Zoox, Inc.

Max Gier

William Anthony Silva

Lichao Ma

Moritz Harmel

Akash Arora

A vehicle computing system may implement techniques to determine an action for a vehicle to perform based on a cost associated therewith. The cost may be based on a detected object (e.g., another vehicle, bicyclist, pedestrian, etc.) operating in the environment and/or a possible object associated with an occluded region (e.g., a blocked area in which an object may be located). The vehicle computing system may determine two or more actions the vehicle could take with respect to the detected object and/or the occluded region and may generate a simulation associated with each action. The vehicle computing system may run the simulation associated with each action to determine a safety cost, a progress cost, a comfort cost, an operational rules cost, and/or an occlusion cost associated with each action. The vehicle computing system may select the action for the vehicle to perform based on an optimal cost being associated therewith.

Cost-based action determination

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object or sensor limitation. An occluded region for an object is determined, along with one or more visible regions proximate the occluded region. Entry and/or exit regions may be determined based on known directions of traffic and/or drivable surface boundaries. Based on a threshold speed, the vehicle can designate portions of the occluded region as pseudo-visible. Additionally, if a dynamic object traverses through the occluded region from the entry region, a portion of the occluded region may be considered pseudo-visible. Pseudo-visibility may also be determined based on movement of an occluded area. The vehicle can be controlled to traverse the environment based on the pseudo-visibility.

Determining occupancy of occluded regions

A vehicle can traverse an environment along a first region and detect an obstacle impeding progress of the vehicle. The vehicle can determine a second region that is adjacent to the first region and associated with a direction of travel opposite the first region. The vehicle can use a state machine to determine an action (e.g., an oncoming action) to utilize the second region to overtake the obstacle. By comparing a cost to a cost threshold and/or to a cost associated with another action (e.g., a 'stay in lane' action), the vehicle, using the state machine, can determine a target trajectory that traverses through the second region and can traverse the environment based on the target trajectory to avoid, for example, the obstacle in the environment while maintaining a safe distance from the obstacle and/or other entities in the environment.

State machine for obstacle avoidance

A vehicle can traverse an environment along a first region and detect an obstacle impeding progress of the vehicle. The vehicle can determine a second region that is adjacent to the first region and associated with a direction of travel opposite the first region. A cost can be determined based on an action (e.g., an oncoming action) to utilize the second region to overtake the obstacle. By comparing the cost to a cost threshold and/or to a cost associated with another action (e.g., a 'stay in lane' action), the vehicle can determine a target trajectory that traverses through the second region. The vehicle can traverse the environment based on the target trajectory to avoid, for example, the obstacle in the environment while maintaining a safe distance from the obstacle and/or other entities in the environment.

Obstacle avoidance action

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, to navigate a junction in an environment. In some cases, the techniques can be used to navigate a turn at the junction or traverse through the junction. Operations include the vehicle detecting a stop signal and preparing the vehicle to stop at a location associated with the junction. The vehicle can determine a time to execute a maneuver and a visibility distance that a sensor can observe in the environment. A speed of the vehicle to execute the maneuver can be determined based on the time to execute the maneuver and the visibility distance.

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Aachen, Germany

Max Gier