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公开(公告)号：US11586213B2
公开(公告)日：2023-02-21
申请号：US17229384
申请日：2021-04-13
Applicant: Waymo LLC
Inventor： Khaled Refaat , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a representation of a trajectory of a target agent in an environment. In one aspect, the representation of the trajectory of the target agent in the environment is a concatenation of a plurality of channels, where each channel is represented as a two-dimensional array of data values. Each position in each channel corresponds to a respective spatial position in the environment, and corresponding positions in different channels correspond to the same spatial position in the environment. The channels include a time channel and a respective motion channel corresponding to each motion parameter in a predetermined set of motion parameters.
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公开(公告)号：US20210200229A1
公开(公告)日：2021-07-01
申请号：US16727724
申请日：2019-12-26
Applicant: Waymo LLC
Inventor： Khaled Refaat , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating training data for training a machine learning model to perform trajectory prediction. One of the methods includes: obtaining a training input, the training input including (i) data characterizing an agent in an environment as of a first time and (ii) data characterizing a candidate trajectory of the agent in the environment for a first time period that is after the first time. A long-term label for the candidate trajectory that indicates whether the agent actually followed the candidate trajectory for the first time period is determined. A short-term label for the candidate trajectory that indicates whether the agent intended to follow the candidate trajectory is determined. A ground-truth probability for the candidate trajectory is determined. The training input is associated with the ground-truth probability for the candidate trajectory in the training data.
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公开(公告)号：US11048253B2
公开(公告)日：2021-06-29
申请号：US16198130
申请日：2018-11-21
Applicant: Waymo LLC
Inventor： Kai Ding , Khaled Refaat , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle and, for only those agents which are high priority agents, generating data characterizing the agents using a first prediction model. In a first aspect, a system identifies multiple agents in an environment in a vicinity of a vehicle. The system generates a respective importance score for each of the agents by processing a feature representation of each agent using an importance scoring model. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The system identifies, as high-priority agents, a proper subset of the plurality of agents with the highest importance scores.
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公开(公告)号：US10739777B2
公开(公告)日：2020-08-11
申请号：US16196769
申请日：2018-11-20
Applicant: Waymo LLC
Inventor： Khaled Refaat , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a representation of a trajectory of a target agent in an environment. In one aspect, the representation of the trajectory of the target agent in the environment is a concatenation of a plurality of channels, where each channel is represented as a two-dimensional array of data values. Each position in each channel corresponds to a respective spatial position in the environment, and corresponding positions in different channels correspond to the same spatial position in the environment. The channels include a time channel and a respective motion channel corresponding to each motion parameter in a predetermined set of motion parameters.
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公开(公告)号：US20200159215A1
公开(公告)日：2020-05-21
申请号：US16198130
申请日：2018-11-21
Applicant: Waymo LLC
Inventor： Kai Ding , Khaled Refaat , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle and, for only those agents which are high priority agents, generating data characterizing the agents using a first prediction model. In a first aspect, a system identifies multiple agents in an environment in a vicinity of a vehicle. The system generates a respective importance score for each of the agents by processing a feature representation of each agent using an importance scoring model. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The system identifies, as high-priority agents, a proper subset of the plurality of agents with the highest importance scores.
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Patent Agency Ranking
公开(公告)号：US11829149B1
公开(公告)日：2023-11-28
申请号：US17750196
申请日：2022-05-20
Applicant: Waymo LLC
Inventor： Khaled Refaat , Kai Ding , Stephane Ross
CPC classification number: G05D1/0219 , G01C21/3446 , G01C21/3492 , G05D1/0221
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining respective importance scores for a plurality of agents in a vicinity of an autonomous vehicle navigating through an environment. The respective importance scores characterize a relative impact of each agent on planned trajectories generated by a planning subsystem of the autonomous vehicle. In one aspect, a method comprises providing different states of an environment as input to the planning subsystem and obtaining as output from the planning subsystem corresponding planned trajectories. Importance scores for the one or more agents that are in one state but not in the other are determined based on a measure of difference between the planned trajectories.
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公开(公告)号：US20230288929A1
公开(公告)日：2023-09-14
申请号：US18197561
申请日：2023-05-15
Applicant: Waymo LLC
Inventor： Kai Ding , Minfa Wang , Haoyu Chen , Khaled Refaat , Stephane Ross , Wei Chai
CPC classification number: G05D1/0088 , G05D1/0214 , G06N3/08 , G05D2201/0213
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle. The high-priority agents can be identified based on a set of mutual importance scores in which each mutual importance score indicates an estimated mutual relevance between the vehicle and a different agent from a set of agents on planning decisions of the other. The mutual importance scores can be calculated based on importance scores assessed from the perspectives of both the vehicle and the agents.
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公开(公告)号：US11687077B2
公开(公告)日：2023-06-27
申请号：US16987980
申请日：2020-08-07
Applicant: Waymo LLC
Inventor： Kai Ding , Minfa Wang , Haoyu Chen , Khaled Refaat , Stephane Ross , Wei Chai
CPC classification number: G05D1/0088 , G05D1/0214 , G06N3/08 , G05D2201/0213
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle. The high-priority agents can be identified based on a set of mutual importance scores in which each mutual importance score indicates an estimated mutual relevance between the vehicle and a different agent from a set of agents on planning decisions of the other. The mutual importance scores can be calculated based on importance scores assessed from the perspectives of both the vehicle and the agents.
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公开(公告)号：US11586931B2
公开(公告)日：2023-02-21
申请号：US16671019
申请日：2019-10-31
Applicant: Waymo LLC
Inventor： Khaled Refaat , Kai Ding , Stephane Ross
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network having a plurality of sub neural networks to assign respective confidence scores to one or more candidate future trajectories for an agent. Each confidence score indicates a predicted likelihood that the agent will move along the corresponding candidate future trajectory in the future. In one aspect, a method includes using the first sub neural network to generate a training intermediate representation; using the second sub neural network to generate respective training confidence scores; using a trajectory generation neural network to generate a training trajectory generation output; computing a first loss and a second loss; and determining an update to the current values of the parameters of the first and second sub neural networks.
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公开(公告)号：US20210269023A1
公开(公告)日：2021-09-02
申请号：US17320727
申请日：2021-05-14
Applicant: Waymo LLC
Inventor： Kai Ding , Khaled Refaat , Stephane Ross
IPC: B60W30/095 , G05D1/02 , G05D1/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle. In one aspect, a method comprises processing an input that characterizes a trajectory of the vehicle in an environment using an importance scoring model to generate an output that defines a respective importance score for each of a plurality of agents in the environment in the vicinity of the vehicle. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The high-priority agents are identified as a proper subset of the plurality of agents with the highest importance scores.
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