GENERATING ENVIRONMENTAL PARAMETERS BASED ON SENSOR DATA USING MACHINE LEARNING

    公开(公告)号:US20200209858A1

    公开(公告)日:2020-07-02

    申请号:US16294274

    申请日:2019-03-06

    Abstract: To generate a machine learning model for controlling autonomous vehicles, training sensor data is obtained from sensors associated with one or more vehicles, the sensor data indicative of physical conditions of an environment in which the one or more vehicles operate, and a machine learning (ML) model is trained using the training sensor data. The ML model generates parameters of the environment in response to input sensor data. A controller in an autonomous vehicle receives sensor data from one or more sensors operating in the autonomous vehicle, applies the received sensor data to the ML model to obtain parameters of an environment in which the autonomous vehicle operates, provides the generated parameters to a motion planner component to generate decisions for controlling the autonomous vehicle, and causes the autonomous vehicle to maneuver in accordance with the generated decisions.

    Autonomous vehicle technology for facilitating safe stopping according to separate paths

    公开(公告)号:US10481605B1

    公开(公告)日:2019-11-19

    申请号:US16138427

    申请日:2018-09-21

    Abstract: Various software techniques for managing operation of autonomous vehicles based on sensor data are disclosed herein. A computing system may generate, based on a set of signals descriptive of a current state of an environment in which the autonomous vehicle is operating, a normal path plan separate from a safe path plan, or a hybrid path plan including a normal path plan and a safe path plan. In generating the safe path plan, the computing system may generate and concatenate a set of motion primitives. When a fault condition occurs, the computing device may transition from executing the normal path plan to executing the safe path plan to safely stop the autonomous vehicle.

    CONTROLLING AN AUTONOMOUS VEHICLE USING MODEL PREDICTIVE CONTROL

    公开(公告)号:US20190113920A1

    公开(公告)日:2019-04-18

    申请号:US16149225

    申请日:2018-10-02

    Abstract: A computer-readable medium stores instructions executable by one or more processors to implement a self-driving control architecture for controlling an autonomous vehicle. A perception component receives sensor data and generates signals descriptive of a current state of the environment. Based on those signals, a prediction component generates signals descriptive of one or more predicted future environment states. A motion planner generates decisions for maneuvering the vehicle toward a destination, at least by using the signals descriptive of the current and future environment states to set values of one or more independent variables in an objective equation. The objective equation includes terms corresponding to different driving objectives over a finite time horizon. Values of one or more dependent variables in the objective equation are determined by solving the equation subject to a set of constraints, and values of the dependent variables are used to generate decisions for maneuvering the vehicle.

    Velocity determination with a scanned lidar system

    公开(公告)号:US12140671B2

    公开(公告)日:2024-11-12

    申请号:US17065011

    申请日:2020-10-07

    Abstract: A scanning imaging sensor is configured to sense an environment through which a vehicle is moving. A method for determining one or velocities associated with objects in the environment includes generating features from the first set of scan lines and the second set of scan lines, the two sets corresponding to two instances in time. The method further includes generating a collection of candidate velocities based on feature locations and time differences, the features selected pairwise with one from the first set and another from the second set. Furthermore, the method includes analyzing the distribution of candidate velocities, for example, by identifying one or more modes from the collection of the candidate velocities.

    AUTONOMOUS VEHICLE TECHNOLOGY FOR FACILITATING SAFE STOPPING ACCORDING TO HYBRID PATHS

    公开(公告)号:US20200097010A1

    公开(公告)日:2020-03-26

    申请号:US16138513

    申请日:2018-09-21

    Abstract: Various software techniques for managing operation of autonomous vehicles based on sensor data are disclosed herein. A computing system may generate, based on a set of signals descriptive of a current state of an environment in which the autonomous vehicle is operating, a normal path plan separate from a safe path plan, or a hybrid path plan including a normal path plan and a safe path plan. In generating the safe path plan, the computing system may generate and concatenate a set of motion primitives. When a fault condition occurs, the computing device may transition from executing the normal path plan to executing the safe path plan to safely stop the autonomous vehicle.

    Autonomous vehicle technology for facilitating operation according to motion primitives

    公开(公告)号:US10394243B1

    公开(公告)日:2019-08-27

    申请号:US16138582

    申请日:2018-09-21

    Abstract: Various software techniques for managing operation of autonomous vehicles based on sensor data are disclosed herein. A computing system may generate, based on a set of signals descriptive of a current state of an environment in which the autonomous vehicle is operating, a normal path plan separate from a safe path plan, or a hybrid path plan including a normal path plan and a safe path plan. In generating the safe path plan, the computing system may generate and concatenate a set of motion primitives. When a fault condition occurs, the computing device may transition from executing the normal path plan to executing the safe path plan to safely stop the autonomous vehicle.

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