DETECTING SAFETY-RELEVANT ROAD TRAFFIC CONFLICTS

    公开(公告)号:US20240355199A1

    公开(公告)日:2024-10-24

    申请号:US18642336

    申请日:2024-04-22

    Applicant: Waymo LLC

    CPC classification number: G08G1/0133 G08G1/0112 G08G1/166

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for automatically designating traffic scenarios as safety-relevant traffic conflicts between agents in a driving environment. One of the methods includes receiving data representing a traffic scenario involving two agents; computing a safety-relevant metric for a first plurality of time points of the traffic scenario; computing a surprise metric for a second plurality of time points of the traffic scenario; determining that the surprise metric satisfies a surprise threshold within a threshold time window of the safety-relevant metric satisfying a safety-relevant threshold; and in response, designating the traffic scenario as a safety-relevant traffic conflict.

    COMPUTING AGENT RESPONSE TIMES IN TRAFFIC SCENARIOS

    公开(公告)号:US20240051582A1

    公开(公告)日:2024-02-15

    申请号:US18233696

    申请日:2023-08-14

    Applicant: Waymo LLC

    CPC classification number: B60W60/0027 B60W40/04 B60W2554/4046

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting agent response times. One of the methods includes continually updating, at each time step of a plurality of time steps, an accumulated measure of surprise for the agent due to the movements of another entity in the traffic environment. A distribution of previously predicted trajectories is obtained at a previous time step for the other entity in the environment. A measure of surprise is computed from the perspective of the agent. An accumulated measure of surprise is updated for the time step using the computed measure of surprise for the agent. If the accumulated measure of surprise crosses a threshold at a particular point in time, a predicted response time for the agent is generated based on the particular point in time that the accumulated measure of surprise crosses the threshold.

    PROBABILISTIC SIMULATION SAMPLING FROM AGENT DATA

    公开(公告)号:US20230011497A1

    公开(公告)日:2023-01-12

    申请号:US17370924

    申请日:2021-07-08

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining the likelihood that a particular event would occur during a navigation interaction using simulations generated by sampling from agent data. In one aspect, a method comprises: identifying an instance of a navigation interaction that includes an autonomous vehicle and agents navigating in an environment; generating multiple simulated interactions corresponding to the instance, comprising, for each simulated interaction: identifying one or more agents; for each identified agent and for each property that characterizes behavior of the identified agent, obtaining a probability distribution for the property; sampling a respective value from each of the probability distributions; and simulating the navigation interaction in accordance with the sampled values; and determining a likelihood that the particular event would occur during the navigation interaction based on whether the particular event occurred during each of the simulated interactions.

    Assessing surprise for autonomous vehicles

    公开(公告)号:US11447142B1

    公开(公告)日:2022-09-20

    申请号:US16414176

    申请日:2019-05-16

    Applicant: WAYMO LLC

    Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.

    Systems And Methods For Detecting And Dynamically Mitigating Driver Fatigue

    公开(公告)号:US20210001864A1

    公开(公告)日:2021-01-07

    申请号:US17024998

    申请日:2020-09-18

    Applicant: Waymo LLC

    Abstract: This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

    Systems and methods for detecting and dynamically mitigating driver fatigue

    公开(公告)号:US10807605B2

    公开(公告)日:2020-10-20

    申请号:US16226322

    申请日:2018-12-19

    Applicant: Waymo LLC

    Abstract: This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

    Assessing surprise for autonomous vehicles

    公开(公告)号:US12017686B1

    公开(公告)日:2024-06-25

    申请号:US17399418

    申请日:2021-08-11

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing a backward looking surprise metric for autonomously driven vehicles. One of the methods includes obtaining first data representing one or more previously predicted states of an agent along one or more predicted trajectories of the agent at a first time step. Second data representing one or more states of the agent at a subsequent time step is obtained. A surprise score is computed from a measure of a difference between the first data computed for the one or more predicted trajectories for the prior time step and the second data computed for the one or more predicted states for the subsequent time step.

    Assessing surprise for autonomous vehicles

    公开(公告)号:US11926332B1

    公开(公告)日:2024-03-12

    申请号:US17946973

    申请日:2022-09-16

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.

    Systems and methods for detecting and dynamically mitigating driver fatigue

    公开(公告)号:US11634145B2

    公开(公告)日:2023-04-25

    申请号:US17025048

    申请日:2020-09-18

    Applicant: Waymo LLC

    Abstract: This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

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