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公开(公告)号:US20240375684A1
公开(公告)日:2024-11-14
申请号:US18784780
申请日:2024-07-25
Applicant: Waymo LLC
Inventor: Jonathan Lee Pedersen , Yu Zheng , Eamonn Michael Doherty , Brian Clair Williammee , Kevin Joseph Malta , Chung Eun Kim , Xu Dong
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.
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公开(公告)号:US11947356B2
公开(公告)日:2024-04-02
申请号:US17229054
申请日:2021-04-13
Applicant: Waymo LLC
Inventor: Daniella Gutlansky , Mishika Vora , Tiffany Washburn , Yu Zheng , Sandra Lennie
CPC classification number: G05D1/0214 , G05D1/0055 , G05D1/0088 , G06V10/25 , G05D2201/0213
Abstract: Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.
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公开(公告)号:US20230099334A1
公开(公告)日:2023-03-30
申请号:US17491068
申请日:2021-09-30
Applicant: Waymo LLC
Inventor: Jonathan Lee Pedersen , Yu Zheng , Eamonn Michael Doherty , Brian Clair Williammee , Kevin Joseph Malta , Chung Eun Kim , Xu Dong
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.
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公开(公告)号:US12071162B2
公开(公告)日:2024-08-27
申请号:US17491068
申请日:2021-09-30
Applicant: Waymo LLC
Inventor: Jonathan Lee Pedersen , Yu Zheng , Eamonn Michael Doherty , Brian Clair Williammee , Kevin Joseph Malta , Chung Eun Kim , Xu Dong
CPC classification number: B60W60/0016 , B60W30/181 , B60W40/06 , G06N20/00 , B60W2552/45 , B60W2555/60
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.
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公开(公告)号:US20240192687A1
公开(公告)日:2024-06-13
申请号:US18588393
申请日:2024-02-27
Applicant: Waymo LLC
Inventor: Daniella Gutlansky , Mishika Vora , Tiffany Washburn , Yu Zheng , Sandra Lennie
CPC classification number: G05D1/0214 , G06V10/25
Abstract: Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.
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公开(公告)号:US20220326711A1
公开(公告)日:2022-10-13
申请号:US17229054
申请日:2021-04-13
Applicant: Waymo LLC
Inventor: Daniella Gutlansky , Mishika Vora , Tiffany Washburn , Yu Zheng , Sandra Lennie
Abstract: Aspects of the disclosure relate to evaluating pullovers for autonomous vehicles. In one instance, a set of potential pullover locations within a predetermined distance of a destination may be identified. Whether any of the potential pullover locations of the set include one or more of a plurality of predetermined types of regions of interest where a vehicle should not park for an extended period of time may be determined. A pullover location is identified based on the determination. The identified pullover location may be compared to a pullover location identified by autonomous vehicle control software in order to evaluate the pullover location identified by the autonomous vehicle control software.
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