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公开(公告)号：US11774259B2
公开(公告)日：2023-10-03
申请号：US17469253
申请日：2021-09-08
Applicant: WAYMO LLC
Inventor： Vishu Goyal , Shubham Gupta
CPC classification number: G01C21/3658 , G01C21/3453 , G05D1/0088 , G05D1/0212 , G06N20/00 , G06V20/588
Abstract: Aspects of the disclosure provide a method of identifying off-road entry lane waypoints. For instance, a polygon representative of a driveway or parking area may be identified from map information. A nearest lane may be identified based on the polygon. A plurality of lane waypoints may be identified. Each of the lane waypoints may correspond to a location within at least one lane. The polygon and the plurality of lane waypoints may be input into a model. A lane waypoint of the plurality of lane waypoints may be selected as an off-road entry lane waypoint. The off-road entry lane waypoint may be associated with the nearest lane. The association may be provided to an autonomous vehicle in order to allow the autonomous vehicle to use the association to control the autonomous vehicle in an autonomous driving mode.
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公开(公告)号：US11753043B2
公开(公告)日：2023-09-12
申请号：US17325952
申请日：2021-05-20
Applicant: Waymo LLC
Inventor： Vishu Goyal , Shubham Gupta , Kai Ding
CPC classification number: B60W60/0027 , G05B13/0265 , G05D1/0214 , B60W2420/40 , B60W2552/53 , B60W2554/4041 , B60W2554/4044 , B60W2554/4045 , B60W2556/10 , G05D2201/0213
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that generates path prediction data for agents in the vicinity of an autonomous vehicle using machine learning models. One method includes identifying an agent in a vicinity of an autonomous vehicle navigating an environment and determining that the agent is within a vicinity of a crossing zone, which can be marked or unmarked. In response to determining that the agent is within a vicinity of a crossing zone: (i) features of the agent and of the crossing zone can be obtained; (ii) a first input that includes the features can be processed using a first machine learning model that is configured to generate a first crossing prediction that characterizes future crossing behavior of the agent, and (iii) a predicted path for the agent for crossing the roadway can be determined from at least the first crossing prediction.
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公开(公告)号：US20230074387A1
公开(公告)日：2023-03-09
申请号：US17469253
申请日：2021-09-08
Applicant: WAYMO LLC
Inventor： Vishu Goyal , Shubham Gupta
Abstract: Aspects of the disclosure provide a method of identifying off-road entry lane waypoints. For instance, a polygon representative of a driveway or parking area may be identified from map information. A nearest lane may be identified based on the polygon. A plurality of lane waypoints may be identified. Each of the lane waypoints may correspond to a location within at least one lane. The polygon and the plurality of lane waypoints may be input into a model. A lane waypoint of the plurality of lane waypoints may be selected as an off-road entry lane waypoint. The off-road entry lane waypoint may be associated with the nearest lane. The association may be provided to an autonomous vehicle in order to allow the autonomous vehicle to use the association to control the autonomous vehicle in an autonomous driving mode.
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公开(公告)号：US20220371624A1
公开(公告)日：2022-11-24
申请号：US17325952
申请日：2021-05-20
Applicant: Waymo LLC
Inventor： Vishu Goyal , Shubham Gupta , Kai Ding
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that generates path prediction data for agents in the vicinity of an autonomous vehicle using one or more machine learning models. One of the methods includes identifying an agent in a vicinity of an autonomous vehicle navigating through an environment and determining that the agent is within a vicinity of a crossing zone across a roadway. The crossing zone can be a marked crossing zone or an unmarked crossing zone. For example, the crossing zone can be an unmarked crossing zone that has been identified based on previous observations of agents crossing the roadway. In response to determining that the agent is within a vicinity of a crossing zone: (i) features of the agent and of the crossing zone can be obtained; (ii) a first input that includes the features can be processed using a first machine learning model that is configured to generate a first crossing prediction that characterizes future crossing behavior of the agent, and (iii) a predicted path for the agent for crossing the roadway can be determined from at least the first crossing prediction.
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