PARALLELIZED TREE-BASED DECISION SCHEME FOR AUTONOMOUS VEHICLE

    公开(公告)号:US20210089030A1

    公开(公告)日:2021-03-25

    申请号:US16582513

    申请日:2019-09-25

    Abstract: A system or method implemented by an autonomous vehicle involves determining a path plan to reach a destination from an origin. The path plan includes two or more path steps indicating tasks to be completed to reach the destination. The method includes, during traversal of the path plan by the autonomous vehicle, evaluating one or more of the two or more path steps of a planning horizon to determine a behavior plan for the planning horizon. The planning horizon is based on a current position of the autonomous vehicle, the behavior plan includes a speed and a trajectory, and the evaluating includes performing a cost analysis using a parallelized tree-based decision scheme at each of two or more simulation intervals within the planning horizon. The evaluating and the determining the behavior plan is repeated at two or more positions of the autonomous vehicle from the origin to the destination.

    AUTOMATED DRIVING SYSTEMS AND CONTROL LOGIC USING MANEUVER CRITICALITY FOR VEHICLE ROUTING AND MODE ADAPTATION

    公开(公告)号:US20200290619A1

    公开(公告)日:2020-09-17

    申请号:US16352918

    申请日:2019-03-14

    Abstract: Presented are automated driving systems and control logic for intelligent vehicle operation in transient driving conditions, methods for constructing/operating such systems, and vehicles equipped with such systems. A method for controlling an automated driving operation includes a vehicle controller receiving path plan data with location, destination, and predicted path data for a vehicle. From the received path plan data, the controller predicts an upcoming maneuver for driving the vehicle between start and goal lane segments. The vehicle controller determines a predicted route with lane segments connecting the start and goal lane segments, and segment maneuvers for moving the vehicle between the start, goal, and route lane segments. A cost value is calculated for each segment maneuver; the controller determines if a cost values exceeds a corresponding criticality value. If so, the controller transmits commands a resident vehicle subsystem to execute a control operation associated with taking the first predicted route.

    Parallelized tree-based decision scheme for autonomous vehicle

    公开(公告)号:US11460843B2

    公开(公告)日:2022-10-04

    申请号:US16582513

    申请日:2019-09-25

    Abstract: A system or method implemented by an autonomous vehicle involves determining a path plan to reach a destination from an origin. The path plan includes two or more path steps indicating tasks to be completed to reach the destination. The method includes, during traversal of the path plan by the autonomous vehicle, evaluating one or more of the two or more path steps of a planning horizon to determine a behavior plan for the planning horizon. The planning horizon is based on a current position of the autonomous vehicle, the behavior plan includes a speed and a trajectory, and the evaluating includes performing a cost analysis using a parallelized tree-based decision scheme at each of two or more simulation intervals within the planning horizon. The evaluating and the determining the behavior plan is repeated at two or more positions of the autonomous vehicle from the origin to the destination.

    Automated driving systems and control logic using maneuver criticality for vehicle routing and mode adaptation

    公开(公告)号:US11052914B2

    公开(公告)日:2021-07-06

    申请号:US16352918

    申请日:2019-03-14

    Abstract: Automated driving systems, control logic, and methods execute maneuver criticality analysis to provide intelligent vehicle operation in transient driving conditions. A method for controlling an automated driving operation includes a vehicle controller receiving path plan data with location, destination, and predicted path data for a vehicle. From the received path plan data, the controller predicts an upcoming maneuver for driving the vehicle between start and goal lane segments. The vehicle controller determines a predicted route with lane segments connecting the start and goal lane segments, and segment maneuvers for moving the vehicle between the start, goal, and route lane segments. A cost value is calculated for each segment maneuver; the controller determines if a cost values exceeds a corresponding criticality value. If so, the controller commands a resident vehicle subsystem to execute a control operation associated with taking the predicted route.

    Automated data collection for continued refinement in the detection of objects-of-interest

    公开(公告)号:US10817728B2

    公开(公告)日:2020-10-27

    申请号:US16255056

    申请日:2019-01-23

    Abstract: A method of updating an identification algorithm of a vehicle includes sensing an image and drawing boundary boxes in the image. The algorithm attempts to identify an object-of-interest within each respective boundary box. The algorithm also attempts to identify a component of the object-of-interest within each respective boundary box, and if component is identified, calculates an excluded amount of a component boundary that is outside an object boundary. When the excluded amount is greater than a coverage threshold, the algorithm communicates the image to a processing center, which may identify a previously un-identified the object-of-interest in the image. The processing center may add the image to a training set of images to define a revised training set of images, and retrain the identification algorithm using the revised training set of images. The updated identification algorithm may then be uploaded onto the vehicle.

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