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公开(公告)号：US20240403114A1
公开(公告)日：2024-12-05
申请号：US18799875
申请日：2024-08-09
Applicant: Waymo LLC
Inventor： Tacettin Dogacan Guney , Kai Ding , Olivier Gravel Aubin
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a task schedule for generating prediction data for different agents. In one aspect, a method comprises receiving data that characterizes an environment in a vicinity of a vehicle at a current time step, the environment comprising a plurality of agents; receiving data that identifies high-priority agents for which respective data characterizing the agents must be generated at the current time step; identifying available computing resources at the current time step; processing the data that characterizes the environment using a complexity scoring model to determine a respective complexity score for each of the high-priority agents; and determining a schedule for the current time step that allocates the generation of the data characterizing the high-priority agents across the available computing resources based on the complexity scores.
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公开(公告)号：US12073244B2
公开(公告)日：2024-08-27
申请号：US16935057
申请日：2020-07-21
Applicant: Waymo LLC
Inventor： Tacettin Dogacan Guney , Kai Ding , Olivier Gravel Aubin
CPC classification number: G06F9/4881 , B60K31/00 , B60K31/0008 , G06F9/3851 , G06F9/48 , G06F9/4806 , G06F9/4843 , G06F9/50 , G06F9/5005 , G06F9/5027 , G06F9/5038 , G06F9/5044 , G06F9/5094 , G06N5/00 , G06N20/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a task schedule for generating prediction data for different agents. In one aspect, a method comprises receiving data that characterizes an environment in a vicinity of a vehicle at a current time step, the environment comprising a plurality of agents; receiving data that identifies high-priority agents for which respective data characterizing the agents must be generated at the current time step; identifying available computing resources at the current time step; processing the data that characterizes the environment using a complexity scoring model to determine a respective complexity score for each of the high-priority agents; and determining a schedule for the current time step that allocates the generation of the data characterizing the high-priority agents across the available computing resources based on the complexity scores.
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公开(公告)号：US20240126296A1
公开(公告)日：2024-04-18
申请号：US18494997
申请日：2023-10-26
Applicant: Waymo LLC
Inventor： Vishu Goyal , Stéphane Ross , Kai Ding
Abstract: To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.
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公开(公告)号：US20240085917A1
公开(公告)日：2024-03-14
申请号：US18506500
申请日：2023-11-10
Applicant: WAYMO LLC
Inventor： Vishu Goyal , Kai Ding
CPC classification number: G05D1/0214 , B60W60/001 , G05B13/0265 , G05B13/048 , B60W2552/05 , B60W2552/15 , B60W2552/20 , B60W2552/30 , B60W2554/4029 , B60W2554/4041 , B60W2554/4042 , B60W2554/4043 , B60W2554/4045 , B60W2554/4046 , B60W2555/60 , G05D2201/0213
Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.
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公开(公告)号：US11873011B2
公开(公告)日：2024-01-16
申请号：US17083988
申请日：2020-10-29
Applicant: Waymo LLC
Inventor： Khaled Refaat , Kai Ding
CPC classification number: B60W60/0027 , B60W40/04 , G06N20/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate future trajectories for agents. One of the methods includes obtaining scene data characterizing a scene in an environment at a current time point; for each of a plurality of lane segments, processing a model input comprising (i) features of the lane segment and (ii) features of the target agent using a machine learning model that is configured to process the model input to generate a respective score for the lane segment that represents a likelihood that the lane segment will be a first lane segment traversed by the target agent after the current time point; selecting, as a set of seed lane segments, a proper subset of the plurality of lane segments based on the respective scores; and generating a plurality of candidate future trajectories for the target agent.
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Patent Agency Ranking
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：US11673550B2
公开(公告)日：2023-06-13
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
CPC classification number: B60W30/0956 , G05D1/0088 , G05D1/0214 , 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. 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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公开(公告)号：US11340622B2
公开(公告)日：2022-05-24
申请号：US16557938
申请日：2019-08-30
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 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：US20220135078A1
公开(公告)日：2022-05-05
申请号：US17083988
申请日：2020-10-29
Applicant: Waymo LLC
Inventor： Khaled Refaat , Kai Ding
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate future trajectories for agents. One of the methods includes obtaining scene data characterizing a scene in an environment at a current time point; for each of a plurality of lane segments, processing a model input comprising (i) features of the lane segment and (ii) features of the target agent using a machine learning model that is configured to process the model input to generate a respective score for the lane segment that represents a likelihood that the lane segment will be a first lane segment traversed by the target agent after the current time point; selecting, as a set of seed lane segments, a proper subset of the plurality of lane segments based on the respective scores; and generating a plurality of candidate future trajectories for the target agent.
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公开(公告)号：US20220073085A1
公开(公告)日：2022-03-10
申请号：US17013298
申请日：2020-09-04
Applicant: Waymo LLC
Inventor： Minfa Wang , Kai Ding , Haoyu Chen , Wei Chai , Maher Mneimneh
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing knowledge distillation for autonomous vehicles. One of the methods includes obtaining sensor data characterizing an environment, wherein the sensor data has been captured by one or more sensors on-board a vehicle in the environment; processing, for each of one or more surrounding agents in the environment, a network input generated from the sensor data using a neural network to generate an agent discomfort prediction that characterizes a level of discomfort of the agent; combining the one or more agent discomfort predictions to generate an aggregated discomfort score; and providing the aggregated discomfort score to a path planning system of the vehicle in order to generate a future path of the vehicle.
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