INTERVENTION BEHAVIOR PREDICTION WITH CONTINUOUS CONFOUNDERS

    公开(公告)号:US20250065921A1

    公开(公告)日:2025-02-27

    申请号:US18237384

    申请日:2023-08-23

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for intervention behavior prediction. One of the methods includes receiving data characterizing a scene that includes a first agent and a second agent in an environment and receiving intervention data specifying a planned intervention to be performed by the second agent. A conditional behavior prediction output that assigns, to each of a plurality of possible future behaviors, (i) a respective conditional likelihood that the first agent performs the possible future behavior given that the second agent performs the planned intervention and (ii) a predicted value of a confounder variable for the possible future behavior is generated using a conditional behavior prediction model. An intervention behavior prediction for the first agent is generated by, for each possible future behavior, generating a corrected likelihood for the possible future behavior based on the respective conditional likelihood for the possible future behavior and the predicted value of the confounder variable for the possible future behavior.

    Verifying predicted trajectories using a grid-based approach

    公开(公告)号:US12204333B2

    公开(公告)日:2025-01-21

    申请号:US17191491

    申请日:2021-03-03

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure provide for controlling a vehicle in an autonomous driving mode. For instance, sensor data for an object as well as a plurality of predicted trajectories may be received. Each predicted trajectory may represent a plurality of possible future locations for the object. A grid including a plurality of cells, each being associated with a geographic area, may be generated. Probabilities that the object will enter the geographic area associated with each of the plurality of cells over a period of time into the future may be determined based on the sensor data in order to generate a heat map. One or more of the plurality of predicted trajectories may be compared to the heat map. The vehicle may be controlled in the autonomous driving mode based on the comparison.

    Trajectory representation in behavior prediction systems

    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

    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.

    Predictability-Based Autonomous Vehicle Trajectory Assessments

    公开(公告)号:US20220169278A1

    公开(公告)日:2022-06-02

    申请号:US17108626

    申请日:2020-12-01

    Applicant: Waymo LLC

    Abstract: Data representing a set of predicted trajectories and a planned trajectory for an autonomous vehicle is obtained. A predictability score for the planned trajectory can be determined based on a comparison of the planned trajectory to the set of predicted trajectories for the autonomous vehicle. The predictability score indicates a level of predictability of the planned trajectory. A determination can be made, based at least on the predictability score, whether to initiate travel with the autonomous vehicle along the planned trajectory. In response to determining to initiate travel with the autonomous vehicle along the planned trajectory, a control system can be directed to maneuver the autonomous vehicle along the planned trajectory.

    ACCELERATED DEEP REINFORCEMENT LEARNING OF AGENT CONTROL POLICIES

    公开(公告)号:US20220036186A1

    公开(公告)日:2022-02-03

    申请号:US17390800

    申请日:2021-07-30

    Applicant: Waymo LLC

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a mixture of a plurality of actor-critic policies that is used to control an agent interacting with an environment to perform a task. Each actor-critic policy includes an actor policy and a critic policy. The training includes, for each of one or more transitions, determining a target Q value for the transition from (i) the reward in the transition, and (ii) an imagined return estimate generated by performing one or more iterations of a prediction process to generate one or more predicted future transitions.

    Verifying Predicted Trajectories Using A Grid-Based Approach

    公开(公告)号:US20210341927A1

    公开(公告)日:2021-11-04

    申请号:US17191491

    申请日:2021-03-03

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure provide for controlling a vehicle in an autonomous driving mode. For instance, sensor data for an object as well as a plurality of predicted trajectories may be received. Each predicted trajectory may represent a plurality of possible future locations for the object. A grid including a plurality of cells, each being associated with a geographic area, may be generated. Probabilities that the object will enter the geographic area associated with each of the plurality of cells over a period of time into the future may be determined based on the sensor data in order to generate a heat map. One or more of the plurality of predicted trajectories may be compared to the heat map. The vehicle may be controlled in the autonomous driving mode based on the comparison.

    GENERATING TRAJECTORY LABELS FROM SHORT-TERM INTENTION AND LONG-TERM RESULT

    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

    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.

    Agent prioritization for autonomous vehicles

    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

    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.

    Verifying predicted trajectories using a grid-based approach

    公开(公告)号:US10969789B2

    公开(公告)日:2021-04-06

    申请号:US16185787

    申请日:2018-11-09

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure provide for controlling a vehicle in an autonomous driving mode. For instance, sensor data for an object as well as a plurality of predicted trajectories may be received. Each predicted trajectory may represent a plurality of possible future locations for the object. A grid including a plurality of cells, each being associated with a geographic area, may be generated. Probabilities that the object will enter the geographic area associated with each of the plurality of cells over a period of time into the future may be determined based on the sensor data in order to generate a heat map. One or more of the plurality of predicted trajectories may be compared to the heat map. The vehicle may be controlled in the autonomous driving mode based on the comparison.

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