Zoox, Inc.

Zhenqi Huang

William Anthony Silva

Jefferson Bradfield Packer

Andrew E Beller

Marin Kobilarov

Janek Hudecek

Mark Jonathon McClelland

Dhanushka Nirmevan Kularatne

A vehicle computing system may implement techniques to control a vehicle to avoid collisions between the vehicle and agents (e.g., dynamic objects) in an environment. The techniques may include generating a representation of a path of the vehicle through an environment as a polygon. The vehicle computing system may compare the two-dimensional path with a trajectory of an agent determined using sensor data to determine a collision zone between the vehicle and the agent. The vehicle computing system may determine a risk of collision based on predicted velocities and probable accelerations of the vehicle and the agent approaching and traveling through the collision zone. Based at least in part on the risk of collision, the vehicle computing system may cause the vehicle to perform an action.

Collision prediction and avoidance for vehicles

An autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a data structure generated based at least in part on sensor data that may indicate occupied space in an environment surrounding an autonomous vehicle. The guidance system may receive a grid and generate a grid associated with the grid and the data structure. The guidance system may additionally or alternatively sub-sample the grid (latterly and/or longitudinally) dynamically based at least in part on characteristics determined from the data structure. The guidance system may identify a path based at least in part on a set of precomputed motion primitives, costs associated therewith, and/or a heuristic cost plot that indicates a cheapest cost to move from one pose to another.

Unstructured vehicle path planner

Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Collision zone detection for vehicles

The techniques discussed herein may comprise an autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a static object map and/or one or more dynamic object maps. The guidance system may identify a path based at least in part on determining set of nodes and a cost map associated with the static and/or dynamic object, among other costs, pruning the set of nodes, and creating further nodes from the remaining nodes until a computational or other limit is reached. The path output by the techniques may be associated with a cheapest node of the sets of nodes that were generated.

Techniques and methods for providing additional safety for interactions with pedestrians. For instance, a vehicle may identify a region through which the vehicle and agent (such as a pedestrian) pass. The vehicle may determine a time buffer value and/or a distance buffer value based on the vehicle and the agent passing through the region. The vehicle may determine a time threshold and/or a distance threshold for passing through the region in the presence of the agent. The time threshold and/or the distance threshold may be based on a velocity of the vehicle, a safety factor, a hysteresis factor, a comfort factor, and/or an assertiveness factor. If the time buffer value is below the time threshold and/or the distance buffer value is below the distance threshold, the vehicle may yield to the agent. Otherwise, the vehicle may not yield to the agent within the region.

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Zhenqi Huang