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公开(公告)号：US20230031375A1
公开(公告)日：2023-02-02
申请号：US17873261
申请日：2022-07-26
Applicant: Waymo LLC
Inventor： Maher Mneimneh , Anne Hobbs Dorsey , Qiaojing Yan
IPC: B60W60/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that determine yield behavior for an autonomous vehicle. An agent that is in a vicinity of an autonomous vehicle can be identified. An obtained crossing intent prediction characterizes a predicted likelihood that the agent intends to cross a roadway during a future time period. First features of the agent and of the autonomous vehicle are obtained. An input that includes the first features and the crossing intent prediction is processed using a machine learning model to generate an intent yielding score that represents a likelihood that the autonomous vehicle should perform a yielding behavior due to the intent of the agent to cross the roadway. From at least the intent yielding score, an intent yield behavior signal is determined and indicates whether the autonomous vehicle should perform the yielding behavior prior to reaching the first crossing region.
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公开(公告)号：US20230059370A1
公开(公告)日：2023-02-23
申请号：US17886747
申请日：2022-08-12
Applicant: Waymo LLC
Inventor： Junhua Mao , Xinwei Shi , Anne Hobbs Dorsey , Rui Yan , Chi Yeung Jonathan Ng
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predicting gaze and awareness using a neural network model. One of the methods includes obtaining sensor data (i) that is captured by one or more sensors of an autonomous vehicle and (ii) that characterizes an agent that is in a vicinity of the autonomous vehicle in an environment at a current time point. The sensor data is processed using a gaze prediction neural network to generate a gaze prediction that predicts a gaze of the agent at the current time point. The gaze prediction neural network includes an embedding subnetwork that is configured to process the sensor data to generate an embedding characterizing the agent, and a gaze subnetwork that is configured to process the embedding to generate the gaze prediction.
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公开(公告)号：US20230068703A1
公开(公告)日：2023-03-02
申请号：US17511053
申请日：2021-10-26
Applicant: WAYMO LLC
Inventor： Tirthkumar Nilaykumar Pandya , Eric Deng , Chinmayee Shah , Jared Stephen Russell , Geoffrey Lalonde , Anne Hobbs Dorsey
IPC: B60W60/00
Abstract: A system for estimating a spacing profile for a road agent includes a first module and a second module. The first module includes instructions that cause one or more processors to receive data related to characteristics of the road agent and road agent behavior detected in an environment of an autonomous vehicle, initiate an analysis of the road agent behavior, and estimate the spacing profile of the road agent as part of the analysis. The spacing profile includes a lateral gap preference and predicted behaviors of the road agent related to changes in lateral gap. The second module includes instructions that cause the one or more processors to determine one or more components of autonomous vehicle maneuver based on the estimated spacing profile and send control instructions for performing the autonomous vehicle maneuver.
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公开(公告)号：US12084088B2
公开(公告)日：2024-09-10
申请号：US17873261
申请日：2022-07-26
Applicant: Waymo LLC
Inventor： Maher Mneimneh , Anne Hobbs Dorsey , Qiaojing Yan
CPC classification number: B60W60/0027 , B60W2520/06 , B60W2520/10 , B60W2552/05 , B60W2552/45 , B60W2554/4029 , B60W2554/4042 , B60W2554/4044 , B60W2554/4045 , B60W2554/802
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that determine yield behavior for an autonomous vehicle. An agent that is in a vicinity of an autonomous vehicle can be identified. An obtained crossing intent prediction characterizes a predicted likelihood that the agent intends to cross a roadway during a future time period. First features of the agent and of the autonomous vehicle are obtained. An input that includes the first features and the crossing intent prediction is processed using a machine learning model to generate an intent yielding score that represents a likelihood that the autonomous vehicle should perform a yielding behavior due to the intent of the agent to cross the roadway. From at least the intent yielding score, an intent yield behavior signal is determined and indicates whether the autonomous vehicle should perform the yielding behavior prior to reaching the first crossing region.
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