Nuro Corp.

Sreeja Nag

Sarah Marie Thornton

According to one aspect, methods to validate an autonomy system using scenes of various complexities are provided. A computing device obtains a plurality of scenes. Each of the plurality of scenes represents an environment in which a vehicle is driven for a predetermined time. The computing device determines a complexity of each of the plurality of scenes based on characteristics of a respective scene and at least one maneuver required from an autonomous driving system to drive the vehicle through the respective scene without a collision. The computing device calculates a complexity score for each of the plurality of scenes based on the complexity determined for the respective scene and validates the autonomous driving system for driving the vehicle using a subset of the plurality of scenes selected based on the complexity score.

Methods and apparatus for assessing scenes

According to one aspect, methods to select and implement a failover behavior based on situational awareness, when an autonomous vehicle enters a failover condition, are provided. Operation design domains, other users who share a road with the autonomous vehicle, and tailgaters may be considered when determining a deceleration profile, a trajectory length, and a trajectory type for the autonomous vehicle to follow when executing failover behavior. An autonomous driving system of an autonomous vehicle detects a failover event while the autonomous vehicle is traveling along a path and analyzes an environment surrounding the autonomous vehicle to determine whether a tailgater is present behind the autonomous vehicle. The autonomous driving system generates a failover plan for performing a failover behavior based on the failover event and the environment surrounding the autonomous vehicle and engages the autonomous vehicle to implement the failover plan for performing the failover behavior.

Methods and apparatus for failover behavior of autonomous vehicles

According to one aspect, methods to validate an autonomy system in conjunction with a teleoperations system are provided. A computing device obtains simulation data of an autonomous driving system of a vehicle. The simulation data includes first environment data representing an environment in which the vehicle is driven using the autonomous driving system. The computing device obtains teleoperations driving data of a teleoperations driving system by which the vehicle is remotely controlled with an aid of a human. The teleoperations driving data includes second environment data representing the environment in which the vehicle is driven using the teleoperations driving system. The computing device determines whether the autonomous driving system in conjunction with the teleoperations driving system meets a minimum deployment standard based on the simulation data and the teleoperations driving data.

Framework for validating autonomy and teleoperations systems

According to one aspect, a method is provided to determine whether an autonomous system is ready to be deployed or is otherwise ready for use, scene-based metrics, or metrics based on instances of scenarios. Scene-based metrics are mapped, or otherwise translated, to distance-based metrics such that substantially standard distance-based metrics may be used to gate the readiness of an autonomy system for deployment.

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Mountain View, CA, United States of America

Sreeja Nag