Abstract: Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

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: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment in a drivable area. A location can be determined along the trajectory. A cost associated with the location can determined and can be evaluated with respect to a cost threshold. Further, the techniques can include determining, based at least in part on the cost meeting or exceeding the cost threshold, an action associated with the location, and controlling the autonomous vehicle to traverse the environment based at least in part on the action.

Abstract: Techniques for compensating for errors in position of a vehicle are discussed herein. In some cases, a discrepancy may exist between a measured state of the vehicle and a desired state as determined by a system of the vehicle. Techniques and methods for a planning architecture of an autonomous vehicle that is able to provide maintain a smooth trajectory as the vehicle follows a planned path or route. In some cases, a planning architecture of the autonomous vehicle may compensate for differences between an estimated state and a planned path without the use of a separate system. In this example process, the planning architecture may include a mission planning system, a decision system, and a tracking system that together output a trajectory for a drive system.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment in a first drivable area. An object within a distance threshold can be detected in the environment and a second drivable area can be determined. Further, the techniques can include determining a target trajectory based at least in part on the reference trajectory and/or the second drivable area which can provide a region for the object to traverse the environment, and controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment. A point density can be determined for various portions of the reference trajectory. In some cases, the point density can be based at least in part on a cost associated with a curvature value associated the reference trajectory or a cost associated with a distance between the reference trajectory and an obstacle in the environment. Further, the techniques can include evaluating a cost function at points on the reference trajectory to generate a target trajectory with respect to the reference trajectory, and controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

Abstract: A vehicle can include various sensors to detect objects in an environment. In some cases, the object may be within a planned path of travel of the vehicle. In these cases, leaving the planned path may be dangerous to the passengers so the vehicle may, based on dimensions of the object, dimensions of the vehicle, and semantic information of the object, determine operational parameters associate with passing the object while maintaining a position within the planned path, if possible.

Abstract: The present disclosure is directed to performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

Abstract: Acceleration determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, objects in an environment of the vehicle are identified and a probability that each object will impact travel of the vehicle is determined. Individual accelerations for responding to each object may also be determined. Weighting factors for each of the accelerations may also be determined based on the probabilities. A control acceleration may be determined based on the weighting factors and the accelerations.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment in a first drivable area. An object within a distance threshold can be detected in the environment and a second drivable area can be determined. Further, the techniques can include determining a target trajectory based at least in part on the reference trajectory and/or the second drivable area which can provide a region for the object to traverse the environment, and controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment in a drivable area. A location can be determined along the trajectory. A cost associated with the location can determined and can be evaluated with respect to a cost threshold. Further, the techniques can include determining, based at least in part on the cost meeting or exceeding the cost threshold, an action associated with the location, and controlling the autonomous vehicle to traverse the environment based at least in part on the action.

Abstract: Acceleration determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, objects in an environment of the vehicle are identified and a probability that each object will impact travel of the vehicle is determined. Individual accelerations for responding to each object may also be determined. Weighting factors for each of the accelerations may also be determined based on the probabilities. A control acceleration may be determined based on the weighting factors and the accelerations.

Abstract: Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment. Portions of the reference trajectory can be identified as corresponding to actions to navigate around a double-parked vehicle or to change lanes, for example. In some cases, a portion of the reference trajectory can be identified based on a proximity to an object in the environment. A weight can be associated with the portions of the reference trajectory, and the techniques can include evaluating a reference cost function at points of the reference trajectory based on the associated weights to generate a target trajectory. Further, the techniques can include controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

Abstract: Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment. A point density can be determined for various portions of the reference trajectory. In some cases, the point density can be based at least in part on a cost associated with a curvature value associated the reference trajectory or a cost associated with a distance between the reference trajectory and an obstacle in the environment. Further, the techniques can include evaluating a cost function at points on the reference trajectory to generate a target trajectory with respect to the reference trajectory, and controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

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: Trajectory determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, a vehicle system includes multiple planning systems for calculating trajectories. A first system may calculate first trajectories at a first frequency and the second system may calculate second trajectories at a second frequency and based on the first trajectories. The first and/or second trajectories may be initialized at states of the vehicle corresponding to a projection onto a previous-in-time respective first or second trajectory. The second trajectories may be control trajectories along which the vehicle is controlled.

Abstract: Acceleration determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, objects in an environment of the vehicle are identified and a probability that each object will impact travel of the vehicle is determined. Individual accelerations for responding to each object may also be determined. Weighting factors for each of the accelerations may also be determined based on the probabilities. A control acceleration may be determined based on the weighting factors and the accelerations.