USING PREDICTION MODELS FOR SCENE DIFFICULTY IN VEHICLE ROUTING

    公开(公告)号:US20190186936A1

    公开(公告)日:2019-06-20

    申请号:US15843223

    申请日:2017-12-15

    Applicant: Waymo LLC

    Abstract: A route is selected for travel by an autonomous vehicle based on at least a level of difficulty of traversing the driving environment along that route. Vehicle signals, provided by one or more autonomous vehicles, indicating a difficulty associated with traveling a portion of a route are collected and used to predict a most favorable driving route for a given time. The signals may indicate a probability of disengaging from autonomous driving mode, a probability of being stuck for an unduly long time, traffic density, etc. A difficulty score may be computed for each road segment of a route, and then the scores of all of the road segments of the route are added together. The scores are based on number of previous disengagements, previous requests for remote assistance, unprotected left or right turns, whether parts of the driving area are occluded, etc. The difficulty score is used to compute a cost for a particular route, which may be compared to costs computed for other possible routes. Based on such information, a route may be selected.

    Model-based routing for autonomous vehicles

    公开(公告)号:US12111170B1

    公开(公告)日:2024-10-08

    申请号:US16436165

    申请日:2019-06-10

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure provide for the selection of a route for a vehicle having an autonomous driving mode. For instance, an initial location of the vehicle may be identified. This location may be used to determine a set of possible routes to a destination location. A cost for each route of the plurality is determined by inputting time of day information, map information, and details of that route into one or more models in order to determine whether the vehicle is likely to be stranded along that route and assessing the cost based at least in part on the determination of whether the vehicle is likely to be stranded along that route. One of the routes of the set of possible routes may be selected based on any determined costs. The vehicle may be controlled in the autonomous driving mode using the selected one.

    Using prediction models for scene difficulty in vehicle routing

    公开(公告)号:US10684134B2

    公开(公告)日:2020-06-16

    申请号:US15843223

    申请日:2017-12-15

    Applicant: Waymo LLC

    Abstract: A route is selected for travel by an autonomous vehicle based on at least a level of difficulty of traversing the driving environment along that route. Vehicle signals, provided by one or more autonomous vehicles, indicating a difficulty associated with traveling a portion of a route are collected and used to predict a most favorable driving route for a given time. The signals may indicate a probability of disengaging from autonomous driving mode, a probability of being stuck for an unduly long time, traffic density, etc. A difficulty score may be computed for each road segment of a route, and then the scores of all of the road segments of the route are added together. The scores are based on number of previous disengagements, previous requests for remote assistance, unprotected left or right turns, whether parts of the driving area are occluded, etc. The difficulty score is used to compute a cost for a particular route, which may be compared to costs computed for other possible routes. Based on such information, a route may be selected.

    USING PREDICTION MODELS FOR SCENE DIFFICULTY IN VEHICLE ROUTING

    公开(公告)号:US20200264003A1

    公开(公告)日:2020-08-20

    申请号:US16869682

    申请日:2020-05-08

    Applicant: Waymo LLC

    Abstract: A route is selected for travel by an autonomous vehicle based on at least a level of difficulty of traversing the driving environment along that route. Vehicle signals, provided by one or more autonomous vehicles, indicating a difficulty associated with traveling a portion of a route are collected and used to predict a most favorable driving route for a given time. The signals may indicate a probability of disengaging from autonomous driving mode, a probability of being stuck for an unduly long time, traffic density, etc. A difficulty score may be computed for each road segment of a route, and then the scores of all of the road segments of the route are added together. The scores are based on number of previous disengagements, previous requests for remote assistance, unprotected left or right turns, whether parts of the driving area are occluded, etc. The difficulty score is used to compute a cost for a particular route, which may be compared to costs computed for other possible routes. Based on such information, a route may be selected.

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