US 9,632,502 B1 · Machine-learning systems and techniques to optimize teleoperation and/or planner decisions

Abstract

A system, an apparatus or a process may be configured to implement an application that applies artificial intelligence and/or machine-learning techniques to predict an optimal course of action (or a subset of courses of action) for an autonomous vehicle system (e.g., one or more of a planner of an autonomous vehicle, a simulator, or a teleoperator) to undertake based on suboptimal autonomous vehicle performance and/or changes in detected sensor data (e.g., new buildings, landmarks, potholes, etc.). The application may determine a subset of trajectories based on a number of decisions and interactions when resolving an anomaly due to an event or condition. The application may use aggregated sensor data from multiple autonomous vehicles to assist in identifying events or conditions that might affect travel (e.g., using semantic scene classification). An optimal subset of trajectories may be formed based on recommendations responsive to semantic changes (e.g., road construction).

Claims23

Dependent claims

A method, comprising:

receiving, from one or more of a sensor or a communication interface, telemetry data associated with an event, the event being a situation or condition associated with operation of an autonomous vehicle;
obtaining policy data, the policy data including instructions for operating an autonomous vehicle according to a trajectory and the policy data including a confidence level associated with the received trajectory, the confidence level indicating a degree of certainty that the autonomous vehicle, in operating according to the trajectory, will operate safely in view of the event;
obtaining candidate trajectories responsive to the event, based on the telemetry data, each candidate trajectory having an associated confidence level;
generating, by machine-learning by a processor and based at least in part on the candidate trajectories and the telemetry data, updated policy data that includes instructions for operating the autonomous vehicle responsive to the event differently than according to the policy data;
and
communicating the updated policy data to at least one autonomous vehicle via a communications interface.

3 more elements

A system comprising:

one or more processors;
a memory having stored thereon first criteria for controlling motion of an autonomous vehicle and a planner module executable by the one or more processors and that, when executed by the one or more processors, configure the system to perform operations including:
obtaining sensor data related to operation of an autonomous vehicle and an event;
determining, based at least on the sensor data and the first criteria, a first trajectory for operation of the autonomous vehicle responsive to the event;
receiving instructions for implementing a second trajectory for operation of the autonomous vehicle responsive to the event;
and
learning, from at least the instructions and the sensor data, second criteria to update the first criteria, the second criteria configuring the one or more processors to determine the second trajectory based at least on the sensor data and the instructions.

4 more elements

One or more non-transitory computer-readable media storing processor-executable instructions that, when executed, cause one or more processors to perform operations, the operations comprising:

receiving telemetry data associated with operation of an autonomous vehicle, the autonomous vehicle storing first criteria used by the autonomous vehicle to determine first trajectories to control motion of the autonomous vehicle from the telemetry data;
receiving instructions for the autonomous vehicle to operate according to a defined trajectory;
learning, from the instructions and the telemetry data, second criteria for determining second trajectories from the telemetry data, where the first trajectories and the second trajectories are different and the second criteria includes an update to the first criteria;
and
communicating the second criteria to at least one autonomous vehicle to update the first criteria of the at least one autonomous vehicle.

2 more elements

Dependencies are inferred from the claim text.

Machine-learning systems and techniques to optimize teleoperation and/or planner decisions

Life of this patent

Machine-learning systems and techniques to optimize teleoperation and/or planner decisions

Life of this patent

Abstract

Claims23