Abstract: Techniques described herein relate to lane handling, for instance to enable vehicles to perform turns without colliding into oncoming vehicles and/or bicycles in other lanes. System(s) associated with a vehicle can access sensor data and/or map data associated with an environment within which the vehicle is positioned in a first lane. The system(s) can determine that the vehicle is to perform a turn and a start of a second lane associated with the turn or a merging zone associated with the second lane. The system(s) can determine a location of the vehicle relative to the start of the second lane or the merging zone associated with the second lane and, based partly on the location, can cause the vehicle to merge into the second lane prior to performing the turn.

Abstract: Junction queueing for vehicles is described, in which vehicles may be queued based on arrival time at a junction, position relative to a stopping location at the junction, and/or an amount of time waiting for other vehicles to proceed through the junction (timeout). In some examples, the queue may be first generated based on the arrival times of any other vehicle relative to a particular vehicle generating the queue. The queue may be updated based on arrival times of other vehicles (e.g., after the particular vehicle), whether another vehicle has proceeded out-of-turn (e.g., based on a position at the junction), and/or a timeout for vehicles that wait for others to yield at the junction. In some examples, hysteresis and alterations of the score for safety reasons may alter queue order. The queue may be used to control the particular vehicle to traverse the junction.

Abstract: 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. An occlusion grid representing the occluded area can be stored as map data or can be dynamically generated. An occlusion grid can include occlusion fields, which represent discrete two- or three-dimensional areas of driveable environment. An occlusion field can indicate an occlusion state and an occupancy state, determined using LIDAR data and/or image data captured by the vehicle. An occupancy state of an occlusion field can be determined by ray casting LIDAR data or by projecting an occlusion field into segmented image data. The vehicle can be controlled to traverse the environment when a sufficient portion of the occlusion grid is visible and unoccupied.

Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.

Abstract: A vehicle safety system within an autonomous or semi-autonomous vehicle may predict and avoid collisions between the vehicle and other moving objects in the environment. The vehicle safety system may determine one or more perturbed trajectories for another object in the environment, for example, by perturbing the state parameters of a perceived trajectory associated with the object. Each perturbed trajectory may be evaluated to determine whether it intersects or potentially collides the planned trajectory of the vehicle. In some examples, the vehicle safety system may aggregate the results of analyses of multiple perturbed trajectories to determine a collision probability and/or additional weights or adjustment factors associated with the collision prediction, and may determine actions for the vehicle to take based on the collision predictions and probabilities.

Abstract: A system and method for regionalized resolution of a network path to one or more file types based on a specific sound or a specific combination of words, phrases and/or sounds. An application with a user interface at a networked device has access to a remote speech to text server via an advanced programmer interface (API) and to a regionalized, accessible database. The regionalized, accessible database can contain text translations of distinct words, phrases, and sounds along with region(s) where the entries are valid that are associated with distinct network paths. Converted audio in a searchable format and location of the networked device are queried at the global database for a match, if a match is found at the regionalized database for the query, the network path associated with the match is returned from the regionalized database to the networked device, and one or more files associated with the returned network path are opened at the networked device.

Abstract: Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on predicted 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. A first occluded region for an object is determined at a first time based on a location of the object. A predicted location for the object can be used to determine a predicted occluded region caused by the object at a second time after the first time. Predicted occluded regions can be determined for multiple trajectories for the vehicle to follow and/or at multiple points along such trajectories, and a trajectory can be selected based on associated occlusion scores and/or trajectory scores associated therewith. The vehicle can be controlled to traverse the environment based on the selected trajectory.

Abstract: Junction queueing for vehicles is described, in which vehicles may be queued based on arrival time at a junction, position relative to a stopping location at the junction, and/or an amount of time waiting for other vehicles to proceed through the junction (timeout). In some examples, the queue may be first generated based on the arrival times of any other vehicle relative to a particular vehicle generating the queue. The queue may be updated based on arrival times of other vehicles (e.g., after the particular vehicle), whether another vehicle has proceeded out-of-turn (e.g., based on a position at the junction), and/or a timeout for vehicles that wait for others to yield at the junction. In some examples, hysteresis and alterations of the score for safety reasons may alter queue order. The queue may be used to control the particular vehicle to traverse the junction.

Abstract: 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.

Abstract: 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.

Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.

Abstract: 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.

Abstract: Drive envelope determination is described. In an example, a vehicle can capture sensor data while traversing an environment and can provide the sensor data to computing system(s). The sensor data can indicate agent(s) in the environment and the computing system(s) can determine, based on the sensor data, a planned path through the environment relative to the agent(s). The computing system(s) can also determine lateral distance(s) to the agent(s) from the planned path. In an example, the computing system(s) can determine modified distance(s) based at least in part on the lateral distance(s) and information about the agents. The computing system can determine a drive envelope based on the modified distance(s) and can determine a trajectory in the drive envelope.

Abstract: 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. An occlusion grid representing the occluded area can be stored as map data or can be dynamically generated. An occlusion grid can include occlusion fields, which represent discrete two- or three-dimensional areas of driveable environment. An occlusion field can indicate an occlusion state and an occupancy state, determined using LIDAR data and/or image data captured by the vehicle. An occupancy state of an occlusion field can be determined by ray casting LIDAR data or by projecting an occlusion field into segmented image data. The vehicle can be controlled to traverse the environment when a sufficient portion of the occlusion grid is visible and unoccupied.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Drive envelope determination is described. In an example, a vehicle can capture sensor data while traversing an environment and can provide the sensor data to computing system(s). The sensor data can indicate agent(s) in the environment and the computing system(s) can determine, based on the sensor data, a planned path through the environment relative to the agent(s). The computing system(s) can also determine lateral distance(s) to the agent(s) from the planned path. In an example, the computing system(s) can determine modified distance(s) based at least in part on the lateral distance(s) and information about the agents. The computing system can determine a drive envelope based on the modified distance(s) and can determine a trajectory in the drive envelope.

Abstract: Techniques described herein relate to lane handling, for instance to enable vehicles to perform turns without colliding into oncoming vehicles and/or bicycles in other lanes. System(s) associated with a vehicle can access sensor data and/or map data associated with an environment within which the vehicle is positioned in a first lane. The system(s) can determine that the vehicle is to perform a turn and a start of a second lane associated with the turn or a merging zone associated with the second lane. The system(s) can determine a location of the vehicle relative to the start of the second lane or the merging zone associated with the second lane and, based partly on the location, can cause the vehicle to merge into the second lane prior to performing the turn.