
申请号:US15601638
申请日:2017-05-22
Applicant: HONDA MOTOR CO., LTD.
Inventor: Yan LU , Jiawei Huang , Yi-Ting Chen , Bernd Heisele
CPC classification number: G06T7/73 , G01S17/023 , G01S17/89 , G06T7/13 , G06T2207/30244 , G06T2207/30252
Abstract: The present disclosure relates to methods and systems for monocular localization in urban environments. The method may generate an image from a camera at a pose. The method may receive a pre-generated map, and determine features from the generated image based on edge detection. The method may predict a pose of the camera based on at least the pre-generated map, and determine features from the predicted camera pose. Further, the method may determine a Chamfer distance based upon the determined features from the image and the predicted camera pose, optimize the determined Chamfer distance based upon odometry information and epipolar geometry. Upon optimization, the method may determine an estimated camera pose.
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